Optimizing beta-lactam antibiotic dosing in critically ill ...393365/s... · Optimizing beta-lactam antibiotic dosing in critically ill patients: Prolonged infusion versus intermittent

Optimizing beta-lactam antibiotic dosing in critically ill patients:

Prolonged infusion versus intermittent bolus administration

Mohd Hafiz Abdul Aziz

BPharm (Hons), MClinPharm

A thesis submitted for the degree of Doctor of Philosophy at

The University of Queensland in 2015

School of Medicine

i

Abstract

Severe sepsis is a major burden in the intensive care unit (ICU) with persistently high mortality

rates. Optimization of antibiotic dosing has been suggested as an intervention to improve clinical

outcomes for critically ill patients with severe sepsis. However, current antibiotic dosing guidelines

may not be appropriate for these patients, as they rarely consider the altered physiology and illness

severity associated with this population. Optimizing antibiotic dosing using pharmacokinetic (PK)

and pharmacodynamic (PD) principles can address these critical illness-related changes and

promote therapeutic success. Due to their wide spectrum of antibiotic activity and excellent safety

profile, beta-lactam antibiotics are commonly used for severe infections in the ICU. Two alternative

dosing approaches to traditional intermittent bolus (IB) dosing, namely continuous infusion (CI)

and extended infusion (EI), have been suggested to maximize the therapeutic potential of these

antibiotics in critically ill patients. Collectively, the two dosing approaches can also be referred as

prolonged infusion (PI).

This Thesis aims to better characterize the pharmacokinetics/pharmacodynamics (PK/PD) of beta-

lactam antibiotics to determine whether there is any therapeutic advantage associated with PI dosing

(CI and/or EI) as compared to IB dosing.

This Thesis comprises of eight chapters. Chapter 1 is an introductory chapter which provides an

overview of the published literature on the area of research. The discussion in Chapter 1 presents a

theoretical framework behind the Thesis objectives. Chapter 1 concludes with the specific aims of

this Thesis.

Chapter 2 reports the findings of a prospective PK study which aimed to describe the population PK

of doripenem in critically ill patients with sepsis and perform dosing simulations to develop

clinically relevant dosing guidelines for these patients. Twelve critically ill participants receiving

500 mg of doripenem 8-hourly as a 1-hr infusion were enrolled. The volume of distribution (Vd)

and clearance (CL) of doripenem in this patient cohort were substantially different than those

usually described in non-critically patients. As current dosing guidelines were mostly derived from

the non-critically ill, findings from this study suggest that the licensed “one-dose-fits-all” dosing for

doripenem is unlikely to achieve optimal exposures in critically ill patients. Empirical use of PI

dosing should be considered to account for PK and illness severity differences, particularly when

less-susceptible pathogens are involved.

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Chapter 3 incorporates a published systematic review which compares the PK/PD data and clinical

outcomes between CI and IB dosing to describe any potential merits supporting either of the two

dosing approaches for critically ill patients. The findings suggest that beta-lactam CI may not be

advantageous for all critically ill patients and may be beneficial in patients with severe infections.

Chapter 4 describes the findings of a post hoc analysis on the Defining Antibiotic Levels in

Intensive care unit patients (DALI) study, which recruited critically ill patients from 68 ICUs across

10 countries. The analysis aimed to compare the PK/PD target attainment and clinical outcomes

between PI (CI and EI) and IB dosing of meropenem and piperacillin/tazobactam in 182 critically

ill patients. In this analysis, PI dosing significantly increased the target attainment for most PK/PD

end-points. Data from this chapter also suggest that the critically ill patients who are most likely to

benefit from altered dosing strategies are those with severe pneumonia and not receiving renal

replacement therapy (RRT).

Chapter 5 is a published review article which scrutinizes the methodology of clinical studies

comparing CI versus IB dosing of beta-lactam antibiotics. Several issues and problems in the

interpretation of results obtained from these studies are discussed. This finally led to a proposal of

how a methodologically robust study should be performed to test the clinical outcome differences of

CI versus IB dosing of beta-lactam antibiotics in critically ill patients.

Chapter 6 reports the findings of the Beta-Lactam In Severe Sepsis (BLISS) study, which was a

two-centre, randomized controlled trial of CI versus IB dosing of beta-lactam antibiotics, enrolling

140 critically ill participants with severe sepsis who were not on RRT. This study aimed to

determine if CI is associated with better clinical outcomes and PK/PD target attainment in critically

ill patients, as opposed to IB dosing. In this study, CI of beta-lactam antibiotics demonstrated higher

clinical cure rates and better PK/PD target attainment than IB dosing. The findings suggest that

beta-lactam CI may be most beneficial for critically ill patients with severe infections, who are

infected with less-susceptible microorganisms.

Chapter 7 incorporates a published review article which systematically analyses the relevance of

PK/PD characteristics of antibiotics and their potential roles in maximizing patient outcomes and

preventing the emergence of antibiotic resistance. Based on the collated data, dosing approaches

which are likely to reduce the risk of antibiotic resistance in the ICU were also proposed.

iii

Chapter 8 will be the final chapter in this Thesis and summarizes the clinical findings of all the

work and highlight potential areas of future research.

iv

Declaration by author

This thesis is composed of my original work, and contains no material previously published or

written by another person except where due reference has been made in the text. I have clearly

stated the contribution by others to jointly-authored works that I have included in my thesis.

I have clearly stated the contribution of others to my thesis as a whole, including statistical

assistance, survey design, data analysis, significant technical procedures, professional editorial

advice, and any other original research work used or reported in my thesis. The content of my thesis

is the result of work I have carried out since the commencement of my research higher degree

candidature and does not include a substantial part of work that has been submitted to qualify for

the award of any other degree or diploma in any university or other tertiary institution. I have

clearly stated which parts of my thesis, if any, have been submitted to qualify for another award.

I acknowledge that an electronic copy of my thesis must be lodged with the University Library and,

subject to the policy and procedures of The University of Queensland, the thesis be made available

for research and study in accordance with the Copyright Act 1968 unless a period of embargo has

been approved by the Dean of the Graduate School.

I acknowledge that copyright of all material contained in my thesis resides with the copyright

holder(s) of that material. Where appropriate I have obtained copyright permission from the

copyright holder to reproduce material in this thesis.

v

Publications during candidature

Published manuscript

Mohd Hafiz AA, Staatz CE, Kirkpatrick CM, Lipman J, Roberts JA. Continuous infusion vs. bolus

dosing: implications for beta-lactam antibiotics. Minerva Anestesiologica 2012; 78(1): 94-104.

Abdul-Aziz MH, Dulhunty JM, Bellomo R, Lipman J, Roberts JA. Continuous beta-lactam

infusion in critically ill patients: the clinical evidence. Annals of Intensive Care 2012; 2(1): 37.

Jamal JA, Abdul-Aziz MH, Lipman J, Roberts JA. Defining antibiotic dosing in lung infections.

Clinical Pulmonary Medicine 2013; 20(3): 121-128.

Roberts JA, Abdul-Aziz MH, Lipman J, Mouton JW, Vinks AA, Felton TW, Hope WW, Farkas A,

Neely MN, Schentag JJ, Drusano G, Frey OR, Theuretzbacher U, Kuti JL. Individualised antibiotic

dosing for patients who are critically ill: challenges and potential solutions. Lancet Infectious

Diseases 2014; 14(6): 498-509.

Abdul-Aziz MH, McDonald C, McWhinney B, Ungerer JP, Lipman J, Roberts JA. Low

flucloxacillin concentrations in a patient with central nervous system infection: the need for plasma

and cerebrospinal fluid drug monitoring in the ICU. Annals of Pharmacotherapy 2014; 48(10):

1380-1384.

Abdul-Aziz MH, Lipman J, Mouton JW, Hope WW, Roberts JA. Applying

pharmacokinetic/pharmacodynamic principles in critically ill patients: optimizing efficacy and

reducing resistance development. Seminars in Respiratory and Critical Care Medicine 2015; 36(1):

136-153.

Abdul-Aziz MH, Abd Rahman AN, Mat-Nor MB, Sulaiman H, Wallis SC, Lipman J, Roberts JA,

Staatz CE. Population pharmacokinetics of doripenem in critically ill patients with sepsis in a

Malaysian intensive care unit. Antimicrobial Agents and Chemotherapy 2015; 60(1): 206-214.

Abdul-Aziz MH, Lipman J, Akova M, Bassetti M, De Waele JJ, Dimopoulos G, Dulhunty J,

Kaukonen KM, Koulenti D, Martin C, Montravers P, Rello J, Rhodes A, Starr T, Wallis SC,

Roberts JA, DALI Study Authors. Is prolonged infusion of piperacillin/tazobactam and meropenem

vi

in critically ill patients associated with improved pharmacokinetic/pharmacodynamic and patient

outcomes? An observation from the Defining Antibiotic Levels in Intensive care unit patients

(DALI) cohort. Journal of Antimicrobial Chemotherapy 2016; 71(1): 196-207.

Alobaid AS, Brinkman A, Frey OR, Roehr AC, Luque S, Grau S, Wong G, Abdul-Aziz MH,

Roberts MS, Lipman J, Roberts JA. What is the effect of obesity on piperacillin and meropenem

trough concentrations in critically ill patients? Journal of Antimicrobial Chemotherapy 2016; 71(3):

696-702.

Abdul-Aziz MH, Helmi S, Mat-Nor MB, Rai V, Wong KK, Hasan MS, Abd Rahman AN, Jamal

JA, Wallis SC, Lipman J, Staatz CE, Roberts JA. BLISS: Beta-Lactam Infusion in Severe Sepsis: a

prospective, two-centre, open-labelled, randomized controlled trial of continuous versus intermittent

beta-lactam infusion in critically ill patients with severe sepsis. Intensive Care Medicine 2016.

Roberts JA, Abdul-Aziz MH, Davis JS, Dulhunty JM, Cotta MO, Myburgh J, Bellomo R, Lipman

J. Continuous versus intermittent beta-lactam infusion in severe sepsis: a meta-analysis of

individual patient data from randomized trials. Am J Respir Crit Care Med 2016.

Conference abstracts

Oral presentation at international conference

Abdul-Aziz MH, Sulaiman H, Mat-Nor MB, Rai V, Wong KK, Hasan MS, Wallis SC, Lipman J,

Staatz CE, Roberts JA. The BLISS Study: Beta-Lactam Infusion in Severe Sepsis: Randomized

controlled trial of continuous versus intermittent beta-lactam infusion in critically ill patients with

severe sepsis in a Malaysian ICU setting. 55th Interscience Conference on Antimicrobial Agents and

Chemotherapy (ICAAC), San Diego, USA, 17-21st September 2015.

Poster presentations

Abdul-Aziz MH, Roberts JA, Akova, Bassetti M, De Waele JJ, Dimopoulos G, Kaukonen KM,

Koulenti D, Martin C, Montravers P, Rello J, Rhodes A, Starr T, Wallis SC, Lipman J. DALI:

Defining Antibiotic Levels in Intensive care unit patients: prolonged infusion of beta-lactam

antibiotics in critically ill patients. 53rd Interscience Conference on Antimicrobial Agents and

Chemotherapy (ICAAC), Denver, USA, 10-13th September 2013.

vii

Abdul-Aziz MH, Udy AA, Wallis SC, Roberts MS, Lipman J, Roberts JA. Plasma and

subcutaneous tissue pharmacokinetics of piperacillin in a large cohort of critically ill patients with

sepsis. 24th European Congress of Clinical Microbiology and Infectious Diseases (ECCMID),

Barcelona, Spain, 10-13th May 2014.

viii

Publications included in this thesis

Abdul-Aziz MH, Abd Rahman AN, Mat-Nor MB, Sulaiman H, Wallis SC, Lipman J, Roberts JA,

Staatz CE. Population pharmacokinetics of doripenem in critically ill patients with sepsis in a

Malaysian intensive care unit. Antimicrobial Agents and Chemotherapy 2015; 60(1): 206-214 –

incorporated as Chapter 2.

Contributor Statement of contribution

Mohd Hafiz Abdul-Aziz (Candidate) Conception and design of the study (60%)

Literature review (70%)

Data collection (70%)

Bioanalysis (30%)

Pharmacokinetic/pharmacodynamic analysis (50%)

Preparation of the manuscript (100%)

Azrin N. Abd Rahman Data collection (10%)


Critical review of the manuscript (10%)

Mohd-Basri Mat-Nor Data collection (20%)


Helmi Sulaiman Critical review of the manuscript (10%)

Steven C. Wallis Bioanalysis (70%)


Jeffrey Lipman Critical review of the manuscript (10%)

Jason A. Roberts Conception and design of the study (20%)




Christine E. Staatz Conception and design of the study (20%)




ix

Mohd Hafiz AA, Staatz CE, Kirkpatrick CM, Lipman J, Roberts JA. Continuous infusion vs. bolus

dosing: implications for beta-lactam antibiotics. Minerva Anestesiologica 2012; 78(1): 94-104 –



Mohd Hafiz Abdul-Aziz (Candidate) Conception and design of the manuscript (30%)



Christine E. Staatz Critical review of the manuscript (40%)

Carl M. J. Kirkpatrick Critical review of the manuscript (10%)

Jeffrey Lipman Conception and design of the manuscript (20%)


Jason A. Roberts Conception and design of the manuscript (50%)



Abdul-Aziz MH, Lipman J, Akova M, Bassetti M, De Waele JJ, Dimopoulos G, Dulhunty J,


Roberts JA, DALI Study Authors. Is prolonged infusion of piperacillin/tazobactam and meropenem

in critically ill patients associated with improved pharmacokinetic/pharmacodynamic and patient


(DALI) cohort. Journal of Antimicrobial Chemotherapy 2016; 71(1): 196-207 – incorporated as

Chapter 4.


Mohd Hafiz Abdul-Aziz (Candidate) Literature review (50%)

Bioanalysis (20%)

Data analysis (70%)


Jeffrey Lipman Conception and design of the study (50%)

Critical review (5%)

Murat Akova Data collection (5%)


x

Matteo Bassetti Data collection (5%)


Jan J. De Waele Literature review (10%)



George Dimopoulos Data collection (5%)


Joel Dulhunty Data analysis (15%)


Kirsi M. Kaukonen Data collection (5%)


Despoina Koulenti Data collection (5%)


Claude Martin Data collection (5%)


Philippe Montravers Data collection (5%)


Jordi Rello Literature review (10%)



Andrew Rhodes Data collection (5%)


Therese Starr Data collection (50%)






Data analysis (15%)


xi

Abdul-Aziz MH, Dulhunty JM, Bellomo R, Lipman J, Roberts JA. Continuous beta-lactam

infusion in critically ill patients: the clinical evidence. Annals of Intensive Care 2012; 2(1): 37 –






Joel M. Dulhunty Critical review of the manuscript (20%)

Rinaldo Bellomo Conception and design of the manuscript (20%)







Abdul-Aziz MH, Helmi S, Mat-Nor MB, Rai V, Wong KK, Hasan MS, Abd Rahman AN, Jamal

JA, Wallis SC, Lipman J, Staatz CE, Roberts JA. BLISS: Beta-Lactam Infusion in Severe Sepsis: a

prospective, two-centre, open-labelled, randomized controlled trial of continuous versus intermittent

beta-lactam infusion in critically ill patients with severe sepsis. Intensive Care Medicine 2016 –



Mohd Hafiz Abdul-Aziz (Candidate) Conception and design of the study (50%)



Bioanalysis (30%)

Data analysis (70%)


Helmi Sulaiman Conception and design of the study (10%)



xii

Mohd-Basri Mat-Nor Conception and design of the study (10%)


Vineya Rai Data collection (10%)


Kang K. Wong Data collection (10%)


Mohd S. Hasan Data collection (10%)


Azrin N. Abd Rahman Data collection (10%)


Janattul-Ain Jamal Bioanalysis (10%)




Jeffrey Lipman Data analysis (10%)


Christine E. Staatz Critical review (20%)



Data analysis (20%)


Abdul-Aziz MH, Lipman J, Mouton JW, Hope WW, Roberts JA. Applying

pharmacokinetic/pharmacodynamic principles in critically ill patients: optimizing efficacy and

reducing resistance development. Seminars in Respiratory and Critical Care Medicine 2015; 36(1):

136-153 – incorporated as Chapter 7.







xiii

Johan W. Mouton Conception and design of the manuscript (30%)



William W. Hope Literature review (10%)





xiv

Contributions by others to the thesis

The contributions of others to study conception, data collection, sample processing and bioanalysis,

data analysis, drafting and critical review of the manuscripts arising from this Thesis are detailed in

each chapter. Additional contributions of others are described in the acknowledgement section of

each chapter of the Thesis.

Statement of parts of the thesis submitted to qualify for the award of another

degree

None

xv

Acknowledgements

I would like to acknowledge the scholarship provided by the Ministry of Education, Malaysia as

well as the research funds granted by the International Islamic University of Malaysia, all of which

has allowed me to perform and complete the planned projects.

The work presented in this Thesis has stemmed from significant contributions of time and effort

from a number of individuals. First and foremost, I am hugely indebted and would like to pay

homage to my principal advisor, Prof. Jason Roberts. This work would not have been possible

without your guidance and continual support. Having read a lot of your previous works, I never

thought that one day I would be meeting you, let alone being accepted as one of your students.

Thank you for your “leap of faith” on me and I hope you have not regretted that decision.

Throughout this challenging journey, you have been my teacher, my guide, my consultant, my

advisor, my problem solver and most importantly, my mentor. If I can be half as good as you are

now, I will consider myself blessed!

I would also like to express my deepest appreciation to my co-advisors, Dr. Christine Staatz and

Prof. Jeffrey Lipman, for their indispensable words of encouragement and unwavering support

offered to me throughout this journey. I am extremely indebted for the amount of time they set aside

for my studies, particularly for reading my manuscripts! I have learnt a lot from these two

individuals on hard work and it has been such a great honour to have been working with them.

I would like to thank everyone at the Burns, Trauma and Critical Care Research Centre (BTCCRC)

for having me and making this journey a smooth and a memorable one. Special thanks go to Dr.

Steven Wallis and Suzanne Parker-Scott. Had I known them earlier, I would most likely choose to

be a chemist rather than a pharmacist! My thanks are also reserved for Jenny Ordonez and Yamarly

Guerra, for without their help, I would have not completed the bioanalysis of all samples within the

stipulated time.

To my beautiful wife, Nurul Azrin Abd Rahman, thank you for joining me in this highly-emotional

roller coaster ride. You remained by my side through thick and thin, through all of its ups and

downs, as we made our way through the ebbs and flows of this emotional journey. Your tolerance

towards my “behaviours” and “carelessness” throughout these years is a testament of your

unflinching support and devotion. You’re the most intelligent and analytical person I have ever

known bar none, and with you by my side it feels that I can do anything.

xvi

To my dearest Mom, Norhaini Osman, this Thesis is dedicated for you. You’re the reason why I’m

here today and thank you for giving me all the things that I ever wanted in this life. You have

always stood by me like a firm rock, a pillar in my time of need and everything I have achieved in

this life, I absolutely owe them to you.

xvii

Keywords

Beta-lactam antibiotics, cefepime, continuous infusion, critically ill, doripenem, intermittent bolus,

meropenem, pharmacokinetics, pharmacodynamics, piperacillin/tazobactam.

Australian and New Zealand Standard Research Classifications (ANZSRC)

ANZSRC code: 11502, Clinical Pharmacology and Therapeutics, 50%

ANZSRC code: 110309, Infectious Disease, 25%

ANZSRC code: 110310, Intensive Care, 25%

Fields of Research (FoR) Classification

FoR code: 1103, Clinical Sciences, 80%

FoR code: 1115, Pharmacology and Pharmaceutical Sciences, 20%

xviii

Table of contents

Abstract ................................................................................................................................................ i

Declaration by author ....................................................................................................................... iv

Publications during candidature ...................................................................................................... v

Publications included in this thesis ................................................................................................ viii

Contributions by others to the thesis............................................................................................. xiv

Statement of parts of the thesis submitted to qualify for the award of another degree ........... xiv

Acknowledgements........................................................................................................................... xv

Keywords ........................................................................................................................................ xvii

Australian and New Zealand Standard Research Classifications (ANZSRC) ......................... xvii

Fields of Research (FoR) Classification ....................................................................................... xvii

Table of contents ........................................................................................................................... xviii

List of Tables ................................................................................................................................. xxvi

List of Figures ................................................................................................................................ xxix

Abbreviations ............................................................................................................................... xxxii

Chapter 1: Introduction and literature overview ......................................................................... 1

1.1 Introduction ........................................................................................................................... 1

1.2 Applied clinical pharmacology of antibiotics ....................................................................... 1

1.2.1 Pharmacokinetic considerations ................................................................................. 1

1.2.2 Pharmacodynamic considerations .............................................................................. 2

1.2.3 Bacterial kill characteristics of different antibiotics .................................................... 2

1.3 Sepsis ..................................................................................................................................... 3

1.4 Pathophysiological changes in critically ill patients with sepsis that can affect drug

pharmacokinetics .............................................................................................................................. 4

1.4.1 Changes of volume of distribution ............................................................................. 5

1.4.1.1 Tissue perfusion and target site distribution of antibiotics......................................... 6

1.4.1.2 Protein binding and hypoalbuminaemia ..................................................................... 6

1.4.2 Changes in drug clearance.......................................................................................... 7

1.4.2.1 Increase in cardiac output and augmented renal clearance ........................................ 7

1.4.2.2 End-organ dysfunction ............................................................................................... 7

1.4.2.3 Extra-corporeal circuits .............................................................................................. 8

1.4.3 Beta-lactam antibiotics and their pharmacokinetic and pharmacodynamic properties . 8

xix

1.4.4 Pharmacokinetic and pharmacodynamic considerations for critically ill patients with

sepsis……………………………………………………………………………………………………10

1.4.5 Continuous beta-lactam infusion .............................................................................. 12

1.4.5.1 In vitro models simulating human pharmacokinetics ............................................... 12

1.4.5.2 In vivo animal studies ............................................................................................... 12

1.4.5.3 Clinical outcomes ..................................................................................................... 13

1.4.6 Extended beta-lactam infusion ................................................................................. 22

1.4.6.1 Doripenem ................................................................................................................ 23

1.4.7 Summary ................................................................................................................. 25

Aims ................................................................................................................................................... 26

Chapter 2: Population pharmacokinetics of doripenem in critically ill patients with sepsis.. 27

2.1 Synopsis............................................................................................................................... 27

2.2 Manuscript entitled “Population pharmacokinetics of doripenem in critically ill patients

with sepsis in a Malaysian intensive care unit” .............................................................................. 28

2.2.1 Abstract ................................................................................................................... 30

2.2.2 Introduction ............................................................................................................. 31

2.2.3 Materials and methods ............................................................................................. 32

2.2.3.1 Setting ....................................................................................................................... 32

2.2.3.2 Study population....................................................................................................... 32

2.2.3.3 Doripenem administration and ancillary treatments ................................................ 32

2.2.3.4 Study protocol .......................................................................................................... 33

2.2.3.5 Doripenem assay ...................................................................................................... 33

2.2.3.6 Population pharmacokinetic analysis ....................................................................... 34

2.2.3.6.1 Software .............................................................................................................. 34

2.2.3.6.2 Structural and stochastic model development .................................................... 34

2.2.3.6.3 Covariate screening and model development ..................................................... 34

2.2.3.6.4 Model evaluation and prediction ........................................................................ 35

2.2.3.6.5 Dosing simulations ............................................................................................. 35

2.2.4 Results ..................................................................................................................... 36

xx

2.2.4.1 Demographic and clinical data ................................................................................. 36

2.2.4.2 Pharmacokinetic model-building ............................................................................. 36

2.2.4.3 Dosing simulations ................................................................................................... 40

2.2.5 Discussion ............................................................................................................... 41

2.2.6 Conclusions ............................................................................................................. 44

2.2.7 Acknowledgments ................................................................................................... 45

2.3 Conclusion ........................................................................................................................... 46

Chapter 3: Continuous beta-lactam infusion in critically ill patients: a structured review of

published literatures ........................................................................................................................ 47

3.1 Synopsis............................................................................................................................... 47

3.2 Manuscript entitled “Continuous infusion vs. bolus dosing: implications for beta-lactam

antibiotics”...................................................................................................................................... 48

3.2.1 Abstract ................................................................................................................... 50

3.2.2 Introduction ............................................................................................................. 51

3.2.3 The Pharmacodynamics of Beta-lactams .................................................................. 52

3.2.4 Comparative Studies between Intermittent and Continuous Administration .............. 52

3.2.4.1 Plasma Pharmacokinetics ......................................................................................... 52

3.2.4.1.1 Critically ill ......................................................................................................... 56

3.2.4.1.2 Peri-operative non-infected patients ................................................................... 56

3.2.4.1.3 Cystic fibrosis ..................................................................................................... 56

3.2.4.1.4 Cancer patients .................................................................................................... 57

3.2.4.1.5 Paediatric population .......................................................................................... 57

3.2.4.2 Tissue pharmacokinetics .......................................................................................... 58

3.2.4.3 Clinical outcomes ..................................................................................................... 59

3.2.4.3.1 Mortality ............................................................................................................. 60

3.2.4.3.2 Clinical cure ........................................................................................................ 60

3.2.4.3.3 Severity of Illness ............................................................................................... 62

3.2.4.3.4 Fever resolution/white blood cell normalization ................................................ 62

3.2.4.3.5 Mechanical ventilation ........................................................................................ 62

3.2.4.3.6 Length of ICU/hospital stay ................................................................................ 62

xxi

3.2.4.3.7 Adverse events .................................................................................................... 63

3.2.4.4 Other considerations ................................................................................................. 63

3.2.4.4.1 Stability Issues .................................................................................................... 63

3.2.5 Conclusions ............................................................................................................. 67

3.3 Conclusion ........................................................................................................................... 68

Chapter 4: Prolonged beta-lactam infusion in critically ill patients: a post hoc analysis on a

large dataset of critically ill patients .............................................................................................. 69

4.1 Synopsis............................................................................................................................... 69

4.2 Manuscript entitled “Is prolonged infusion of piperacillin/tazobactam and meropenem in

critically ill patients associated with improved pharmacokinetic/pharmacodynamic and patient


(DALI) cohort” ............................................................................................................................... 70

4.2.1 Abstract ................................................................................................................... 73

4.2.1.1 Objectives ................................................................................................................. 73

4.2.1.2 Methods .................................................................................................................... 73

4.2.1.3 Results ...................................................................................................................... 73

4.2.1.4 Conclusions .............................................................................................................. 73

4.2.2 Introduction ............................................................................................................. 74

4.2.3 Materials and methods ............................................................................................. 75

4.2.3.1 Study design ............................................................................................................. 75

4.2.3.2 Sample integrity and bioanalysis .............................................................................. 75

4.2.3.3 Pharmacokinetic/pharmacodynamic and clinical outcome measures ...................... 75

4.2.3.4 Statistical analysis .................................................................................................... 77

4.2.4 Results ..................................................................................................................... 77

4.2.4.1 Pharmacokinetic/pharmacodynamic and clinical outcome measures ...................... 81

4.2.4.2 Outcome measures predictors .................................................................................. 82

4.2.5 Discussion ............................................................................................................... 89

4.2.6 Conclusion ............................................................................................................... 91

4.2.7 Acknowledgements .................................................................................................. 92

4.2.7.1 Authors’ Contribution .............................................................................................. 92

xxii

4.2.7.2 Members of the DALI Study group ......................................................................... 92

4.2.7.3 Funding information ................................................................................................. 98

4.2.7.4 Transparency declarations ........................................................................................ 99

4.3 Conclusion ......................................................................................................................... 100

Chapter 5: The ideal characteristics of a clinical trial investigating continuous infusion

versus intermittent bolus dosing of beta-lactam antibiotics....................................................... 101

5.1 Synopsis............................................................................................................................. 101

5.2 Manuscript entitled “Continuous beta-lactam infusion in critically ill patients: the clinical

evidence” ...................................................................................................................................... 102

5.2.1 Abstract ................................................................................................................. 104

5.2.2 Introduction ........................................................................................................... 105

5.2.3 PK/PD considerations ............................................................................................ 109

5.2.3.1 Inconsistent PD end-points for comparison ........................................................... 109

5.2.3.2 The role of post-antibiotic effect ............................................................................ 110

5.2.3.3 Revision in antibiotic breakpoints .......................................................................... 110

5.2.3.4 The role of optimal PK/PD targets in the prevention of antibiotic resistance ........ 110

5.2.4 Controversies surrounding data interpretation ........................................................ 111

5.2.4.1 Heterogeneous patient populations ........................................................................ 115

5.2.4.2 Inclusion of patients with a low level of illness severity ....................................... 115

5.2.4.3 Inconsistent antibiotic dosing regimen ................................................................... 116

5.2.4.4 Pathogens with low MIC values ............................................................................. 116

5.2.4.5 Concomitant administration of other antibiotics .................................................... 117

5.2.4.6 Insufficient sample sizes ........................................................................................ 117

5.2.5 Other relevant concerns ......................................................................................... 118

5.2.6 Methodology concerns and the proposed characteristics of an “ideal” trial ............. 118

5.2.7 Conclusion ............................................................................................................. 122

5.3 Conclusion ......................................................................................................................... 123

xxiii

Chapter 6: Continuous beta-lactam infusion in critically ill patients with severe sepsis: A

prospective, two-centre, open-labelled, randomized controlled trial ........................................ 124

6.1 Synopsis............................................................................................................................. 124

6.2 Manuscript entitled “BLISS: Beta-Lactam Infusion in Severe Sepsis: a prospective, two-

centre, open-labelled, randomized controlled trial of continuous versus intermittent beta-lactam

infusion in critically ill patients with sepsis” ............................................................................... 125

6.2.1 Abstract ................................................................................................................. 128

6.2.1.1 Purpose ................................................................................................................... 128

6.2.1.2 Methods .................................................................................................................. 128

6.2.1.3 Results .................................................................................................................... 128

6.2.1.4 Conclusions ............................................................................................................ 128

6.2.2 Introduction ........................................................................................................... 129

6.2.3 Methods ................................................................................................................. 130

6.2.3.1 Study design ........................................................................................................... 130

6.2.3.2 Participants and randomization .............................................................................. 130

6.2.3.3 Intervention ............................................................................................................ 130

6.2.3.4 Outcomes and measurements ................................................................................. 132

6.2.3.5 Pharmacokinetic sampling and bioanalysis ............................................................ 134

6.2.3.6 Sample size calculations ......................................................................................... 135

6.2.3.7 Statistical analysis .................................................................................................. 135

6.2.4 Results ................................................................................................................... 136

6.2.4.1 Baseline demographics and clinical characteristics ............................................... 136

6.2.4.2 Outcome measures ................................................................................................. 140

6.2.4.3 Outcome measures predictors ................................................................................ 141

6.2.4.4 Pharmacokinetic/pharmacodynamic data ............................................................... 154

6.2.4.5 Adverse events ....................................................................................................... 155

6.2.5 Discussion ............................................................................................................. 156

6.2.6 Conclusion ............................................................................................................. 158

6.3 Conclusion ......................................................................................................................... 159

xxiv

Chapter 7: Optimizing antibiotic treatment in critically ill patients via

pharmacokinetic/pharmacodynamic principles .......................................................................... 160

7.1 Synopsis............................................................................................................................. 160

7.2 Manuscript entitled “Applying pharmacokinetic/pharmacodynamic principles in critically

ill patients: optimizing efficacy and reducing resistance development” ...................................... 161

7.2.1 Abstract ................................................................................................................. 163

7.2.2 Introduction ........................................................................................................... 164

7.2.3 Applied clinical pharmacology of antibiotics ......................................................... 165

7.2.3.1 Pharmacokinetic considerations ............................................................................. 166

7.2.3.2 Pharmacodynamic considerations .......................................................................... 166

7.2.4 Pharmacokinetic/pharmacodynamic considerations and the resistance descriptors.. 168

7.2.4.1 Mutant selection window ....................................................................................... 169

7.2.4.2 Mutant prevention concentration............................................................................ 170

7.2.4.3 Application of experimental mixture models ......................................................... 171

7.2.5 Specific antibiotic classes ...................................................................................... 171

7.2.5.1 Quinolones.............................................................................................................. 172

7.2.5.2 Aminoglycosides .................................................................................................... 175

7.2.5.3 Beta-lactams ........................................................................................................... 176

7.2.5.4 Carbapenems .......................................................................................................... 177

7.2.5.5 Vancomycin............................................................................................................ 179

7.2.5.6 Linezolid ................................................................................................................. 180

7.2.5.7 Daptomycin ............................................................................................................ 180

7.2.5.8 Fosfomycin ............................................................................................................. 181

7.2.5.9 Colistin ................................................................................................................... 182

7.2.6 Modifying treatment approaches to prevent emergence of resistance ...................... 183

7.2.6.1 Combination antibiotic therapy .............................................................................. 183

7.2.6.2 Duration of therapy ................................................................................................ 184

7.2.6.3 Altered dosing approaches ..................................................................................... 184

7.2.7 Conclusion ............................................................................................................. 185

7.3 Conclusion ......................................................................................................................... 187

xxv

Chapter 8: Summary of findings, general discussion, conclusion and future directions ...... 188

8.1 Summary of findings and general discussion .................................................................... 188

8.2 Future directions for research ............................................................................................ 192

8.3 Conclusion ......................................................................................................................... 193

References ....................................................................................................................................... 194

xxvi

List of Tables

Chapter 1

Table 1-1: Pharmacokinetic characteristics of hydrophilic and lipophilic antibiotics in general ward

versus ICU patients .............................................................................................................................. 5

Table 1-2: Characteristics of previously published studies of continuous versus bolus dosing of

beta-lactam antibiotics ....................................................................................................................... 16

Table 1-3: Antibiotics dosage and outcome data of previously published studies for CI versus IB

dosing of beta-lactam antibiotics ....................................................................................................... 19

Table 1-4: Possible advantages and disadvantages of employing CI versus IB dosing of beta-lactam

antibiotics ........................................................................................................................................... 23

Chapter 2

Table 2-1: Clinical and demographic details of the enrolled patients................................................ 37

Table 2-2: Typical population parameter estimates for the base and final covariate model and the

2000 bootstrap runs ............................................................................................................................ 38

Chapter 3

Table 3-1: Comparison of respective plasma pharmacokinetic between continuous and intermittent

administration of beta-lactams in critically ill or septic patients ....................................................... 54

Table 3-2: Penetration of beta-lactams into various tissues when administered as continuous or

intermittent administration ................................................................................................................. 58

Table 3-3: Clinical outcome data for patients receiving bolus or continuous infusion/extended-

dosing of beta-lactam antibiotics ....................................................................................................... 64

Chapter 4

Table 4-1: Definitions used for pharmacokinetic/pharmacodynamic end-points and clinical outcome

variables ............................................................................................................................................. 76

Table 4-2: Baseline demographics and characteristics ...................................................................... 79

xxvii

Table 4-3: Differences in patient characteristics and treatment-related variables between those who

demonstrated positive and negative clinical outcome ........................................................................ 83

Table 4-4: Factors predicting clinical cure and 30-day survival for all patients who received

antibiotics for treatment of infections ................................................................................................ 87

Chapter 5

Table 5-1: Possible advantages and disadvantages of employing continuous or intermittent

administration of beta-lactam antibiotics ......................................................................................... 108

Table 5-2: Characteristics of previously published studies of continuous versus bolus dosing of

beta-lactam antibiotics ..................................................................................................................... 112

Table 5-3: Antibiotics dosage and outcome data of previously published studies for CI versus IB

dosing of beta-lactam antibiotics ..................................................................................................... 113

Table 5-4: Description of a randomized clinical trial that should be performed to investigate CI

versus IB of beta-lactam antibiotics ................................................................................................. 119

Chapter 6

Table 6-1: Antibiotic dosing protocol according to treatment arm in the BLISS study .................. 131

Table 6-2: Definitions used for primary and secondary clinical end-points .................................... 132

Table 6-3: Baseline demographic and clinical characteristics of the intention-to-treat population . 137

Table 6-4: Microbiological characteristics of the intention-to-treat population .............................. 140

Table 6-5: Primary and secondary end-points by treatment arm in the intention-to-treat population

and the sub-groups of interest .......................................................................................................... 142

Table 6-6: Primary and secondary end-points by treatment arm in the modified intention-to-treat

population......................................................................................................................................... 145

Table 6-7: Primary and secondary end-points by treatment arm in the per-protocol population .... 147

Table 6-8: Differences in clinical characteristics and treatment-related variables between

participants who demonstrated clinical cure and clinical failure in the ITT population.................. 149

Table 6-9: Factors predicting clinical cure in the ITT population ................................................... 152

xxviii

Chapter 7

Table 7-1: Optimal pharmacokinetic/pharmacodynamic indices for antibiotic activity and the

magnitudes associated with maximal therapeutic outcomes and resistance suppression ................ 173

xxix

List of Figures

Chapter 1

Figure 1-1: A diagram outlining the relationship between pharmacokinetics (PK) and

pharmacodynamics (PD) of an antibiotic ............................................................................................. 2

Figure 1-2: Pharmacokinetic (PK) and pharmacodynamic (PD) of antibiotics on a hypothetical

concentration versus time curve ........................................................................................................... 3

Figure 1-3: The simulated concentration-time profile of cefepime when administered by IB or CI

dosing ................................................................................................................................................. 11

Figure 1-4: Description of the current limitations and methodological flaws associated with current

clinical trials ....................................................................................................................................... 14

Chapter 2

Figure 2-1: Goodness-of-fit plots associated with final population pharmacokinetic model for

doripenem........................................................................................................................................... 39

Figure 2-2: Visual predictive check plot associated with the final population pharmacokinetic model

for doripenem ..................................................................................................................................... 40

Figure 2-3: The probability of target attainment for various simulated doripenem dosing regimens to

achieve 40% fT>MIC in patients with a creatinine clearance of (a) 30 mL/min; (b) 50 mL/min; (c) 70

mL/min; (d) 100 mL/min; and (e) 150 mL/min ................................................................................. 41

Chapter 3

Figure 3-1: Comparative flucloxacillin concentration between continuous (CI) and intermittent

administration (IB) assuming similar pharmacokinetic properties in ICU patients. The same daily

dose for IB and CI was simulated from a previous population pharmacokinetic study whereby 2 g 6

hourly for IB and 8 g over 24 hours was simulated for CI ................................................................ 53

Chapter 4

Figure 4-1: Study flowchart demonstrating the number of patients who were included and excluded

in each stage of the planned analysis ................................................................................................. 78

xxx

Figure 4-2: Method of piperacillin/tazobactam and meropenem administration according to

participating countries ........................................................................................................................ 81

Figure 4-3: Clinical cure rates comparison between prolonged infusion and intermittent bolus

dosing for patients who received antibiotics for treatment of infections, stratified according to sub-

groups ................................................................................................................................................. 85

Figure 4-4: Comparison of 30-day survival between prolonged infusion and intermittent bolus

dosing for patients who received antibiotics for treatment of infections, stratified according to sub-

groups. ................................................................................................................................................ 86

Chapter 5

Figure 5-1: Study flowchart demonstrating the number of patients who were included and excluded

in each stage of the planned analysis ............................................................................................... 106

Figure 5-2: The simulated concentration-time profile of a beta-lactam when administered by

intermittent bolus dosing or continuous infusion ............................................................................. 106

Figure 5-3: Observed steady state plasma and tissue concentrations for meropenem administered to

critically ill patients with sepsis by intermittent bolus dosing and continuous infusion ................. 107

Figure 5-4: The summary of the current limitations and flaws associated with the available clinical

trial ................................................................................................................................................... 115

Chapter 6

Figure 6-1: The BLISS study CONSORT flow diagram ................................................................. 136

Figure 6-2: Free plasma antibiotic concentration by beta-lactam antibiotics and treatment groups

measured at (a) 50% of the dosing interval on Day 1 (b) 100% of the dosing interval on Day 1 (c)

50% of the dosing interval on Day 3 and (d) 100% of the dosing interval on Day 3 ...................... 154

Figure 6-3: Free plasma antibiotic concentration to minimum inhibitory concentration (MIC) ratio

by beta-lactam antibiotics and treatment groups measured at (a) 50% of the dosing interval on Day

1 (b) 100% of the dosing interval on Day 1 (c) 50% of the dosing interval on Day 3 and (d) 100% of

the dosing interval on Day 3 ............................................................................................................ 155

xxxi

Chapter 7

Figure 7-1: The graphical illustration of fundamental pharmacokinetic and pharmacodynamic

parameters of antibiotics on a hypothetical concentration-time curve ............................................ 167

Figure 7-2: Graphical illustration of the mutant selection window and mutant prevention

concentration on a hypothetical concentration-time curve .............................................................. 170

xxxii

Abbreviations

% fT>MIC The percentage of time that free (unbound) drug concentration

remains above the minimum inhibitory concentration during a

dosing interval

The influence of creatinine clearance on drug clearance

ACCP The American College of Chest Physicians

AKI Acute kidney injury

APACHE II Acute Physiology and Chronic Health Evaluation II

ARC Augmented renal clearance

AUC Area under the concentration-time curve over a dosing interval

AUC0-24 Area under the concentration-time curve over a 24-hour period

AUC0-24/MIC The ratio of the area under the concentration-time curve during a

24-hour period to minimum inhibitory concentration

AUC0-24/MPC The ratio of the area under the concentration-time curve during a

24-hour period to mutant prevention concentration

BLING Beta-Lactam Infusion Group

BLISS Beta-Lactam In Severe Sepsis

BMI Body mass index

BOV Between-occasion variability

BSV Between-subject variability

BTCCRC Burns, Trauma and Critical Care Research Centre

CAP Community-acquired pneumonia

CART Classification and Regression Tree

CFR Cumulative fraction of response

CI Continuous infusion

CL Clearance

CLCR Creatinine clearance

CLSI Clinical and Laboratory Standards Institute

Cmax Peak drug concentration over a dosing interval

Cmax/MIC The ratio of peak drug concentration to minimum inhibitory

concentration

Cmin Minimum drug concentration over a dosing interval

CMS Colistin methanesulfonate

CNS Central nervous system

xxxiii

CO Cardiac output

COPD Chronic obstructive pulmonary disease

CPB Cardiopulmonary bypass

CRP C-reactive protein

CRRT Continuous renal replacement therapy

Css Steady-state concentration

CV Coefficient of variation

CVVH Continuous venovenous haemofiltration

CWRES Conditional weighted residual

DALI Defining Antibiotic Levels in Intensive care unit patients

ECMO Extracorporeal membrane oxygenation

EDD Extended-daily dosing

EI Extended infusion

ELF Epithelial lining fluid

ESBL Extended-spectrum beta-lactamase

EUCAST European Committee on Antimicrobial Susceptibility Testing

FEV1 Forced expiratory volume in 1 second

FOCE-I First-order conditional estimation with interaction

fT>4 x MIC The time that free (unbound) drug concentration remains four times

above the minimum inhibitory concentration during a dosing

interval

fT>MIC The duration time that free (unbound) drug concentration remains

above the minimum inhibitory concentration during a dosing

interval

GFR Glomerular filtration rate

HFIM Hollow-fibre infection model

HPLC High-performance liquid chromatography

HR Hazard ratio

IAI Intra-abdominal infection

IB Intermittent bolus

ICU Intensive care unit

IPRED Individual predicted concentration

IQR Interquartile range

ISF Interstitial fluid

ITT Intention-to-treat

xxxiv

IV Intravenous

IWRES Individual weighted residual

LD Loading dose

LOS Length of stay

MDR Multi-drug resistant

MIC Minimum inhibitory concentration

MIC90 Minimum inhibitory concentration required to inhibit the growth of

90% of organisms

mITT Modified intention-to-treat

MPC Mutant prevention concentration

MRSA Methicillin-resistant Staphylococcus aureus

MSSA Methicillin-susceptible Staphylococcus aureus

MSW Mutant selection window

MV Mechanical ventilation

OFV Objective function value

OR Odds ratio

PAE Post-antibiotic effect

PD Pharmacodynamics

PD50 The dose needed to protect 50% of animals from death

PK Pharmacokinetics

PK/PD Pharmacokinetic/pharmacodynamic

PP Per-protocol

PRED Population predicted concentration

PsN Perl-Speaks-NONMEM®

PTA Probability of target attainment

Q Inter-compartmental clearance

RCT Randomized controlled trial

RRT Renal replacement therapy

RUV Residual unexplained variability

SCCM The Society of Critical Care Medicine

SIRS Systemic inflammatory response syndrome

SLED Sustained low-efficiency dialysis

SOFA Sequential Organ Failure Assessment

SSTI Skin and skin-structure infection

SW Selective window

xxxv

T Time

TDM Therapeutic drug monitoring

tMSW The time spent in the mutant selection window

UTI Urinary tract infection

V1 Central volume of distribution

V2 Peripheral volume of distribution

VAP Ventilator-associated pneumonia

Vd Volume of distribution

VISA Vancomycin-intermediately susceptible Staphylococcus aureus

VPC Visual predictive check

VRE Vancomycin-resistant enterococci

WCC White cell counts

ΔOFV The change in objective function value

θCLpop The typical value of clearance in the population

1

Chapter 1: Introduction and literature overview

1.1 Introduction

The mortality rate due to severe sepsis and septic shock in the intensive care unit (ICU) setting

remains high despite recent therapeutic advances [1]. Source control of the infection, along with

early and appropriate antibiotic administration, are the most effective strategies available to

clinicians for the management of critically ill septic patients [2-4]. However, appropriate antibiotic

administration is not straightforward as critically ill patients may develop pathophysiological

changes that can alter the antibiotic pharmacokinetics (PK). Indeed, dosing that does not account for

these alterations may lead to inadequate antibiotic exposure and therapeutic failure [5-8]. Beta-

lactam antibiotics are key in the treatment of severe infections due to their spectrum of antibiotic

activity and overall tolerability. These antibiotics display time-dependent pharmacodynamics (PD),

whereby the time which the antibiotic concentration remains above the minimum inhibitory

concentration (MIC) best characterizes bacterial killing [9-12]. Based on this property, maximal

beta-lactam activity is likely to be achieved through a continuous infusion (CI) or an extended

infusion (EI) strategy which maintains concentrations at higher concentrations throughout a dosing

interval, rather than traditional intermittent bolus (IB) dosing [13-17]. Different dosing approaches

in critically ill patients with sepsis may lead to better attainment of PK and PD targets potentially

leading to greater clinical success.

1.2 Applied clinical pharmacology of antibiotics

Pharmacology is the science of drugs or study of drug actions. The two main areas of pharmacology

are PK and PD. Knowledge on PK and PD is essential to comprehend the complex effect of

pathophysiological changes in critically ill patients and how they alter plasma and tissue antibiotic

concentrations. Furthermore, a personalized dosing regimen can be established for critically ill

patients by using pharmacokinetic/pharmacodynamic (PK/PD) principles.

1.2.1 Pharmacokinetic considerations

PK refers to the study of concentration changes of a drug over a given time period. It provides a

mathematical basis to assess the time course of drugs and their effects in the body. The important

PK parameters for antibiotics are: (a) volume of distribution (Vd); (b) clearance (CL); (c) peak drug

concentration over a dosing interval (Cmax); (d) minimum drug concentration during a dosing

2

interval (Cmin); and (e) area under the concentration-time curve over a dosing interval (AUC) or

over a 24-hour period (AUC0-24) [18].

1.2.2 Pharmacodynamic considerations

PD is the study of the relationship between measures of drug exposure and pharmacological effect.

For antibiotics, PD relates concentration to the ability of an antibiotic to kill or inhibit the growth of

a pathogen. This can be done by integrating antibiotic PK data with information on pathogen

susceptibility (e.g., MIC). PD indices include the following: (a) the duration of time (T) that the free

(unbound) drug concentration remains above the MIC during a dosing interval (fT>MIC); (b) the ratio

of peak drug concentration (Cmax) to MIC (Cmax/MIC); and (c) the ratio of the area under the

concentration-time curve during a 24-hour period (AUC0-24) to MIC (AUC0-24/MIC) [18]. Together,

PK parameters and PD indices describe the dose-concentration-effect relationship. Figure 1-1

outlines the interrelationship of PK and PD.

Figure 1-1: A diagram outlining the relationship between pharmacokinetics (PK) and

pharmacodynamics (PD) of an antibiotic

1.2.3 Bacterial kill characteristics of different antibiotics

Different classes of antibiotics have been shown to have different kill characteristics on pathogens.

These kill characteristics have been determined predominantly from in vitro studies and describe

the PK measurements that represent optimal bactericidal activity [19]. Generally, antibiotics can be

classified into three categories based on their modes of bacterial killing: (a) concentration-

dependent antibiotics (e.g., aminoglycosides); (b) time-dependent antibiotics (e.g., beta-lactams);

and (c) both i.e., concentration and time-dependent antibiotics (e.g., vancomycin and

fluoroquinolones) [12]. The fundamental concepts of antibiotic kill characteristics are further

3

illustrated in Figure 1-2. As an example, for time-dependent antibiotics such as the beta-lactams,

fT>MIC is strongly correlated with bacteriostasis and bactericidal activity [12, 20-26]. Thus, for a

time-dependent antibiotic, the longer the effective drug concentration is maintained over a dosing

period the greater drug efficacy [25, 27, 28].

Figure 1-2: Pharmacokinetic (PK) and pharmacodynamic (PD) of antibiotics on a

hypothetical concentration versus time curve

1.3 Sepsis

Severe sepsis and septic shock are the most common causes of morbidity and mortality in critically

ill patients [1, 29-35]. In a multicentre point prevalence study involving 1265 ICUs across 75

countries, 51% of the ICU patients were classified as infected on the day of study with an ICU

mortality rate of 25.3% [31]. Data from a large European ICU study has further corroborated severe

sepsis status as a major healthcare burden, whereby severe sepsis accounted for 26.7% of ICU

admissions with mortality rates for patients with severe sepsis and septic shock were 32.2% and

54.1%, respectively [33]. Based on the Malaysian Registry of Intensive Care report for year 2011,

23.2% of Malaysian ICU patients developed severe sepsis within 24 hours of ICU admission with a

mortality rate approaching 60% [36]. Despite an emerging trend for improved survival in ICU

patients [32, 37-39], the mortality rate in critically ill patients remains unacceptably high

4

worldwide, ranging from 30-50% in severe sepsis and 40-87% in patients with septic shock [37, 40-

45]. As a consequence, huge hospital resources are spent worldwide on septic patients [46, 47].

The “older” definition of sepsis [48] has been refined in 2005 by The American College of Chest

Physicians (ACCP) and the Society of Critical Care Medicine (SCCM) [49, 50] as an infection in

the presence of systemic inflammatory response syndrome (SIRS) [50]. SIRS has been described as

a constellation of physiological (e.g., temperature, heart rate, respiratory rate) and laboratory

abnormalities (e.g., white cell count [WCC]) that accompany inflammation independent of its

underlying aetiology [48]. Severe sepsis is defined as sepsis complicated by at least one organ

dysfunction or tissue hypoperfusion. Organ dysfunction can be described using definitions that were

previously developed by Marshall et al., [51] or a more recent definition used in the Sequential

Organ Failure Assessment (SOFA) score [52]. Septic shock refers to acute circulatory failure

characterized by persistent arterial hypotension unexplained by other causes. Specifically, septic

shock can be defined as sepsis induced hypotension (hypotension is defined as a systolic blood

pressure of <90 mmHg or mean arterial pressure of <70 mmHg or a systolic blood pressure

decrease >40 mmHg), which persists despite adequate volume resuscitation in the absence of other

causes for hypotension [48, 50].

1.4 Pathophysiological changes in critically ill patients with sepsis that can

affect drug pharmacokinetics

Physiological changes that can occur from either pharmacological interventions or the natural

course of sepsis may alter antibiotic PK and consequently affect antibiotic exposure in critically ill

patients. Vd and drug CL are the most important PK parameters in terms of calculating a drug

dosing requirements and both may be significantly altered in critically ill patients with severe

sepsis. Table 1-1 describes the anticipated changes in Vd and CL of various antibiotics in ICU

patients compared to the general population.

5

Table 1-1: Pharmacokinetic characteristics of hydrophilic and lipophilic antibiotics in general

ward versus ICU patients

Antibiotic PK parameters General PK Altered PK in ICU patients

Hydrophilic Vd Low Vd Vd

e.g., aminoglycosides,

beta-lactams, colistin,

glycopeptides, linezolid

CL Predominantly

renal

or depending on renal

function

Intracellular

penetration

Poor interstitial penetration

Lipophilic Vd High Vd Unchanged

e.g., fluoroquinolones,

lincosamides,

macrolides, tigecycline

CL Predominantly

hepatic

or depending on renal

function

Intracellular

penetration

Good Unchanged

Abbreviation: CL, clearance; ICU, intensive care unit; PK, pharmacokinetics; Vd, volume of

distribution.

1.4.1 Changes of volume of distribution

The Vd of a drug is defined as the apparent volume of fluid (usually expressed in L or L/kg) that

drug distributes into to give a total concentration the same as is measured in the plasma. Changes in

antibiotic Vd have been noted in critically ill patients [6, 53-57], and the contributing factors are

discussed below.

Sepsis involves release of various inflammatory mediators [49, 58-60] that eventually increases

capillary permeability [61-63]. This capillary leak syndrome causes fluid shifting from the

intravascular compartment to the interstitial space, which is commonly described as the third

spacing phenomenon. This phenomenon increases the Vd of hydrophilic antibiotics, decreasing their

plasma and tissue concentrations in critically ill patients [64]. Consequently, a higher dose of such

antibiotics is needed in order to achieve effective antibiotic exposure in critically ill patients with

severe sepsis. In contrast, fluid shifts have a minimal effect on lipophilic antibiotics as they

inherently possess a larger Vd due to their greater partitioning out of the blood stream (typically into

intracellular and adipose compartments). In addition, several medical interventions in the ICU such

as aggressive fluid resuscitation [65-68], mechanical ventilation [69-72], extracorporeal circuits

[73], the presence of postsurgical drains [74, 75] and total parenteral nutrition [76] have also been

6

reported to be associated with increased Vd and consequently decreased concentrations of

hydrophilic antibiotics.

1.4.1.1 Tissue perfusion and target site distribution of antibiotics

Effective antibiotic concentrations need to be achieved in the interstitial fluid of tissues as most

infections are thought to occur here [77]. However, critically ill patients with sepsis have shown

diminished microvascular perfusion, which results in impaired distribution of drugs especially to

sites of infection such as soft tissues [78-82]. This phenomenon can be attributed to capillary

leakage, tissue oedema and microvascular failure which are frequently seen in such patients. Using

an in vivo sampling technique known as microdialysis, the extent of antibiotic penetration into

tissues of critically ill patients has been described [72, 83-88]. Critically ill patients with septic

shock are initially managed with large boluses of intravenous (IV) fluids to increase blood pressure.

However, in the presence of increased permeability, large administration of IV fluids eventually

leads to extreme volume expansion in the interstitial space which markedly increases Vd for

hydrophilic antibiotics [56, 89]. In patients with septic shock, antibiotic concentrations in interstitial

fluid may be 5- to 10-times lower than corresponding plasma concentrations as well as those

concentrations observed in healthy volunteers [90]. However, in patients with sepsis but without

shock, there seems to be a less significant effect on tissue distribution and penetration of antibiotics

[85, 91]. The difference in these findings may be attributed to the level of sickness severity (sepsis

versus septic shock) whereby septic shock causes greater impairment in microvascular perfusion

that leads to lower antibiotic penetration than patients with sepsis.

1.4.1.2 Protein binding and hypoalbuminaemia

Hypoalbuminaemia is a common condition in the ICU with reported incidences as high as 40-50%

[92, 93]. In critically ill patients, hypoalbuminaemia is usually caused by the increase in capillary

permeability [94], downregulation of its hepatic synthesis [95] and malnutrition [96]. What follows

is an increase in the free concentration of drugs that are usually bound to this negative acute phase-

protein. The unbound concentration of such antibiotics is not only available for elimination, but also

for distribution [97-106]. For moderate-to-highly-protein bound antibiotics, this phenomenon has

been associated with a 90% increase in Vd [106, 107]. However, tissue concentrations remain low

despite increased drug distribution, due to significant fluid shifts during the acute phase response

and the large requirements for IV fluids in critically ill patients [97, 100, 102, 105, 108].

7

1.4.2 Changes in drug clearance

CL can be defined as the volume of blood (usually expressed in L/hr or L/hr/kg) cleared of drug per

unit time. CL measures the irreversible elimination of a drug from the body by either excretion

and/or metabolism. Changes in drug CL have been noted in critically ill patients [109, 110] with

contributing factors discussed below.

1.4.2.1 Increase in cardiac output and augmented renal clearance

Critically ill patients with severe sepsis frequently develop SIRS. A major component of this

inflammatory response is a hyperdynamic cardiovascular state, which is characterized by an

increase in cardiac output (CO) and enhanced blood flow to major organs [111-113]. One of the

major organs affected are the kidneys whereby the increase in renal blood flow associated with

increases in CO leads to increases glomerular filtration rates (GFR) [109]. Furthermore, therapeutic

interventions used to reverse hypotension in critically ill patients usually include large boluses of IV

fluid and administration of vasopressor infusions, which are also associated with an early increase

in CO and GFR [60, 111, 112, 114, 115]. Consequently, all of these factors lead to increased renal

CL of some drugs, a phenomenon referred to as augmented renal clearance (ARC, defined as a

creatinine clearance [CLCR] >130 mL/min). As hydrophilic antibiotics are predominantly cleared by

the kidney, ARC in critically ill patients usually causes lower plasma concentrations [116-124].

Identifying patients with ARC is not easy as critically ill patients may have elevated renal function

despite normal serum creatinine concentrations [125-128]. Thus, antibiotic dosing in this unique

patient population is usually flawed as most clinicians fail to address this phenomenon [129].

1.4.2.2 End-organ dysfunction

As disease progresses in a critically ill patient, myocardial depression may occur leading to

decreased organ perfusion and microcirculatory failure eventually resulting in end-organ damage or

in extreme cases, multiple organ dysfunction syndrome [60, 130, 131]. This syndrome often

includes renal and/or hepatic dysfunction that consequently results in a decrease in antibiotic CL.

The resulting accumulation of drugs and their metabolites in plasma increases the likelihood of

toxicity [132]. It is imperative to note that certain antibiotics can be cleared by other organs when

the primary eliminating organ (usually the kidneys) is impaired. By way of example, some

antibiotics such as ticarcillin and piperacillin demonstrate increased biliary CL that causes little

change in their plasma concentration despite mild to moderate renal dysfunction [133, 134].

8

1.4.2.3 Extra-corporeal circuits

Sepsis is the most common cause of acute kidney injury (AKI) in critically ill patients and the

associated mortality rates are higher in septic AKI population compared to those with non-septic

AKI [135-137]. The PK of antibiotics in this population are highly variable as parameters may be

altered by both AKI and critical illness. In addition, patients with AKI may be receiving

extracorporeal therapies including continuous renal replacement therapy (CRRT) or sustained low-

efficiency dialysis (SLED) to remove fluid and wastes from the body, and extracorporeal membrane

oxygenation (ECMO) to support impaired cardiac and/or pulmonary systems to maintain

appropriate blood gas concentrations. These interventions may influence antibiotic dosing

requirements as critically ill patients with CRRT and SLED were reported to have variable

antibiotic CL [138-142]. There is limited data on the influence of ECMO [141, 143-146].

1.4.3 Beta-lactam antibiotics and their pharmacokinetic and pharmacodynamic

properties

The beta-lactam antibiotics are made up of penicillins, cephalosporins, carbapenems and

monobactams. This group of antibiotics are generally hydrophilic in nature, demonstrate low Vd

(0.1-0.6 L/kg), and are predominantly cleared by the kidneys [8]. In relation to protein binding

properties, most beta-lactams have a moderate (30-70%) to low (<30%) degree of protein binding.

However, ertapenem, cefazolin, ceftriaxone and flucloxacillin demonstrate high protein-binding

(>90%) when compared to the other beta-lactams members, highlighting that PK variability may

exist within the group.

The fT>MIC is regarded as the optimal PD index for beta-lactams and as such, maintaining effective

drug concentration above the MIC should be the priority when this antibiotic class is used [9, 11,

12, 24]. Specifically, the percentage (%) of fT>MIC (% fT>MIC) needed for bacteriostasis is 35-40%,

30%, 20% for cephalosporins, penicillins and carbapenems, respectively and for bactericidal is 60-

70%, 50%, 40% for cephalosporins, penicillins and carbapenems, respectively [10-12, 24].

However, emerging clinical data from critically ill patients suggests that these patients may benefit

from higher and longer antibiotic exposures than those described in in vitro and in vivo studies [22,

23, 25-28, 147]. In a study specifically investigating critically ill patients with sepsis, McKinnon et

al., found a % fT>MIC of 100% was associated with higher rates of bacteriological eradication and

clinical cure than lesser % fT>MIC values [28]. Thus, it has been suggested that maintaining

concentrations above the MIC for 90-100% of the dosing interval is an appropriate PD target for

9

critically ill patients and may prevent antibiotic resistance [5, 148, 149]. It has also been

demonstrated that maximal bactericidal activity occurs when drug concentrations are maintained at

four- to five-times the MIC, with higher concentrations providing little added benefit [23, 25, 26,

147, 150-152]. Thus, it has been suggested that beta-lactam concentrations should be maintained at

least four- to five-times the MIC for extended periods during each dosing interval [5, 7, 153].

Another consideration for optimizing antibiotic exposure is the post-antibiotic effect (PAE), i.e., the

suppression of bacterial growth even with antibiotic concentrations below the MIC [154-158]. The

beta-lactams except for the carbapenems, produce minimal or no PAE against Gram-negative

pathogens. Carbapenems have been found to have a significant PAE against Gram-negative bacilli,

including Pseudomonas aeruginosa strains [155, 157, 158]. This PAE property of carbapenems

may explain their faster bacterial killing rate and shorter % fT>MIC for optimal bactericidal activity

[158-162].

Maintaining effective beta-lactams exposure for extended periods or increasing % fT>MIC would be

especially appropriate in immunocompromised patients including critically ill patients [7, 27, 163].

Furthermore, achieving an optimal PD index may increase the likelihood of therapeutic success in

these patients [20-23, 26, 27, 147]. Traditional IB dosing produces antibiotic concentrations below

the MIC for much of the dosing interval [67, 85, 86, 106, 151, 164-175]. This has prompted

clinicians to consider several dose optimization strategies that maximize the value of % fT>MIC.

Research has shown that improved antibiotic exposure can be obtained via three general

approaches: (1) increasing the antibiotic dose; (2) increasing the frequency of antibiotic dosing or;

(3) by utilizing EI or CI [67, 85, 86, 106, 151, 164-175]. However, increasing the antibiotic dose

has been shown to be less effective to adequately maintain effective drug concentration during a

dosing period. Increasing the antibiotic dose only raises the % fT>MIC for one half-life, which is

usually short (i.e., 1 or 2 hours) for most beta-lactams. Although study findings have been

inconclusive, increasing the antibiotic dose could theoretically lead to toxicity issues, which has

indeed been described in a recent meta-analysis [176] and several case reports [177-180]. Hence, EI

and CI of beta-lactam antibiotics have been proposed as a means of achieving optimal PK/PD

targets in critically ill patients without increasing a patient’s total daily dose [85]. These new

administration approaches may be especially important in patients who develop ARC and/or have

increased Vd which are common in critical illness [6, 7]. Specific PK changes associated with beta-

lactam use in critically ill patients are discussed below.

10

1.4.4 Pharmacokinetic and pharmacodynamic considerations for critically ill patients

with sepsis

It is being increasingly shown that heterogeneity in beta-lactam PK is significant among critically ill

patients and this phenomenon may affect treatment outcomes [6, 7]. Large Vd and CL differences

are common [56, 181]. For example, mean Vd for meropenem in severe sepsis can range from 0.3-

0.5 L/kg (healthy volunteers Vd 0.2 L/kg) [86, 182-195]. The increased Vd in critical illness can

result in sub-therapeutic antibiotic concentrations particularly in the early phase of the disease and

thus, should prompt clinicians to use higher loading doses to achieve optimal concentrations rapidly

[57, 196-199].

Apart from antibiotic Vd, high and variable beta-lactam CL is also frequently noted in patients with

severe sepsis [181, 200]. For beta-lactams, CL is frequently correlated with CLCR, which may

increase in critical illness [69, 117, 118, 120, 121, 175, 201-206]. A review by Goncalves-Pereira

and Povoa reported high CL with variable antibiotic trough concentrations in most clinical studies

investigating beta-lactam PK in ICU patients [56]. Chapuis et al., found 40-fold variations in

cefepime trough concentrations in his study and interestingly, 50% of the patients had antibiotic

concentrations lower than the target concentration (i.e., 4 mg/L) when a standard cefepime dosing

regimen was used [198]. The low antibiotic concentrations commonly observed are likely to be

caused by the presence of ARC [117, 121, 129]. To account for this PK change, altered dosing

approaches for beta-lactams such as the use of higher doses or increased frequency is necessary to

ensure adequate fT>MIC is achieved [207]. However, drug CL may increase or decrease based on

patient organ function and reduced beta-lactam CL can occur with renal and/or hepatic dysfunction.

In this situation, dose reduction may be indicated to prevent toxicity from elevated drug

concentrations.

Reduction in tissue penetration of beta-lactams has been described in critically ill patients and is

likely to be caused by microcirculatory failure [66, 72, 80, 83-88, 90, 91, 189, 208]. Emerging

PK/PD data from critically ill patients suggests better antibiotic tissue penetration and optimal PD

target attainment can be achieved via CI of beta-lactam antibiotics [79, 81, 82, 85, 86, 167, 209-

212].

Numerous PK/PD studies have suggested potential flaws in the current mode of beta-lactam

administration (i.e., IB administration) in terms of achieving optimal PK/PD targets in patients with

severe sepsis. Generally, IB administration produces high unnecessary peaks, which confer no PD

11

advantage for this antibiotic class and results in low trough concentrations (Figure 1-3) [7]. Lipman

et al., performed a prospective PK/PD clinical study to describe the PK properties and PD

characteristics associated with twice daily dosing of cefpirome in patients with severe sepsis [67].

Using 60% fT>MIC as the PD target, the authors reported that only 60% and 10% of the patients met

the PD target for MIC of 4 and 16 mg/L, respectively. In addition, the authors also concluded that

the standard dosing regimen produces low cefpirome trough concentrations and may not be

sufficient to treat severe infections in critically ill patients. Apart from this study, numerous other

PK/PD modelling and dosing simulation studies concluded that an improved beta-lactam PK/PD

profile is achieved with more frequent dosing or via EI or CI [53, 67, 79, 82, 85, 86, 106, 167-171,

173-175, 184, 187, 190, 204, 205, 213, 214]. All present in vitro and in vivo animal data also

support the use of CI compared to IB dosing in patients with altered PK [15]. Therefore, CI and EI

dosing of beta-lactam antibiotics may be meritorious and may maximize the likelihood of

therapeutic success.

Figure 1-3: The simulated concentration-time profile of cefepime when administered by IB or

CI dosing

Abbreviation: CI, continuous infusion dosing; IB, intermittent bolus dosing; MIC, minimum

inhibitory concentration.

12

1.4.5 Continuous beta-lactam infusion

CI of beta-lactam antibiotics is likely to offer the greatest advantage over IB administration when

less susceptible pathogens (e.g., P. aeruginosa) are present [85, 86, 169, 215, 216]. When

susceptible pathogens are involved, because of a lower MIC, the mode of administration (i.e., CI or

IB) is likely to be less important. Therefore, CI of beta-lactam antibiotics is unlikely to be

advantageous for all patients but may be particularly important in specific patient cohorts such as

critically ill patients with high level of sickness severity, who are also more likely to have less-

susceptible pathogens [217].

1.4.5.1 In vitro models simulating human pharmacokinetics

Although results from several animal studies clearly show that CI of beta-lactam antibiotics is more

efficacious than IB administration, the half-life of these drugs in animals (i.e., rodents) is much

shorter than in humans and thus, extrapolating the results to patients may not be completely

representative [15]. In vitro models that mimic human PK may provide better information with

regards to antibiotic exposure and its effect in humans [218].

In one of their earlier in vitro PK models, Mouton and den Hollander suggested that continuous

ceftazidime administration was more efficacious against P. aeruginosa compared to IB dosing

[152]. After the fourth dose, a marked difference in bacterial counts was observed between the two

dosing approaches (CI; 2.2 log10 versus IB; 2.8 log10). The authors added that maximal

bactericidal activity may be achieved with sustained antibiotic concentrations at four- to five-times

the MIC, with higher concentrations providing little further benefit. Other investigators have

confirmed these results in their studies [219-225].

1.4.5.2 In vivo animal studies

The effectiveness of CI versus IB administration of beta-lactam antibiotics has also been examined

in in vivo animal studies [226-237]. In one of their leading reviews, Craig and Ebert concluded that

based on numerous in vitro and in vivo animal studies, CI of beta-lactam antibiotics demonstrated

many potential advantages, particularly in Gram-negative infections and in immunocompromised

hosts [17]. Roosendaal et al., found similar results when the efficacy of CI of ceftazidime was

studied in a cohort of neutropenic rats [231]. In this study, the daily dose needed to protect 50% of

the animals from death (PD50) was 16-times lower with CI (1.52 mg/kg per day versus 24.37 mg/kg

per day; p <0.001). However, when the authors studied non-neutropenic rats, the differences

13

between the two dosing methods almost completely disappeared. This interesting finding suggests

that CI administration may be more beneficial in immunocompromised hosts. Similar findings have

been reported in several other studies [17, 233, 235]. Importantly, some in vivo models have shown

more rapid bactericidal activity with IB [232, 234]. However, the administration of a loading dose

prior to CI will enable faster achievement of effective concentration for CI [238].

1.4.5.3 Clinical outcomes

Despite strong in vitro and in vivo PK/PD data supporting the administration of beta-lactams by CI,

there is currently no “convincing” data on patient outcomes that differentiate the two dosing

methods. This may be attributed to several methodological flaws in studies that may mask the

benefits of CI previously observed in pre-clinical studies [13, 14, 217, 239, 240]. Findings from

clinical trials suggest that CI of beta-lactam antibiotics may have variable efficacy in different

patient groups [166, 241-243]. It has been suggested that patients who are most likely to benefit

from CI are critically ill patients with a high level of illness severity [166, 242, 243], but with

conserved renal function [241, 244, 245].

Numerous clinical comparative studies have been conducted with beta-lactams testing various

dosing strategies in various patient populations including critically ill patients [85, 86, 151, 166,

169, 171, 172, 241-243, 246-252], patients receiving extracorporeal renal circuit [244, 245, 253],

trauma patients [254], patients with malignant diseases [255], patients with intra-abdominal

infections [256], patients with chronic obstructive pulmonary disease (COPD) [257, 258] and non-

specific hospitalized patients [173, 259-262] (Table 1-2). These studies have not shown whether

alternative dosing approaches (i.e., CI and EI) are advantageous nor which patient groups may

benefit. Most of these trials were conducted in North America and Europe between 1979 and 2015,

with all but five studies published after 2010 [166, 241, 242, 246, 259]. A number of articles have

also discussed the potential advantages and disadvantages of CI [13-17, 263-265]. A recent

systematic review of the published literature by Abdul-Aziz et al., [13] found no statistically

significant differences in critically ill patients with regards to mortality rate [151, 172, 243, 248],

clinical cure [172, 243, 266], time to normalization of leukocytosis or pyrexia [248, 254],

mechanical ventilation [172, 243, 254, 266], hospital or ICU length of stay [172, 243, 254, 266] and

adverse events [266] between CI and IB dosing. In addition, three meta-analyses have been

published to determine if any clinical benefits of CI beta-lactams can be found from the combined

clinical data of the present studies [217, 240, 267]. Again, the analyses have not reported any

significant difference between CI and IB dosing with regards to clinical cure and survival.

14

However, wide confidence intervals can be observed in the meta-analyses that suggest a clinically

relevant difference between the two dosing approaches may still exist if more stringent

methodology was used in the studies [217]. Nevertheless, Kasiakou et al., suggested that fewer

daily CI doses are needed to produce similar outcomes as IB dosing [267]. Despite these findings,

there are currently four recent meta-analyses which reported significant patient benefits with altered

dosing approaches [239, 268-271]. However, the recent findings should be interpreted with caution

as the meta-analyses have included a significant number of retrospective and non-randomized

studies in their pooled analysis. A large-scale prospective clinical trial with a robust design is

required to answer the controversy surrounding the effectiveness of CI versus IB dosing in critically

ill patients. Future trials need to address the methodological flaws associated with current studies.

These methodological flaws have been described in detail by Abdul-Aziz et al., in a recent review

article [13, 14]. Figure 1-4 summarizes the current limitations and flaws associated with the

available clinical trials.

Figure 1-4: Description of the current limitations and methodological flaws associated with

current clinical trials

15

It is also imperative to highlight the clinical findings of three recent randomized controlled trials

(RCT) which demonstrated some clinical outcome advantages favouring CI administration of beta-

lactam antibiotics when only critically ill patients were recruited [166, 242, 243]. In a prospective,

open-labelled RCT which recruited Australian ICU patients (n = 57), Roberts et al., [243]

demonstrated higher clinical cure rates favouring CI administration as opposed to IB dosing of

ceftriaxone (52% versus 20%; p = 0.04). In a prospective, multicentre, double-blind, RCT (Beta-

Lactam Infusion Group [BLING] I; n = 60), Dulhunty et al., [166] showed that participants in the

CI treatment arm demonstrated higher clinical cure rates (77% versus 50%; p = 0.032) compared to

the IB arm. In a single-centre RCT which recruited 240 critically ill Czech participants, Chytra et

al., [242] reported higher microbiological cure rates in the CI treatment arm as opposed to the IB

arm (91% versus 78%; p = 0.020). However, none of the studies demonstrated significant patient

survival advantages.

It follows that, CI administration of beta-lactam antibiotics may not result in better outcomes for all

critically ill patients. This was recently highlighted in a multicentre, double-blind, RCT (BLING II;

n = 420) [241]. Despite recruiting only patients with severe sepsis, Dulhunty et al., [241] found no

significant difference between CI and IB participants, in all five clinical end-points evaluated. In

this study, Dulhunty et al., included patients receiving renal replacement therapy (RRT) (~25% of

participants) and this inclusion criterion may have reduced PK/PD exposure differences between CI

and IB dosing because patients with reduced drug clearances, as seen during RRT, are less likely to

manifest sub-therapeutic antibiotic exposures [211, 244, 245, 253]. Patients receiving RRT are

therefore less likely to benefit from altered dosing approaches such as CI administration. Based on

these inconsistent findings and other relevant retrospective clinical data [272-276], we await the

outcome of future clinical trials that use a more rigorous and stringent methodology to demonstrate

the clinical outcome differences between CI and IB, if they do exist.

16

Table 1-2: Characteristics of previously published studies of continuous versus bolus dosing of beta-lactam antibiotics

Study Setting

(Country)

Antibiotic Critically ill Population Sample

size

Agea Allocation

sequence

generator

Allocation

concealment

Masking Concomitant

antibiotic CI IB

Angus et al.,

[151]

Not specified

(Thailand)

Ceftazidime Yes Septicaemic

melioidosis

21 48

(29-58)

43

(27-73)

Not specified Not specified Not specified Various

Bodey et al.,

[255]

Non-ICU

(USA)

Cefamandole No Malignant diseases

with neutropenia

204 Not specified Adequate Adequate Not specified Carbenicillin

Buck et al.,

[173]

Non-ICU

(Germany)

Piperacillin/tazobactam No Hospitalized

infections

24 60-88b 32-76b Not specified Adequate No Nil stated

Chytra et al.,

[242]

ICU

(Czech)

Meropenem Yes Critically ill patients

with severe sepsis

240 45±18 47±16 Yes Adequate No Various

Cousson et al.,

[249]

ICU

(France)

Ceftazidime Yes Critically ill patients

with nosocomial

pneumonia

16 61 (21-81) Yes Not specified Not specified Not specified

De Jongh et al.,

[247]

ICU

(Belgium)

Temocillin Yes Critically ill patients

with nosocomial

infections

17 58±8 56±9 Not specified Not specified No Various

Dulhunty et al.,

[241]

ICU

(Australia, New

Zealand & Hong

Kong)

Meropenem,

piperacillin/tazobactam,

ticarcillin/clavulanate

Yes Critically ill patients

with severe sepsis

432 64 (54-72) 65 (53-72) Yes Yes Yes Various

Dulhunty et al.,

[166]

ICU

(Australia &

Hong Kong)

Meropenem,

piperacillin/tazobactam,

ticarcillin/clavulanate

Yes Critically ill patients

with severe sepsis

60 54±19 60±19 Adequate Adequate Yes Various

Georges et al.,

[172]

ICU

(France)

Cefepime Yes Critically ill with

Gram-negative

infections

50 50±17 46±24 Not specified Not specified No Amikacin

Hanes et al.,

[254]

ICU

(USA)

Ceftazidime Yes Critically ill trauma 32 33.5±12.5 36.1±12.8 Not specified Not specified No Nil stated

Jamal et al.,

[244]

ICU

(Malaysia)


with severe

sepsis/septic shock

receiving CVVH

16 48 (32-63) 45 (29-61) Not specified Yes No Nil stated

Jamal et al.,

[245]

ICU

(Malaysia)

Piperacillin/tazobactam Yes Critically ill patients

with severe

sepsis/septic shock

receiving CVVH

16 44 (34-70) 63 (46-71) Yes Yes No Nil stated

Lagast et al.,

[262]

Not specified

(Belgium)

Cefoperazone No Gram-negative

septicaemia

45 37-77b Not specified Not specified No Nil stated

17

Laterre et al.,

[259]

ICU

(Belgium)

Temocillin Yes Critically ill patients

with intra-abdominal

and LRTI

32 68±11 65±15 Not specified Not specified No Various

Lau et al.,

[256]

ICU

(USA)

Piperacillin/tazobactam No Complicated intra-

abdominal infections

262 50.4±16.6 49.3±17.8 Not specified Not specified No Nil stated

Lipman et al.,

[250]

ICU

(Hong Kong)

Ceftazidime Yes Critically ill patients 18 64±9 53±14 Yes Not specified Not specified Nil stated

Lubasch et al.,

[258]

Not specified

(Germany)

Ceftazidime No Hospitalized patients

with COPD

exacerbation

81 65.3±10.1 Not specified Not specified No Nil stated

Nicolau et al.,

[251]

ICU

(USA)

Ceftazidime Yes Critically ill patients 34 43±15 51±21 Not specified Not specified Not specified Tobramycin

Nicolau et al.,

[252]

ICU

(USA)


with nosocomial

pneumonia

24 37±13 45±19 Not specified Not specified Not specified Tobramycin

Nicolau et al.,

[266]

ICU

(USA)


with sepsis

41 46±16 56±20 Adequate Not specified No Tobramycin

Okimoto et al.,

[260]

Not specified

(Japan)

Meropenem No Elderly patients with

CAP

50 80 Not specified Not specified Not specified Nil stated

Pedeboscq et al.,

[261]

ICU

(France)

Piperacillin/tazobactam Yes Severe sepsis 7 58±12 Not specified Not specified No Ofloxacin

Rafati et al.,

[248]

ICU

(Iran)

Piperacillin Yes Critically ill patients

with sepsis

40 50.1±22.2 48.0±20.7 Not specified Not specified No Amikacin

Roberts et al.,

[169]

ICU

(Australia)


with sepsis


Roberts et al.,

[85]

ICU

(Australia)


with sepsis

13 25 (19-35) 42 (23-65) Not specified Yes No Nil stated

Roberts et al.,

[86]

ICU

(Australia)


with sepsis


Roberts et al.,

[243]

ICU

(Australia)

Ceftriaxone Yes Critically ill patients

with sepsis

57 43±19 52±16 Adequate Adequate Adequatec Multiple

depending on

indication

Sakka et al.,

[171]

ICU (Germany) Imipenem/cilastatin Yes Critically ill patients

with sepsis

20 62±16 59±16 Not specified Adequate No Nil stated

Tamer et al.,

[246]

ICU

(Egypt)


with severe sepsis

100 Not specified Not specified Not specified Not specified Nil stated

Van Zanten et

al.,

[257]

Not specified

(Netherlands)

Cefotaxime No Hospitalized patients

with COPD

exacerbation


Abbreviation: CAP, community-acquired pneumonia; CI, continuous infusion; COPD, chronic obstructive pulmonary disease; CVVH, continuous venovenous haemofiltration; IB, intermittent bolus; ICU, intensive care unit.

aValues are reported according to published results as mean (±SD) or median (interquartile range).

18

bValues are reported as range. cOnly outcome assessment was blinded.

19

Table 1-3: Antibiotics dosage and outcome data of previously published studies for CI versus IB dosing of beta-lactam antibiotics

Study Types of infection Number of patients

(APACHE II scorea)

Antibiotic dosage regimen Concurrent

PK/PD analysis

Clinical outcome

measures

CI IB p-valueb

CI IB CI IB

Angus et al.,

[151]

Septicaemic melioidosis 10 (15) 11 (21) 12 mg/kg LD, then 4

mg/kg every 1 hr

40 mg/kg every 8 hrs Yes Mortality 20% 36.4% 0.89

Bodey et al.,

[255]

Pneumoniae, UTI &

neutropenic fever

167 (ND) 162 (ND) 3 g LD, then 12 g/24

hrs

3 g every 6 hrs No Clinical cure 64% 57% ND

Buck et al.,

[173]

Pneumoniae, IAI & fever

of unknown origin

12 (ND) 12 (ND) 2 g LD, then 8 g/24 hrs 4 g every 8 hrs Yes Clinical response 67% 67% ND

Chytra et al.,

[242]

Pneumoniae, IAI, UTI,

CNS infection, SSTI &

blood stream infection

120 (21) 120 (22) 2 g LD, then 4 g/24 hrs 2 g every 8 hrs No Clinical cure 83% 75% 0.18

Bacteriological cure 91% 78% 0.02

ICU mortality 12% 14% 0.7

ICU LOS 10 days 12 days 0.04

De Jongh et al.

[247]

Pneumoniae & UTI 7 (12) 10 (13) 2 g LD, then 4g/24 hrs 2 g every 12 hrs Yes Clinical cure 100% 86% ND

Survival at day 28 100% 86% ND

Dulhunty et al.,

[241]




212 (21) 220 (20) Three different beta-lactams standard ICU daily

doses

No Clinical cure 52% 50% 0.56

Survival at day 90 74% 73% 0.67

Alive ICU-free days 18 20 0.38

Organ failure-free days 6 6 0.27

Duration of bacteraemia 0 0 0.24

Dulhunty et al.,

[166]




30 (21) 30 (23) Three different beta-lactams standard ICU daily

doses

Yes Clinical cure 70% 43% 0.37

ICU mortality 93% 87% 0.67

Days to clinical resolution 11 17 0.14


Georges et al.,

[172]

Pneumoniae & blood

stream infection

24 (45)c 23 (44)c 2 g/12 hrs twice daily 2 g every 12 hrs No Clinical cure 85% 67% ND

Mortality 12% 13% ND

Duration of MV 24 days 25 days ND

ICU LOS 34 days 40 days ND

Hanes et al.,

[254]

Pneumoniae 17 (13) 14 (11) 2 g LD, then 60 mg/kg

every 24 hrs

2 g every 8 hrs Yes Duration of leukocytosis 8 days 11 days 0.35

Duration of pyrexia 8 days 4 days 0.06

Duration of MV 23 days 12 days 0.16


Hospital LOS 41 days 29 days 0.37

Jamal et al.,

[244]




with CVVH

8 8 1 g LD, then 125 mg/hr

every 24 hrs

2 g LD, then 1 g every

8 hrs

Yes Adverse events 0% 0% ND

20

Jamal et al.,

[245]




with CVVH

8 (33) 8 (34) 2.25 g LD, then 37.5

mg/hr every 24 hrs

4.5 g LD, then 2.25 g

every 6 hrs


Lagast et al.,

[262]

Blood stream infection 20 (ND) 25 (ND) Day 1: 1 g LD, then 3

g/24 hrs

Day 2 +: 4 g/24 hrs


ICU mortality 70% 80% ND

Laterre et al.,

[259]


SSTI & blood stream

infection

14 (17) 14 (16) 2 g LD, then 6 g/24 hrs 2 g every 8 hrs Yes Clinical cure 93% 79% NS

ICU mortality 14% 36% NS

Treatment duration 7 days 6 days NS

Lau et al.,

[256]

IAI 81 (8) 86 (8) 2 g LD, then 12 g /24

hrsg

3 g every 6 hrsg No Clinical cure 86% 88% 0.817


Lipman et al.,

[250]




9 (21) 9 (16) 12 mg/kg LD, then 2 g

over 478 mins,

followed by 2 g every 8

hrs

12 mg/kg LD, then 2 g

over 28 mins, followed

by 2 g every 8 hrs


Lubasch et al.,

[258]

Pneumoniae 41 (ND) 40 (ND) 2 g LD, then 2 g/7 hrs

twice daily

2 g every 8 hrs Yes Clinical cure 90% 90% ND

Bacteriological cure 90% 88% ND

Nicolau et al.,

[251]

Pneumoniae 17 (14) 17 (15) 1 g LD, then 3 g/24 hrs 2 g every 8 hrs Yes Adverse events 0% 0% ND

Nicolau et al.,

[252]

Pneumoniae 11 (14) 13 (15) 1 g LD, then 3 g/24 hrs 2 g every 8 hrs Yes Adverse events 0% 0% ND

Nicolau et al.,

[266]

Pneumoniae 17 (14) 18 (16) 1 g LD, then 3 g/24 hrsh 2 g every 8 hrsh No Clinical cure 41% 33% 0.592


Days to defervescence 3 days 5 days 0.015

Days to WCC

normalization

7 days 6 days 0.259

LOS ICU 9 days 9 days 0.691

Pedeboscq et al.,

[261]

IAI 3 (ND) 4 (ND) 12 g/24 hrs 4 g every 8 hrs Yes Mortality 0% 0% ND

Rafati et al.,

[248]




20 (16) 20 (14) 2 g LD, then 8 g/24 hrs 3 g every 6 hrs Yes Mortality 30% 25% 0.72

Decrease in illness

severity

CI>ITd

Duration of pyrexia 2 days 1 day 0.08

WCC normalization 75% 83% ND

Roberts et al.,

[169]




8 (20) 8 (24) Day 1: 4.5 g LD, then

8g/24 hrs

Day 2 +: 13.5 g/24 hrs

4.5 g every 6 hrs or 8

hrs

Yes Survival 100% 100% 1.00

21

Roberts et al.,

[85]




6 (18) 7 (24) Day 1: 4.5 g LD, then

8g/24 hrs

Day 2 +: 13.5 g/24 hrs

4.5 g every 6 hrs or 8

hrs

Yes Clinical cure 100% 100% ND

Roberts et al.,

[86]




5 (ND) 5 (ND) 0.5 g LD, then 3 g/24

hrs

1.5 g LD, then 1 g

every 8 hrs

Yes Survival 60% 100% 0.06

Roberts et al.,

[243]




29 (19) 28 (16) 0.5 g LD, then 2 g/24

hrs

Day 1: 2.5 g/24 hrs

Day 2: 2 g/24 hrs

No Clinical curee 52% 20% 0.04

Mortality 10% 0% 0.25




Sakka et al.,

[171]

Pneumoniae 10 (26) 10 (28) 1 g LD, then 2 g /24 hrs 1 g every 8 hrs Yes Mortality 10% 20% ND

Tamer et al.,

[246]




50 (ND) 50 (ND) 2 g LD, then 4 g/24 hrs 2 g every 8 hrs No Clinical cure 74% 62% 0.198

Mortality at day 28 26% 38% 0.198

SOFA at the EOT 3 5 <0.001

WCC at day 5 of therapy 14 15 0.042

CRP at day 7 of therapy 109 119 0.035

LOS ICU 10 days 12 days <0.001

Van Zanten et al.,

[257]

COPD exacerbation 40 (ND) 43 (ND) 1 g LD, then 2 g/24 hrs 1 g every 8 hrs Yes Clinical cure 93% 93% 0.93

Abbreviation: APACHE, Acute Physiology and Chronic Health Evaluation; CI, continuous infusion; CNS, central nervous system; CRP, C-reactive protein; IAI, intra-abdominal infection; IB, intermittent bolus; ICU,

intensive care unit; LD, loading dose; LOS, length of stay; MV, mechanical ventilation; ND, not described; PK/PD, pharmacokinetic/pharmacodynamic; SOFA, Sequential Organ Failure Assessment; SSTI, skin and skin-

structure infection; UTI, urinary tract infection; WCC, white cell counts.

Legend:

aValues are reported as mean or median.

bBold values indicate statistical significance at p <0.05.

cValues are SAPS scores.

dStatistically significant difference in APACHE II scores on days 2, 3 and 4.

eA priori analysis.

22

1.4.6 Extended beta-lactam infusion

Although potential efficacies have been described, there are unfortunately several drawbacks

associated with CI such as the need for a dedicated IV line (Table 1-4) [13, 15, 264, 277].

Furthermore, some beta-lactams lack the physicochemical stability to be continuously exposed to

room temperatures that may lead to formation of degradation products [278-285]. Thus, extending

the infusion time, typically for three to four hours, has been suggested as an alternative way to

maximize the fT>MIC for some of these antibiotics [13, 286-288]. Several observational and

retrospective studies have suggested potential benefits associated with EI of beta-lactam antibiotics

particularly in patients with severe infections [164, 165, 286, 289-298]. In a recent multicentre,

retrospective cohort study, Yost et al., compared the effectiveness between EI of

piperacillin/tazobactam infusion and IB dosing of comparator antibiotics in 359 patients with

documented Gram-negative infections [295]. The authors found a decrease in mortality in the EI

group (9.7% versus 17.9%; p = 0.02) and further analysis confirmed that the dosing approach

prolonged survival by 2.77 days (p <0.01) in this study. Another non-randomized study of note

reported a significant lower 14-day mortality rate in patients with an Acute Physiology and Chronic

Health Evaluation II (APACHE II) score ≥17 favouring EI compared to IB administration of

piperacillin/tazobactam in critically ill patients infected with P. aeruginosa (12.2% versus 31.6%; p

= 0.04) [298]. Therefore, it has been suggested that EI of beta-lactam antibiotics is a suitable

alternative to IB dosing in critically ill patients. However, further prospective, clinical studies are

required to support the clinical benefits that were reported in these retrospective studies.

23

Table 1-4: Possible advantages and disadvantages of employing CI versus IB dosing of beta-

lactam antibiotics

Administration

method

Advantages Disadvantages

Continuous infusion Stable and predictable antibiotic PK

profiles

Intensive educational effort to

update clinical staff on the

administration method prior to

implementation

Lower antibiotic daily dose is a

possibility with this approach

Requires special infusion pumps

and infusion bags that are costly

Reduces drug acquisition costs

when lower antibiotic doses are

used

Some beta-lactams are not stable

under prolonged exposure at room

temperature

Intermittent bolus Effective resource consumption

(e.g., reduce the time required for

pharmacists or nurses to prepare

and administer antibiotic)

Risk of drug wastage is high with

this approach (e.g., when a patient

dies during treatment)

A simple antibiotic administration

method

PD targets may not be met

especially in critically ill patients

Does not require dedicated line

access for drug administration thus

incompatibility with other drugs is

not an issue

Neurological adverse effects are

theoretically more possible with

high Cmax

Less likely to have unexpected

device failures and dosing delivery

rate error

Abbreviation: Cmax, peak drug concentration over a dosing interval; PK, pharmacokinetic; PD,

pharmacodynamic.

1.4.6.1 Doripenem

Doripenem is a new member in the carbapenem class of beta-lactam antibiotics, which

demonstrates broad antibiotic coverage against Gram-positive, Gram-negative and anaerobic

pathogens including the highly resistant multi-drug resistant (MDR) strains [299, 300].

Furthermore, doripenem has enhanced activity compared to meropenem against P. aeruginosa

(doripenem minimum inhibitory concentration required to inhibit the growth of 90% of organisms

[MIC90]; 8 mg/L versus meropenem MIC90; 16 mg/L), one of the most frequently isolated

pathogens in the ICU [300]. With promising results in several clinical studies, doripenem has been

approved for the treatment of severe infections namely complicated intra-abdominal infections

24

[301], complicated urinary tract infections [302-304] and for nosocomial pneumonia [305, 306]. In

all these studies, doripenem was reported as effective and non-inferior to its comparator drug (i.e.,

imipenem, meropenem, piperacillin/tazobactam or levofloxacin) and to significantly reduce

mechanical ventilation and hospitalization days [307-312].

In the earlier phase of development, doripenem dosing was guided using a PK/PD approach [313-

316]. This approach is especially important for finding the most advantageous dosing regimen for

the treatment of less susceptible Gram-negative pathogens. Like other beta-lactams, doripenem

displays time-dependent activity whereby its efficacy is related to fT>MIC [317-319]. Combined with

its favourable stability profile, administering doripenem via EI to extend the fT>MIC is an appropriate

and appealing approach compared to CI and IB dosing. Furthermore, several PK/PD modelling

studies have provided data supporting extended doripenem infusion particularly if severe infections

are involved [53, 185-188, 313-316, 320-326].

A typical doripenem dose of 500 mg to 1000 mg every 8 hours, administered as a 1- to 4-hour IV

infusion, is recommended to enhance PK/PD target attainment, especially when dealing with severe

infections [313, 314, 316, 326]. However, to date, population PK/PD models to describe doripenem

usage have mostly been developed in heterogeneous patient groups [313, 314, 316, 326-329] which

are unlikely to address the PK differences and the disease severity of critically ill patients [6-8,

330]. For example, a doripenem dose of 500 mg every 8 hours as a 1-hour infusion is only effective

against pathogens with a MIC of ≤2 mg/L. This standard doripenem dose is likely to fail in

critically ill patients, who may have altered PK and who are commonly infected with pathogens

with higher MICs [331-335]. In this context, it is important to highlight the recent termination of an

industry-sponsored clinical trial investigating the use of doripenem in ventilator-associated

pneumonia (VAP) [336]. This phase III, prospective, multicentre, double-blind RCT aimed to

demonstrate the non-inferiority of a fixed 7-day course of doripenem (1 g every 8 hours as a 4-hour

infusion) compared to a 10-day course of imipenem-cilastatin (1 g every 8 hours as a 1-hour

infusion) in adult patients with VAP. The trial was terminated when interim analyses showed

greater clinical failure and mortality rates in the doripenem treatment arm. Further analysis (i.e.,

modified intention to treat [mITT] analysis group) also revealed that patients receiving doripenem

with high CLCR (150 mL/min) had clinical cure rates that were 27% worse than the comparator

group (doripenem 44.4% versus imipenem-cilastatin 71.4%, 95% confidence interval: -55.4% to

1.4%). This among other findings [187, 188, 322, 337] indicates that “one-dose-fits-all” dosing

approach is no longer relevant in critically ill patients due to their possible altered physiology and

25

thus, PK/PD analyses of doripenem are needed to develop clinically relevant dosing guidelines in

this population.

1.4.7 Summary

Several important pathophysiological changes in critically ill patients may alter antibiotic PK and

consequently influence PK/PD target attainment. Use of a standard dosing regimen, which is

usually derived from healthy volunteers, does not address the altered PK phenomenon and may

increase the likelihood of therapeutic failure. Furthermore, pathogens that are commonly isolated in

the ICU differ from the general wards in a way that their MICs tend to be relatively higher [334,

335]. Altered dosing approaches (i.e., CI and EI) may be needed to ensure effective antibiotic

exposure and may produce better therapeutic outcomes in critically ill patients.

26

Aims

This Thesis aims to better characterize the PK/PD of beta-lactam antibiotics in critically ill patients

and to determine whether there is any therapeutic advantage associated with the PI dosing strategy

(i.e., CI and EI) as compared to traditional IB dosing in this unique patient population.

The specific aims of the Thesis are:

1. To describe the population PK of doripenem in critically ill patients with sepsis in a

Malaysian ICU and to investigate sources of PK variability

To determine PK parameter estimates of doripenem in critically ill patients with

sepsis.

To identify potential covariates which would help to explain PK variability in this

population.

To develop clinically relevant dosing guidelines for this population which would

help to maximize therapeutic efficacy and minimizing antibiotic resistance.

2. To review the published literature describing the PK/PD and clinical outcomes associated

with CI versus IB dosing of beta-lactam antibiotics in hospitalized patients.

3. To perform a post hoc analysis on the Defining Antibiotic Levels in Intensive care unit

patients (DALI) study data to compare the PK/PD and clinical outcomes associated with PI

(i.e., CI and EI) versus IB dosing of beta-lactam antibiotics in a large cohort of critically ill

patients.

4. To identify the methodological shortcomings associated with current clinical studies seeking

to compare CI versus IB and to describe the criteria that should be considered for

performing a definitive clinical trial of this intervention in critically ill patients.

5. To perform a randomized controlled trial in order to determine if CI administration of beta-

lactam antibiotics is associated with improved clinical outcomes as compared to IB dosing

in a large cohort of critically ill patients with severe sepsis in a Malaysian ICU setting.

6. To review the published literature on the relevance of PK exposure and PD characteristics of

different antibiotic classes on maximizing therapeutic efficacy and minimizing development

of antibiotic resistance in critically ill patients.

27

Chapter 2: Population pharmacokinetics of doripenem in critically ill

patients with sepsis

2.1 Synopsis

Beta-lactam antibiotics are commonly used to treat severe infections due to their wide antibiotic

spectrum and overall tolerability. However, inappropriate usage has contributed to increases in

resistance to many beta-lactams and consequently, threatens the utility of this antibiotic family.

Furthermore, infection caused by MDR pathogens, such as P. aeruginosa, is significantly

associated with patient’s morbidity and mortality. Doripenem, the latest addition to the carbapenem

class of antibiotic, offers a glimmer of hope in the management of severe Gram-negative infections

as it demonstrates broad antimicrobial coverage against Gram-positive, Gram-negative and

anaerobic pathogens, including the “troublesome” MDR strains. For this reason, doripenem has

been approved for several indications, including complicated intra-abdominal infections,

complicated urinary tract infections and for nosocomial pneumonia. Like other beta-lactam

antibiotics, the length of time that drug concentrations remains above the MIC of infection-causing

pathogen is related to doripenem’s effectiveness. A typical doripenem dose of 500 mg to 1000 mg

every 8 hours, administered as a 1-hour IV infusion, is currently recommended for severe

infections. However, this dosing recommendation was developed based on the PK of doripenem in

healthy volunteers and therefore, pathophysiological alterations in critically ill patients were not

taken into consideration. As reported in previous studies, failing to account for critical-illness

related changes may lead to inadequate antibiotic exposure and therapeutic failure. Furthermore,

previous PK/PD analyses of doripenem have mainly been performed in non-infected, heterogeneous

Caucasian patient groups and therefore, the existing PK data may not accurately characterize the PK

differences of other population such as in the Malaysian critically ill population. This chapter

therefore aims to describe the population PK of doripenem in Malaysian critically ill patients with

sepsis and use Monte Carlo dosing simulations to develop clinically relevant dosing guidelines

specifically for these patients.

28

2.2 Manuscript entitled “Population pharmacokinetics of doripenem in

critically ill patients with sepsis in a Malaysian intensive care unit”

The manuscript entitled “Population pharmacokinetics of doripenem in critically ill patients with

sepsis in a Malaysian intensive care unit” has been accepted for publication in the Antimicrobial

Agents and Chemotherapy (2015).

The co-authors contributed to the manuscript as follows: Conception and development of the study

design was performed by the PhD candidate, Mohd-Hafiz Abdul-Aziz, under the guidance of Prof.

Jason A. Roberts and Dr. Christine E. Staatz. Literature review was performed by the PhD

candidate, Mohd-Hafiz Abdul-Aziz, under the guidance of Prof. Jason A. Roberts and Dr. Christine

E. Staatz. Data collection was performed by the PhD candidate, Mohd-Hafiz Abdul-Aziz, Azrin N.

Abd Rahman and Dr. Mohd-Basri Mat-Nor. Sample bioanalysis was performed by the PhD

candidate, Mohd-Hafiz Abdul-Aziz, under the supervision of Dr. Steven C. Wallis. PK/PD analysis

was performed by the PhD candidate, Mohd-Hafiz Abdul-Aziz and Azrin N. Abd Rahman under

the supervision of Prof. Jason A. Roberts and Dr. Christine E. Staatz. The PhD candidate took the

leading role in manuscript preparation and all co-authors reviewed and contributed to the final draft

of the manuscript.

The accepted version of this manuscript is presented and incorporated in this chapter. However,

some text, tables and figures may have been inserted at slightly different positions to fit the overall

style of the thesis. Numbering of pages, tables and figures may also change to fit the thesis

requirements. Manuscript references have been collated with all other references in the thesis.

Permission has been granted by the publisher and copyright owner, American Society of

Microbiology, to reproduce the manuscript in this Thesis.

29

Population pharmacokinetics of doripenem in critically ill patients with sepsis in a Malaysian

intensive care unit

Authors

Mohd H. Abdul-Aziz (1, 2), Azrin N. Abd Rahman (2, 3), Mohd-Basri Mat-Nor (4), Helmi

Sulaiman (5), Steven C. Wallis (1), Jeffrey Lipman (1, 6), Jason A. Roberts (1, 6), Christine E.

Staatz (3, 7)

Affiliations

(1) Burns, Trauma and Critical Care Research Centre, The University of Queensland, Brisbane,

Australia.

(2) School of Pharmacy, International Islamic University of Malaysia, Kuantan, Pahang, Malaysia.

(3) School of Pharmacy, The University of Queensland, Brisbane, Australia.

(4) Department of Anaesthesiology and Intensive Care, School of Medicine, International Islamic

University of Malaysia, Kuantan, Pahang, Malaysia.

(5) Infectious Diseases Unit, Department of Medicine, Faculty of Medicine, University of Malaya,

Kuala Lumpur, Malaysia.

(6) Royal Brisbane and Women’s Hospital, Brisbane, Australia.

(7) Australian Centre of Pharmacometrics, Brisbane, Australia.

Running title: Population pharmacokinetics of doripenem.

Keywords: beta-lactams; carbapenems; intensive care; modelling; pharmacodynamics; prolonged

infusion.

Corresponding author:

Mr. Mohd Hafiz Abdul Aziz,

Burns, Trauma & Critical Care Research Centre, The University of Queensland,

Level 3, Ned Hanlon Building, Royal Brisbane & Women’s Hospital,

Herston, Queensland 4029, Australia

Ph +61736361847; Fax +61736463524

Email: [email protected]

mailto:[email protected]

30

2.2.1 Abstract

Doripenem has been recently introduced in Malaysia and is used for severe infections in the ICU.

However, limited data currently exist to guide optimal dosing in this scenario. We aimed to describe

the population PK of doripenem in Malaysian critically ill patients with sepsis and use Monte Carlo

dosing simulations to develop clinically relevant dosing guidelines for these patients. In this PK

study, 12 critically ill adult patients with sepsis receiving 500 mg of doripenem 8-hourly as a 1-hour

infusion were enrolled. Serial blood samples were collected on two different days and population

PK analysis was performed using a non-linear mixed effects modelling approach. A two-

compartment linear model with between-subject and between-occasion variability on CL was

adequate in describing the data. Typical Vd and CL of doripenem in this cohort was 0.47 L/kg and

0.14 L/kg/hr, respectively. Doripenem CL was significantly influenced by patients’ CLCR such that

a 30 mL/min increase in estimated CLCR would increase doripenem CL by 52%. Monte Carlo

dosing simulations suggested that for pathogens with a MIC of 8 mg/L, a dose of 1000 mg 8-hourly

as a 4-hour infusion is optimal for patients with CLCR of 30-100 mL/min whilst a dose of 2000 mg

8-hourly as a 4-hour infusion is best for patients manifesting a CLCR >100 mL/min. Findings from

this study suggest that for doripenem usage in Malaysian critically ill patients, an alternative dosing

approach may be meritorious, particularly when MDR pathogens are involved.

31

2.2.2 Introduction

Doripenem, a member of the carbapenem class of antibiotics, demonstrates broad antibiotic activity

including against the troublesome MDR pathogens [338]. The PK profile of doripenem closely

resembles that of other carbapenems. Similarly, this antibiotic demonstrates time-dependent

activity, where the PK/PD index that best correlates with its efficacy is fT>MIC [317]. Doripenem has

been approved for complicated intra-abdominal and urinary tract infections in the United States, and

is also indicated for nosocomial pneumonia in Europe and the Asia-Pacific. In Malaysia, doripenem

is commonly reserved for the management of complicated infections deemed to be caused by P.

aeruginosa and to some extent, Acinetobacter baumannii. As per local antibiotic guidelines,

patients receiving doripenem in a Malaysian ICU typically receive a standard dose of 500 mg 8-

hourly as a 1-hour IV infusion. However, the appropriateness of this dosing regimen is disputable as

it is based on PK/PD data derived from earlier studies which mostly recruited heterogeneous

cohorts of healthy volunteers and non-critically ill Caucasian patients [313, 314, 316, 326].

Importantly, results of subsequent PK/PD studies suggest that current recommendations may be

grossly flawed in critically ill patients and optimal dosing requirements may significantly differ

from that initially proposed [187, 188, 322].

Antibiotic dosing in critically ill patients is rarely a straightforward process [6]. Extreme alterations

in antibiotic PK, particularly increases in Vd and profound increases or decreases in renal drug CL,

are common occurrences in the ICU and may severely influence drug exposure [56, 121]. To further

complicate matters, pathogens that are usually isolated in the ICU differ from general wards, as they

are commonly less susceptible to the current antibiotic armamentarium [334, 335]. Additionally,

local microbiology and antibiotic resistance patterns may greatly vary across different geographical

regions affecting antibiotic dosing requirements [332]. In this context, it is imperative to consider

regional antibiotic susceptibility data whereby in the Asia-Pacific region, the MIC90 for doripenem

against P. aeruginosa was reported as 8 mg/L [332, 333]. As previously mentioned, the commonly

administered dose of 500 mg 8-hourly as a 1-hour infusion is reported to only be effective against

pathogens with an MIC of ≤2 mg/L and its application is therefore likely to fail in such a scenario

[313, 316].

Current population PK models which describe doripenem disposition have mostly been developed

in heterogeneous Caucasian patient groups [186, 187, 313, 314, 316, 321, 322]. However, it is

likely that the PK of doripenem may vary across different races and therefore, the existing PK

models may not accurately characterize the PK differences in Malaysian critically ill patients [339].

32

Interethnic differences, such as relatively smaller body size and lower body fat distribution among

Malaysian critically ill patients as opposed to their Caucasian counterparts, may influence

doripenem exposure and consequently, dosing requirements may also differ between these two

patient populations.

In this study, we aimed to describe the population PK of doripenem in Malaysian critically ill

patients with sepsis and also, to investigate sources of PK variability. With this resulting model, we

then sought to develop clinically relevant dosing guidelines specifically for these patients.

2.2.3 Materials and methods

2.2.3.1 Setting

This prospective, open-label PK study was undertaken in a general ICU of a tertiary hospital in

Pahang, Malaysia between November 2012 and October 2013. The study was registered and

approved by the Medical Research Ethics Committee Malaysia (ID: NMRR-12-649-13058).

Written informed consent to participate in the study was obtained from each participant or their

legally-authorized representative.

2.2.3.2 Study population

Patients were eligible for recruitment if they were; (a) adult (≥18 years old) ICU patients; and (b)

were prescribed doripenem for the treatment of sepsis (defined as presumed or confirmed infection

with SIRS manifesting in the previous 48 hours). Patients were excluded if they; (a) required any

form of extracorporeal renal support; (b) were pregnant or lactating mothers; or (c) were known or

presumed to be allergic to doripenem or any of the carbapenem antibiotics.

2.2.3.3 Doripenem administration and ancillary treatments

Doripenem (Doribax®; Janssen-Cilag, Raritan, NJ) was administered over 1-hour using a

volumetric infusion pump controller at a dose of 500 mg in 100 mL of 0.9% sodium chloride as part

of the patients prescribed course of therapy. All subsequent patient management, including the

addition of other antibiotics and drugs, was at the discretion of the treating clinician and was not

affected by study procedures.

33

2.2.3.4 Study protocol

PK sampling was performed during one 8-hour dosing interval on Day 1 (i.e., representing a

scenario when patients were presumed to be at their worst clinically) and Day 3 (i.e., representing a

scenario when patients were presumed to be more clinically stable) of doripenem treatment. Blood

samples (3 mL) were drawn from a central line and were collected into lithium-heparinised tubes at

the following times on Day 1 (occasion 1) and Day 3 (occasion 2) of therapy, immediately before

the first doripenem dose was administered, then 0.5, 0.75, 1, 1.5, 2, 4, and 8 hours after the start of

the infusion.

Blood samples were immediately refrigerated at 4°C and within 1 hour, centrifuged at 3000 rpm for

10 minutes to separate plasma. Plasma samples were frozen at -80°C within 24 hours of collection.

The frozen plasma samples were shipped on dry ice by a commercial courier company and were

then assayed at the Burns, Trauma and Critical Care Research Centre (BTCCRC), The University of

Queensland, Australia.

Apart from blood collection, various demographic, anthropometric and clinical data were also

collected prospectively. The severity of illness indices, which included the APACHE II score on

admission [340] and the SOFA scores on each occasion of sampling [52], were recorded. CLCR was

estimated on each occasion of sampling using the Cockcroft-Gault formula [341].

2.2.3.5 Doripenem assay

Doripenem concentrations in plasma samples were measured, after protein precipitation, by a

validated high-performance liquid chromatography (HPLC) method with ultraviolet detection on a

Shimadzu Prominence (Shimadzu Corporation, Kyoto, Japan) instrument. Cefotaxime was used as

the internal standard. Samples were assayed in batches, alongside calibration standards and quality

control replicates at high, medium and low concentrations. All bioanalysis techniques were

conducted in accordance with the US Food and Drug Administration’s guidance for industry on

bioanalysis [342]. The assay limit for doripenem in plasma was 0.2 mg/L, with precision and

accuracy determined at 5.7% and 4.4%, respectively. Linearity of the assay was demonstrated in the

range of 0.2-100 mg/L. Inter-assay precision and accuracy, determined at three different

concentrations over three separate days, were all within 7%. Observed concentrations of doripenem

were corrected for protein binding by reducing the concentrations by 10% [343].

34

2.2.3.6 Population pharmacokinetic analysis

2.2.3.6.1 Software

Plasma concentration-time data for doripenem were analysed using non-linear mixed-effect

modelling approach in NONMEM® version 7.3 (Icon Development Solutions, Ellicott City, MD,

USA) with an Intel® FORTRAN compiler and Perl-Speaks-NONMEM® (PsN) version 4.0 [344].

Throughout the model building process, typical population PK parameter estimates, between-

subject variability (BSV), between-occasion variability (BOV) and residual unexplained variability

(RUV) were estimated using the first-order conditional estimation with interaction (FOCE-I)

method. Data exploration and visualization, as well as model diagnostics were performed using PsN

version 4.0 [345], Pirana version 2.7.1 [346], and Xpose version 4.0 (http://xpose.sourceforge.net) in

R (http://www.r-project.org) [347].

2.2.3.6.2 Structural and stochastic model development

Plasma concentration-time data for doripenem were fitted to one-, two- and three-compartment

disposition models with first-order elimination using the ADVAN subroutines from the

NONMEM® library. BSV and BOV were evaluated using an exponential variability model. BSV

was evaluated on all PK parameter estimates and when significant, it was then included in the next

model-building step. Covariance between values of BSV was estimated using a variance-covariance

matrix. Additive, proportional and combined residual random error models were tested to describe

RUV.

Competing models were assessed on the basis of minimum objective function value (OFV),

goodness-of-fit diagnostics and their physiological plausibility. A reduction in the OFV of >3.84 for

one-degree of freedom was considered a statistically significant improvement (p <0.05) for a nested

model. Observed versus population predicted concentration (PRED) or individual predicted

concentration (IPRED) plots, individual weighted residual (IWRES) versus IPRED plots, and

conditional weighted residual (CWRES) versus time after dose plots were used to evaluate the

graphical goodness-of-fit of various models.

2.2.3.6.3 Covariate screening and model development

Potential covariates that were clinically plausible were screened for their influence on the PK of

doripenem. Factors tested included patient total body weight, estimated CLCR and SOFA score on

http://xpose.sourceforge.net/

http://www.r-project.org/

35

the day of investigation. Covariate effects were identified via visual (scatter plots) and also

numerical (stepwise, generalized additive models by Xpose version 4.0) methods. Allometric

scaling was applied a priori and fixed to theory based values of ¾ for CL and 1 for Vd, all

standardized to a bodyweight of 70 kg [348]. The covariate-parameter models that were evaluated

were linear, piecewise-linear, exponential, power and sigmoidal models. During the covariate

model-building process, stepwise forward inclusion and backward elimination approaches were

employed. A reduction in the OFV of >3.84 (p <0.05) and >10.83 (p <0.01) was required for a

covariate to be considered significant in the forward inclusion and backward elimination steps,

respectively.

2.2.3.6.4 Model evaluation and prediction

A non-parametric bootstrap method (n = 2000) was used to assess the final model accuracy and

stability. From the bootstrap empirical posterior distribution, 95% confidence interval for the

bootstrap replicates were obtained and compared with parameter estimates from the final model. A

visual predictive check (VPC) was also performed by simulating 5000 patients to evaluate the

predictive performance of the final model. Visual checks were performed by overlaying the

observed data points with the 95% confidence intervals of the simulated 5th, 50th and 95th percentile

curves.

2.2.3.6.5 Dosing simulations

Different doripenem dosing regimens in subjects with various degrees of renal function were

examined using Monte Carlo simulation in NONMEM®. Final PK model parameter estimates were

used to generate concentration-time profiles based on 1000 simulations. Both a 1- and 4-hour

infusion of 250 mg, 500 mg, 1000 mg and 2000 mg of doripenem every 8 hours was examined in

subjects with a CLCR of 30 mL/min, 50 mL/min, 70 mL/min, 100 mL/min and 150 mL/min,

respectively. The probability of target attainment (PTA) for a dosing regimen was calculated as the

percentage of patients achieving an fT>MIC of 40% for a given MIC. These probabilities were then

plotted against a range of MICs and optimal dosing was denoted by achieving at least 90% PTA.

36

2.2.4 Results

2.2.4.1 Demographic and clinical data

A total of 140 plasma samples across two sampling occasions were collected from 12 critically ill

patients. Demographic and clinical characteristics of the recruited patients are presented in Table 2-

1. More than 65% of the cohort were males and ≥45 years of age. Median APACHE II and SOFA

score on admission was 19 and 6, respectively. Median SOFA scores were similar on both sampling

occasions. More than half of the patients had an estimated CLCR of ≥80 mL/min on ICU admission.

The median CLCR on occasion 1 (88.0 mL/min) was higher than on occasion 2 (72.0 mL/min). The

majority (66.7%) received doripenem for VAP and the most prevalent causative pathogen identified

was A. baumannii. All patients required invasive mechanical ventilation and vasopressor support.

Three patients died during their ICU stay and the deaths were more likely to be related to patients’

pre-existing comorbidities and progressive worsening of their clinical conditions. All three patients

had a pre-ICU hospital stay of ≥2 months prior to study inclusion.

2.2.4.2 Pharmacokinetic model-building

The time course of doripenem in plasma was adequately described by a two-compartment linear

model with combined residual error. BSV on CL (ΔOFV = -97.1), central volume of distribution

(V1; ΔOFV = -46.6) and peripheral volume of distribution (V2; ΔOFV = -8.04) significantly

improved the model fit. Introduction of BOV on CL (ΔOFV = -26.9) resulted in further model

improvement.

During covariate testing inclusion of an influence of CLCR (normalized to the population mean

value of 82.5 mL/min) on CL improved the model fit (decreasing the OFV by 32.3 points and

reducing BSV on CL from 56.7% to 10.4%). The influence of CLCR on CL of doripenem was best

described in an exponential relationship as shown in Eq. 1:

(1)

where CL is the estimated doripenem clearance in a given individual (in L/hr/70 kg), θCLpop is the

typical value of doripenem clearance in the population; describes the influence of creatinine

clearance on doripenem clearance and CLCR is the patient’s estimated creatinine clearance (in

mL/min). Typical PK parameter estimates from the base and final model are summarized in Table

2-2.

37

Table 2-1: Clinical and demographic details of the enrolled patients

Subject Sex Age

(in years)

BMI

(kg/m2)

APACHE IIa SOFAb Admission diagnosis CLCR

(mL/min)c

Causative

pathogen

Clinical outcome

1 M 68 23.4 22 10 Intra-abdominal sepsis 30 Nil Survived

2 M 39 21.8 17 7 VAP 77 A. baumannii Died

3 F 19 16.7 11 3 VAP 161 A. baumannii Survived

4 M 74 29.7 18 5 Intra-abdominal sepsis 65 A. baumannii Died

5 M 61 29.7 12 6 VAP 119 Nil Survived


7 M 31 22.6 16 7 Intra-abdominal sepsis 92 Nil Survived

8 M 44 20.8 21 5 VAP 126 A. baumannii Died


10 M 58 24.7 20 5 VAP 44 A. baumannii Survived

11 M 57 19.3 15 4 VAP 99 P. aeruginosa Survived

12 F 31 22.2 23 5 Intra-abdominal sepsis 66 Nil Survived

Median 52 22.9 19 6 85

IQR 33-60 21.1-24.6 15-22 5-7 49-118

Abbreviation: APACHE II, Acute Physiology and Chronic Health Evaluation II; BMI, body mass index; CLCR, estimated Cockcroft-Gault creatinine

clearance; F, female; M, male; SOFA, Sequential Organ Failure Assessment; VAP, ventilator-associated pneumonia.

Legend:

aAPACHE II score on admission.

bSOFA score on admission.

cEstimated creatinine clearance on admission.

38

Table 2-2: Typical population parameter estimates for the base and final covariate model and

the 2000 bootstrap runs

Base

Model

Final

Model

Bootstrap (n = 2000)

Mean Median 95% CI

2.5% 97.5%

Objective function value,

OFV

381.03 348.76

Fixed effects

CL (L/hr/70kg) 11.5 10.1 9.9 9.9 8.9 10.9

V1 (L/70kg) 15.5 15.5 16.1 15.8 10.5 22.0

V2 (L/70kg) 17.9 17.7 18.6 18.1 12.2 26.6

Q (L/hr/70kg) 36.6 36.3 36.1 36.8 28.4 41.5

- 0.014 0.014 0.014 0.012 0.017

Between-subject variability,

BSV

CL (%) 56.7 10.4 14.8 14.3 4.8 21.5

V1 (%) 62.0 59.7 59.3 57.2 22.8 87.0

V2 (%) 73.3 73.8 68.4 64.7 40.0 94.0

Between-occasion

variability, BOV

CL (%) 33.9 22.2 16.2 8.7 4.11 28.3

Random error

Proportional (% CV) 8.3 9.0 10.0 9.1 3.7 18.8

Additive (SD, mg/L) 1.31 1.25 0.97 1.17 0.17 1.64

Abbreviation: CL, clearance; CV, coefficient of variation; Q, inter-compartmental clearance; V1,

volume of distribution of central compartment; V2, volume of distribution of peripheral

compartment; , effect of estimated Cockcroft-Gault creatinine clearance on doripenem

clearance.

Final model:

39

Basic goodness-of-fit plots, including the CWRES versus time after dose plot, demonstrated that the

final model adequately described the data with little model mis-specification (Figure 2-1). PRED

and IPRED values were in good agreement with observed doripenem concentrations. CWRES

values were generally homogeneously distributed over the sampling period. In a VPC plot

associated with the final model the predicted median curve demonstrated a good fit to the observed

data, albeit with a slight over-prediction of concentrations during the elimination phase (Figure 2-

2). Results from the non-parametric bootstrap further corroborated the robustness of the final

model, demonstrating narrow 95% confidence interval with bootstrap median values close to typical

population PK parameter estimates of the final model (Table 2-2).

Figure 2-1: Goodness-of-fit plots associated with final population pharmacokinetic model for

doripenem

Legend: The solid black line represents the line of identity and the dashed grey line represents the

smooth fitting for observations. Clinical observations are represented by the black solid circles.

40

Figure 2-2: Visual predictive check plot associated with the final population pharmacokinetic

model for doripenem

Legend: The solid black circles represent the observed data, the solid grey line represents the 50th

percentile of the observed data, the solid black line represents the 50th percentile of the simulated

data, the dashed grey lines represent the 5th and 95th percentiles of the observed data, the dashed

black lines represent the 5th and 95th percentiles of the simulated data and the shaded areas represent

the 95% confidence intervals of the 5th, 50th and 95th percentiles of the simulated plasma

concentrations.

2.2.4.3 Dosing simulations

The PTA for 40% fT>MIC for various doripenem dosing regimens, with varying MIC and CLCR

values, are presented in Figure 2-3. In patients with a CLCR of 70 mL/min, a standard doripenem of

500 mg 8-hourly as a 1-hour infusion demonstrated optimal rates of PTA (>90%) against pathogens

with an MIC of ≤2 mg/L. In other scenarios, alternative dosing strategies showed better rates of

target attainment; with 1000 mg and 2000 mg 8-hourly as a 4-hour infusion demonstrating optimal

rates of PTA against pathogens with an MIC of ≤8 and ≤16 mg/L, respectively. Increasing CLCR

values were associated with lower rates of PTA for the same MIC. With increasing MIC values, the

likelihood of obtaining optimal PTA diminishes whilst increasing the dose and prolonging the

duration of infusion resulted in higher rates of PTA.

41

Figure 2-3: The probability of target attainment for various simulated doripenem dosing

regimens to achieve 40% fT>MIC in patients with a creatinine clearance of (a) 30 mL/min; (b)

50 mL/min; (c) 70 mL/min; (d) 100 mL/min; and (e) 150 mL/min

Abbreviation: MIC, minimum inhibitory concentration.

Legend: The dashed black lines denote optimal doripenem dosing, which was signified by

achieving at least 90% of probability of target attainment.

2.2.5 Discussion

Despite profound PK and physiological differences to the non-critically ill population, critically ill

patients are typically given conventional dosing regimens [27], potentially leading to sub-optimal

antibiotic exposure and subsequently, therapeutic failures. Failure of emerging antibiotics in several

recent clinical trials recruiting critically ill patients underscores the deficiencies associated with the

licensed “one-dose-fits-all” dose in this unique population [336, 349]. Furthermore, the

ramifications of this simplistic dosing approach may be more severe in some geographical regions,

42

particularly among the Southeast Asian countries, where local microbiology and antibiotic

resistance patterns significantly vary from that of the Western countries. In our current study, we

were able to demonstrate how bacterial susceptibility and physiological changes associated with

critical illness substantially influence optimal doripenem exposure and importantly, how these

alterations may be circumvented via alternative dosing strategies.

In our cohort of critically ill patients, the PK of doripenem was best described using a two-

compartment model with zero-order input and first-order elimination. Such a disposition model is in

agreement with other currently available literature in critically ill patients with conserved renal

function [185-188]. Typical Vd (V1 + V2) of doripenem in our cohort was 0.47 L/kg (range: 0.14-

1.7 L/kg), which is generally consistent with other reports in critically ill patients with conserved

renal function (0.30-0.54 L/kg) [185-188]. This estimate is considerably larger than that previously

described in healthy volunteers (0.22-0.24 L/kg) [328, 329] and non-critically ill patients (0.18-0.24

L/kg) [320, 321, 323, 327]. This is anticipated as the Vd of hydrophilic antibiotics, such as

aminoglycosides [350, 351] and beta-lactams [56], are often reported to be two-fold greater in

critically ill patients. This could be attributed to extreme fluid extravasation into the interstitium, a

phenomenon commonly associated with increasing sickness severity [61]. Furthermore, medical

interventions including aggressive fluid resuscitation [66] and mechanical ventilation [71], both of

which were provided to all of our patients during their earlier course of therapy, have been

associated with increased Vd.

Typical CL of doripenem in this cohort was 0.14 L/kg/hr (range: 0.06-0.45 L/kg/hr), which is

generally consistent with that reported in critically ill patients with conserved renal function (0.12-

0.25 L/kg/hr) [185-188]. However, this estimate is notably lower than that previously described in

healthy volunteers (0.22-0.25 L/kg/hr) [328, 329] and non-critically ill patients (0.16-0.25 L/kg/hr)

[320, 322, 323, 327]. The differences are expected as the non-critically ill population would

presumably have better end-organ function than our patient cohort. Consistent with previous data

[185, 313, 320, 327], estimated Cockcroft-Gault CLCR, a surrogate measure for renal function in our

analysis albeit being less accurate as measured CLCR, was a key predictor of doripenem CL. This

relationship is highly predictable since doripenem is extensively cleared via renal elimination;

approximately 75% and in some reports, up to 90% of doripenem is cleared via the renal route

[329]. Based on Eq. 1, a 30 mL/min increase in the estimated CLCR would increase doripenem CL

by 52%.

43

Our model was also significantly improved with the incorporation of BOV on CL, denoting a

certain degree of variability in doripenem CL between the first and second sampling occasion.

Based on Eq. 1, doripenem CL on Day 1 (0.16 L/kg/hr) was approximately 30% higher than on Day

2 (0.12 L/kg/hr). Essentially, this means that dosing requirements in this population may be

dynamic and as such, regular dosing reviews and modifications may also be needed throughout

antibiotic treatment. Given the variability in antibiotic exposures is being increasingly reported in

critically ill patients, beta-lactam therapeutic drug monitoring (TDM) is highly warranted in this

population and the approach would appear to be meritorious, not only to prevent underdosing which

may increase the likelihood of antibiotic resistance, but also to minimize the risk of adverse effects

during therapy.

ARC [109] is highly prevalent in most ICU settings (17.9-41.1%) [352, 353], including Malaysian

critically ill populations [354] and has been linked with sub-therapeutic concentrations of beta-

lactams and poor clinical outcomes [120, 121, 164]. In patients with an elevated CLCR (≥130

ml/min), a conventional “one-dose-fits-all” approach to doripenem dosing appears to be grossly

flawed. Our Monte Carlo simulations highlighted that while a standard dose of 500 mg 8-hourly as

a 1-hour infusion in a patient with a CLCR of 70 mL/min would have 98.7% PTA against pathogens

with an MIC of 2 mg/L, a patient with ARC manifesting a CLCR of 150 mL/min, would only have

9.9% PTA. The repercussions of neglecting the phenomenon when dosing antibiotics in critically ill

patients can be highlighted by the premature termination of a Phase III, prospective, multicentre,

double-blind, RCT comparing a fixed 7-day course of doripenem (1000 mg 8-hourly as a 4-hour

infusion) with a 10-day course of imipenem-cilastatin (1000 mg 8-hourly as a 1-hour infusion) in

critically ill adult patients with VAP [336]. The trial was terminated when interim analyses revealed

greater clinical failure and mortality rates in the doripenem treatment arm. Crucially, further

analysis in the modified intention to treat group also showed that patients receiving doripenem with

high CLCR (>150 mL/min) had clinical cure rates 27% worse than the comparator group (95%

confidence interval 1.4% to 55.4%). Essentially, patients at high risk of ARC, such as young trauma

patients without significant organ dysfunction [109], need to be identified early so that appropriate

dose modifications can be implemented immediately.

In Malaysia, particularly in our ICU, doripenem monotherapy is reserved for the management of

complicated infections deemed to be caused by P. aeruginosa, and to some extent A. baumannii. In

two large antibiotic susceptibility prevalence studies conducted in the Asia-Pacific region [332,

333], the MIC90 for doripenem against P. aeruginosa was 8 mg/L. Our data suggest that for such an

MIC, a dose of 1000 mg 8-hourly as a 4-hour infusion is optimal for patients with CLCR of 30-100

44

mL/min and a dose of 2000 mg every 8-hourly as a 4-hour infusion is best for patients manifesting a

CLCR >100 mL/min. Such recommendations are consistent with several large PD simulation studies

conducted in the Asia-Pacific region [331, 355] as well as other parts of the world [314, 356]. This

study provides additional PK/PD data to support an alternative doripenem dosing approach in

critically ill patients, particularly when pathogens with high MIC are involved. However, future

clinical studies, preferably in the form of a multinational RCT, are required to ascertain the clinical

efficacy and safety of the suggested doripenem dosing regimen in this patient group. For A.

baumannii, which is commonly MDR, empirical combination antibiotic therapy is currently

preferred than doripenem monotherapy in our ICU. Furthermore, the MIC90 for doripenem against

A. baumannii in the Asia-Pacific region was reported as ≥32 mg/L [332, 333]. For such an MIC,

even with a dose of 2000 mg 8-hourly as a 4-hour infusion, optimal exposure is only achieved for

patients with reduced CLCR in our cohort (e.g., <70 mL/min).

This study has several limitations. A relatively small number of critically ill patients (n = 12) with a

narrow bodyweight- and CLCR-range were included and thus, our model may not fully characterize

the PK of doripenem in all Malaysian ICU patients. A number of patients with conserved renal

function were recruited to examine altered dosing approaches in this cohort. Dosing

recommendations derived from our Monte Carlo simulations should not be extrapolated to other

patient populations such as the obese or those on extra-corporeal renal support. We also

acknowledge limitations with the Cockcroft-Gault formula in estimating renal function in this

cohort, with measured CLCR more appropriate in the ICU setting. Neither free (unbound) doripenem

concentrations nor drug concentration at the sites of infections (e.g., epithelial lining fluid

concentrations) were measured in this study. Total doripenem concentration was measured and

applied in the analysis with correction for protein binding. We believe that this approach is highly

acceptable for drugs with low protein-binding properties, such as doripenem (approximately 10%

protein bound) [99]. Although data on concomitant drugs were available, we did not evaluate the

PK of those drugs and their potential influence on doripenem exposure in critically ill patients.

2.2.6 Conclusions

Critically ill patients frequently manifest extreme physiological changes, which may alter antibiotic

PK and subsequently reduce effective drug exposure. Importantly, findings from this study further

show that the licensed “one-dose-fits-all” dosing strategy for doripenem is likely to be flawed in the

critically ill population. An alternative dosing approach such as the empirical use of a prolonged 4-

45

hour infusion may be considered to account for PK and illness-severity differences in this unique

patient population, particularly when MDR Gram-negative organisms are involved.

2.2.7 Acknowledgments

This project has received funding from the International Islamic University of Malaysia (IIUM)

Research Endowment Grant. Mohd H. Abdul-Aziz and Azrin N. Abd Rahman would like to

acknowledge the support of the Ministry of Education, Malaysia in the form of scholarship. Jason

A. Roberts is funded by a Career Development Fellowship from the National Health and Medical

Research Council of Australia (APP1048652).

46

2.3 Conclusion

This chapter describes how critically ill patients are markedly different from those in general ward

settings and demonstrates how these differences influence doripenem dosing requirements. The Vd

and CL of doripenem in this patient cohort were observed to be substantially different than those

usually described in healthy volunteers and non-critically ill patients. As current dosing

recommendations were mostly derived from these two populations, findings from this study further

emphasize that the licensed “one-dose-fits-all” dosing strategy for doripenem is likely to be flawed

in critically ill patients. The findings of presented in this chapter also provides additional PK/PD

data which supports alternative dosing approaches for doripenem in critically ill patients,

particularly when less-susceptible pathogens are involved.

47

Chapter 3: Continuous beta-lactam infusion in critically ill patients: a

structured review of published literatures

3.1 Synopsis

Mortality rates due to severe sepsis and septic shock in critically ill patients remain persistently high despite

recent therapeutic advances. Beta-lactam antibiotics are commonly used and are regarded as first-line

therapies around the world, particularly in the management of critically ill patients with severe sepsis.

However, dosing modifications for these antibiotics are frequently needed in critically ill patients to prevent

therapeutic failures due to significant pathophysiological perturbations in this patient population over time.

Beta-lactam antibiotics display time-dependent bacterial kill characteristics, whereby fT>MIC best describes

their antimicrobial properties. In terms of drug administration, CI administration of beta-lactam antibiotics,

as opposed to conventional IB dosing, is more likely to achieve this PK/PD end-point. Despite this

theoretical advantage, a global shift away from the traditional dosing method towards CI administration has

been difficult to be instigated as comparative studies in humans mostly fail to demonstrate a significant

difference in clinical outcomes between the two dosing approaches. However, comparisons between the two

dosing approaches were mostly performed in heterogeneous non-critically ill patient population and thus, the

question still remains whether there is any real benefit of administering beta-lactam antibiotics via CI dosing

in critically ill patients. Therefore, this chapter aims to critically analyse the available literature, by

comparing the PK/PD data and clinical outcomes associated with by CI and IB dosing, in order to establish

any potential benefits supporting either of the two dosing approaches for critically ill patients.

48

3.2 Manuscript entitled “Continuous infusion vs. bolus dosing: implications

for beta-lactam antibiotics”

The manuscript entitled “Continuous infusion vs. bolus dosing: implications for beta-lactam

antibiotics” has been accepted for publication in the Minerva Anestesiologica (2012; 78 (1): 94-

104).



Jason A. Roberts and Prof. Jeffrey Lipman. Literature review was performed by the PhD candidate,

Mohd-Hafiz Abdul-Aziz, under the guidance of Prof. Jason A. Roberts. The PhD candidate took the

leading role in manuscript preparation and all co-authors reviewed and contributed to the final draft

of the manuscript.





Permission has been granted by the publisher and copyright owner, Edizioni Minerva Medica, to

reproduce the manuscript in this Thesis.

49

CONTINUOUS INFUSION VS. BOLUS DOSING: IMPLICATIONS FOR BETA-LACTAM

ANTIBIOTICS

Authors

Mohd H. Abdul-Aziz (1), Christine E. Staatz (2), Carl M. J. Kirkpatrick (3), Jeffrey Lipman (4, 5),

Jason A. Roberts (4, 5, 6)

Affiliations

(1) School of Pharmacy, International Islamic University of Malaysia, Kuantan, Malaysia.

(2) School of Pharmacy, University of Queensland, Brisbane, Australia.

(3) Faculty of Pharmacy and Pharmaceutical Sciences, Monash University, Melbourne, Australia.

(4) Burns, Trauma and Critical Care Research Centre, University of Queensland, Brisbane,

Australia.

(5) Department of Intensive Care, Royal Brisbane and Women’s Hospital, Brisbane, Australia.

(6) Pharmacy Department, Royal Brisbane and Women’s Hospital, Brisbane, Australia.

Keywords: Beta-lactam antibiotic; clinical outcome; continuous infusion; bolus dosing;

pharmacodynamics; pharmacokinetics.

Address for correspondence

Prof. Jeffrey Lipman,

Burns, Trauma & Critical Care Research Centre,

Level 3 Ned Hanlon Building, Royal Brisbane and Women’s Hospital,

Butterfield St, Brisbane,

Queensland 4029 Australia.

Ph: +61736361852 Fax: +61736363542

50

3.2.1 Abstract

Beta-lactam antibiotics display time-dependant PD whereby constant antibiotic concentrations

rather than high peak concentrations are most likely to result in effective treatment of infections

caused by susceptible bacteria. CI administration has been suggested as an alternative strategy, to

conventional IB dosing, to optimize beta-lactam PK/PD properties. With increasing data emerging,

we elected to systematically investigate the published literature describing the comparative PK/PD

and clinical outcomes of beta-lactam antibiotics administered by CI or IB. We found that the studies

have been performed in various patient populations including critically ill, cancer and cystic fibrosis

patients. Available in vitro PK/PD data conclusively support the administration of beta-lactams via

CI for maximizing bacterial killing from consistent attainment of PD end-points. In addition,

clinical outcome data supports equivalence of CI and IB, even with the use of a lower dose with CI.

However, the present clinical data is limited with small sample sizes commonly associated with

insufficient power to detect advantages in favour of either dosing strategy. With abundant positive

pre-clinical data as well as document in vivo PK/PD advantages, large multicentre RCTs are needed

to describe whether CI administration of beta-lactams is truly more effective than IB dosing.

51

3.2.2 Introduction

The mortality rate due to severe sepsis and septic shock remains high despite recent therapeutic

advances. Source control of the pathogen along with early and appropriate antibiotic administration

remains the best strategy available to clinicians in the management of critically ill septic patients

[330, 357]. However, appropriate antibiotic administration is not straightforward as critically ill

patients may develop pathophysiological changes that alter the PK of the prescribed antibiotic [8,

64]. Indeed dosing that does not account for these pathophysiological changes may lead to

inadequate antibiotic concentrations and therapeutic failure. Therefore, different dosing approaches

may be required to ensure that antibiotic concentrations meet PK/PD targets likely to enable clinical

success.

Beta-lactam antibiotics are still regarded as key antibiotics in severe infections due to their spectrum

of antibacterial activity and overall tolerability. These antibiotics display time-dependent PD

whereby fT>MIC best describes their bacterial kill characteristics (5). Based on this property,

maximal beta-lactam activity is thought to be achieved by utilizing either smaller doses more

frequently than standard IB dosing or utilizing EI or CI.

The aim of this paper is to systematically review and critically analyse the published literature

comparing the PK and clinical outcomes of administering beta-lactams by IB and CI in various

patient populations. The review will address the question on which administration strategy most

consistently achieves PK/PD targets and results in improvement of clinical endpoints.

Data for this review were identified by incorporating PUBMED searches (1966 to February 2011)

and references from relevant papers. Search terms were “continuous infusion” or “intermittent

infusion”, “antibiotic” or “antibacterial” or “antimicrobial”, “beta-lactams” or “penicillins” or

“cephalosporins” or “monobactams” or “carbapenems” and “pharmacokinetics” or

“pharmacodynamics”. Relevant primary research papers comparing the administration of beta-

lactams by IB and CI were identified and evaluated. All relevant English original articles were

systematically evaluated. To emphasize new developments in this area, we have given particular

focus to the more recently published studies. Below, we discuss the published studies in terms of

PK and clinical outcomes and then outline the results that have been obtained in specific patient

populations.

52

3.2.3 The Pharmacodynamics of Beta-lactams

Beta-lactam antibiotics include the penicillins, cephalosporins, carbapenems and monobactams.

These antibiotics have slow bacterial kill characteristics which are almost exclusively dependent on

the serum free drug concentration exceeding the MIC of the pathogen [12]. Maximal beta-lactam

bacterial killing is achieved when the serum free drug concentration is maintained at 4-5 times the

MIC [152]. The PD of beta-lactams have been extensively reviewed by Turnidge previously [358].

One of the main areas of contention for the PD of beta-lactams relates to the comparative target

exposures required for CI and for IB. Mouton and den Hollander used an in vitro PK model that

was able to replicate plasma ceftazidime concentrations administered by IB or by CI [152]. In this

study, the authors found that maintaining a CI concentration near the MIC does not provide

bacterial killing advantages over IB. However, when concentrations are maintained at 4 x MIC, CI

is associated with significantly greater bacterial killing. In combination with other available PD

data, this data suggests that therapeutic targets for CI therapy should be a steady-state concentration

(Css) that is at least 4 x MIC. It follows, that comparative PK studies should be evaluating the

relative ability of IB to achieve a Cmin greater than the MIC of the likely pathogen (this is likely to

ensure 40-70% of the time that free (unbound) drug concentration remains four times above the

MIC during a dosing interval [fT>4xMIC]) and for CI, a Css greater than 4 x MIC.

Of particular importance, published PK/PD studies need to be interpreted in light of the new

susceptibility breakpoints that have been classified by the European Committee on Antimicrobial

Susceptibility Testing (EUCAST; available at: http://www.eucast.org/clinical_breakpoints) [359]

and Clinical and Laboratory Standards Institute (CLSI; available at http://www.clsi.org/) [360, 361].

Specifically, the recent EUCAST susceptibility breakpoint recommendations are lower than those

of CLSI, which may in turn influence clinicians’ view on the results from PK/PD studies. These

new data may mean that the present dosing approaches are more, or less likely to achieve PK/PD

targets.

3.2.4 Comparative Studies between Intermittent and Continuous Administration

3.2.4.1 Plasma Pharmacokinetics

Before describing the published data, it is important to note that the PK advantages reported by

studies comparing the Cmin from IB and Css from CI of beta-lactams are expected based on PK

principles. Statistically significant differences favouring CI would be seen as the Css will always be

http://www.eucast.org/clinical_breakpoints

http://www.clsi.org/

53

higher than Cmin from IB. This concept is described in Figure 3-1 which uses PK modelled data,

adapted from a previous study with flucloxacillin [102], to describe the inevitability of achieving a

higher Css from CI in critically ill patients. This limitation has also been discussed in a review article

by Roberts et al., identifying the deficient reporting approach in some PK studies resulting

disadvantages to IB [277]. The key comparison in the PK studies should be the achievement of the

PD end-points, 100% fT>MIC for IB and 100% fT>4xMIC for CI. We would advocate a PD target of

100% fT>MIC for IB as this is likely to result in a concentration 4 x MIC for 40-70% of the dosing

interval as required for the different classes of beta-lactams.

Figure 3-1: Comparative flucloxacillin concentration between continuous (CI) and

intermittent administration (IB) assuming similar pharmacokinetic properties in ICU

patients. The same daily dose for IB and CI was simulated from a previous population

pharmacokinetic study whereby 2 g 6 hourly for IB and 8 g over 24 hours was simulated for

CI

Legend:

Continuous infusion (dotted lines); intermittent bolus dosing (solid lines).

Studies comparing the plasma PK of IB and CI administration of beta-lactams have generally

shown that administration via CI maintains superior concentrations throughout a treatment period.

Table 3-1 compares the published data of plasma pharmacokinetic exposures for each

administration method.

54

Table 3-1: Comparison of respective plasma pharmacokinetic between continuous and intermittent administration of beta-lactams in critically ill or septic patients

Antibiotic n Design MIC

(mg/L)

Dosage Regimen AUCa

(mg/L*h)

Cmaxa

(mg/L)

Cmina

(mg/L)

Cssa

(mg/L)

%fT>MIC

(%)

CI IB CI IB IB IB CI CI IB

Piperacillinb

[85]

13 RCT

(critically ill septic)

- 12 g/24 hrs 4 g q6/8hrs 464 803 152

(90-275)

2

(2-8)

17

(11-24)

- -

Piperacillinb

[253]

7 Randomized crossover


- 4 g LD then 8 g/24 hrs 4 g q8hrs 210±120 391±183 228

(172-359)

4.8

(1-43)

22

(14-53)

- -

Piperacillin

[362]

52 RCT

(complicated intra-abdominal infections)

- 2 g LD then 12/24 hrs 3 g q6hrs - - 122±30 - 35±12 100 95

Piperacillinb

[173]

24 RCT

(severe infections)

- 2 g LD then 8 g/24 hrs 4 g q8hrs 936 - - - 39 - -

Meropenem

[253]


(critically ill with CRRT)

8 0.5 g LD then 2 g/24 hrs 1 g q12hrs 227

(182-283)

233

(202-254)

63

(51-85)

8

(5-18)

19

(13-25)

100 46

Meropenemb

[193]



- 2 g LD then 3 g/24 hrs 2 g q8hrs 118±13 194±21 110±7 9±1 12±5 - -

Meropenem

[86]

10 RCT


4 0.5 g LD then 3g/24 hrs 1.5 g LD then 1 g q8hrs 99c 97c 93

(74-119)

0

(0-2)

7d

(5-16)

100e 80e

Ceftazidime

[82]

18 RCT

(severe intra-abdominal infections)

8 1 g LD then 4.5 g/24 hrs 1.5 g q8hrs 1131

(505-2230)

1064

(505-1950)

89

(58-125)

19

(6-68)

47

(21-93)

67f 69f

Ceftazidime

[254]

30 RCT

(critically ill, trauma, VAP)

- 2 g LD then 60 mg/kg/24

hrs

2 g q8hrs - - 91±44 4±4 19±9 100 100g

Ceftazidimeb

[363]



P. aeruginosa

isolate

2 g LD then 3 g/24 hrs 2 g q8hrs 112±56 331±165 124±53 25±18 30±17 100 92

Ceftazidimeb

[364]


(Cystic fibrosis-chronic)

- 100 mg/kg over 23.5 hrs 200 mg/kg divided thrice

daily

- - 159±44 9±5 32±12 - -

Ceftazidime

[365]


(Cystic fibrosis-acute exacerbation)

- 60 mg/kg LD then 200

mg/kg over 23 hrs

200 mg/kg divided thrice

daily

- - 216±72 12±9 56±23 - -

Ceftazidimeb

[366]

14 (Cystic fibrosis-chronic) - 100 mg/kg over 24 hrs 200 mg/kg divided thrice

daily

- - - 10±12h 30±10h - -

Temocillin

[247]

13 RCT


16 2 g LD then 4 g/24 hrs 2 g q12hrs 1759±188 1856±282 147±12 28±5 73±3 100 51

Cefazolin

[168]

20 RCT

(peri-operative-CPB)

8 2 g LD then 3 g/18 hrs 2 g LD, 1 g after CPB, 1 g

at 9 hrs &15 hrs after 2nd

dose

1700±205 1551±310 184±20 15±10.3i 53±19i 90j 30j

Cefotaxime

[79]

15 RCT

(peri-operative-liver transplant)

4 1 g LD then 4 g/24 hrs 1 g q6hrs 53±23k 72±21k 43±13 2±2 18±5 100 60

Abbreviation: AUC, area under the concentration-time curve; CI, continuous infusion; Cmax, peak concentrations; Cmin, trough concentrations; ; CPB, cardiopulmonary bypass; CRRT, continuous renal replacement therapy; Css, steady-state concentrations; IB,

intermittent bolus; LD, loading dose; MIC, minimum inhibitory concentration; RCT, randomized controlled trial; VAP, ventilator-associated pneumonia; % fT>MIC, percentage of time (dosing interval) where free (unbound) antibiotic concentration remains

above MIC.

Legend:

aValues are described according to published results as mean (±SD) or median (range).

bLower CI dose used.

cDay 1 AUC0-8.

dDay 1 Cmin.

55

e% of patients achieving 40% fT>MIC.

f4 x MIC.

gAll patients achieved % fT>MIC of 100% except 1 who achieved 92%.

hDay 3.

iAverage concentration at 24 hours.

j% of patients achieving 90% fT>MIC.

kAUC0-8.

56

Below, we will specifically discuss the previously published PK studies comparing the two study

approaches in specific populations. The issues identified relating to different PK/PD targets are

relevant to some of the studies depicted below.

3.2.4.1.1 Critically ill

Critically ill patients have been the focus of many studies (Table 3-1) as they are postulated to be

likely to benefit most from the PK/PD advantages of CI [82, 85, 86, 173, 193, 247, 253, 254, 363,

367]. These patients commonly develop an increased Vd and ARC thus producing low drug

concentrations in the presence of standard dosing [357].

Roberts et al., reported a superior PK/PD profile for piperacillin in an RCT where CI was compared

to IB in 13 critically ill patients with sepsis [85]. Despite a 25% lower dose, the median Cmin on Day

2 of therapy was 16.6 versus 4.9 mg/L for CI and IB respectively (p = 0.007). Langgartner et al.,

observed higher median Css (18.6 mg/L) when meropenem was administered via CI compared to

trough concentrations (8.2 mg/L) provided by IB in 6 critically ill patients who also received CRRT

[253]. De Jongh et al., also reported significantly higher temocillin Css (73 mg/L) in CI compared to

IB (trough concentrations; 28 mg/L) [247]. The authors also added that CI of temocillin achieved a

plasma concentration that is 4 times the MIC of the least susceptible pathogens in the study. Other

studies have described PK/PD advantages in critically ill patients [79, 82, 86, 172, 173, 193, 253,

254, 362, 363].

3.2.4.1.2 Peri-operative non-infected patients

Several studies (Table 3-1) have sought to investigate the PK properties of CI of beta-lactams in

preventing infections after surgical procedures [79, 168, 368]. The majority of these studies support

the PK/PD superiority of CI compared to IB dosing. Adembri et al., described stable serum

cefazolin concentrations with low interpatient variability using CI for antibiotic prophylaxis in

cardiopulmonary bypass surgery [168].

3.2.4.1.3 Cystic fibrosis

Several studies (Table 3-1) have shown PK/PD advantages supporting the use of CI of ceftazidime

in cystic fibrosis patients [364-366, 369]. The idea of administering ceftazidime as CI was proposed

due to the drug’s rapid renal elimination whereby 65% urinary recovery within 2 hours of 50 mg/kg

ceftazidime bolus dose was reported in the sub-population [370]. Hubert et al., performed an RCT

57

to compare the PK properties of ceftazidime administered as either thrice-daily or 24-hour CI in 49

cystic fibrosis patients with acute exacerbation of chronic pulmonary P. aeruginosa infection [365].

The authors found superior concentration-time profile benefits which favoured CI of ceftazidime

whereby the mean Css was significantly higher compared to the Cmin of thrice-daily administration

(CI; 56.2 mg/L versus IB; 12.1 mg/L, p <0.05). Some of the Cmin values were reported to be very

low, even lower than the MIC of the offending pathogens whereas the Css remained constantly

above the MIC throughout CI administration. However, it is unknown if these concentrations were

indeed 4 x MIC to demonstrate maximal antibacterial activity. Riethmueller et al., found higher

mean Css (32 mg/L) of CI compared to Cmin (8.5 mg/L) of thrice-daily administration of ceftazidime

in 56 cystic fibrosis patients with chronic P. aeruginosa infection [364]. The authors described

superior target ceftazidime concentration achievement by CI despite using a lower ceftazidime dose

of 100 mg/kg/day compared to the conventional 200 mg/kg/day in three divided doses. Studies by

Rappaz et al., and Vinks et al., also reported similar findings with a lower ceftazidime dose of 100

mg/kg/day administered as continuous application [366, 371]. Each of the studies reported higher

average steady-state beta-lactams concentrations in CI administration compared to trough

concentrations of IB up to a factor of 4 which is theoretically likely to enable PK/PD superiority in

favour of CI.

3.2.4.1.4 Cancer patients

Comparative studies on CI and IB dosing of beta-lactams in cancer patients are lacking. Most of the

studies that are available have focused on the safety and efficacy of CI in cancer patients without the

inclusion of an IB regimen for comparison [255, 372, 373]. Studies have also supported the notion

of using CI administration in cancer patients based on the postulated superior PK/PD properties

compared to IB dosing as neutropenic patients may develop increased Vd and higher drug CL [255,

372, 373]. More prospective comparative studies are needed in to further describe the clinical

applicability of CI in this sub-population.

3.2.4.1.5 Paediatric population

Studies (Table 3-1) comparing the PK properties of CI and IB in paediatric population are lacking

[366, 372]. Robust prospective comparative studies are warranted in this specific patient group.

58

3.2.4.2 Tissue pharmacokinetics

Antibiotic-bacteria interactions usually occur at the tissue level (e.g., interstitial fluid) thus, any

administration method that could enhance antibiotic penetration into tissues is vital in predicting

response. Significant antibiotic concentration is needed at the target site but most antibiotics are

unevenly partitioned and serum concentration does not always reflect tissue concentrations. Table

3-2 describes the penetration of beta-lactam antibiotics into various tissues when administered via

CI or IB.

Table 3-2: Penetration of beta-lactams into various tissues when administered as continuous or

intermittent administration

Antibiotic Population n Measurement site % Tissue penetration

CI IB

Piperacillina

[277]

Critically ill

septic patients

13 Subcutaneous tissue

(AUCtissue/AUCserum)

21% 20%

Piperacillin/tazobactam

[211]

Critically ill

septic patients

40 ELF 40-50% 57%


[80]

Critically ill

septic patients

10 ELF - 57%

Meropenem

[86]

Critically ill

septic patients

10 Subcutaneous tissue

(AUCtissue/AUCserum)

89% 74%

Cefotaxime

[79]

Peri-operative

non-infected

patients

15 Bile

(AUCbile/AUCserum)

90% 80%

Ceftazidime

[82]

Peri-operative

infected

patients

18 Peritoneal exudate

(AUCexudate/AUCserum)

56% 35%

Abbreviation: AUC, area under the concentration-time curve; CI, continuous infusion; ELF,

epithelial lining fluid; IB, intermittent bolus.

Legend:

aLower CI dose used.

Roberts et al., found similar plasma and tissue PK of piperacillin when administered by IB or CI

[85]. However, the RCT also described higher PD targets attainment by CI despite utilizing 25%

smaller dose compared to IB. The authors also added that the clinical significance of this difference

is only important in pathogens with high MICs (2 or 4 mg/L). In a prospective comparative study,

Boselli et al., sought to investigate plasma and alveolar PK of piperacillin/tazobactam administered

via CI in critically ill patients with VAP and various degrees of renal impairment [211]. The authors

59

reported large variability in the drug’s concentrations with an alveolar percentage penetration of 40-

50% and 65-85% for piperacillin and tazobactam respectively. It is interesting to note that in

patients with no/mild renal impairment, a CI daily dose of piperacillin/tazobactam 16/2 g achieved

the alveolar target concentration which was not observed with 12/1.5 g per day. In this study, it was

postulated that the latter dosing regimen in patients with no/mild renal impairment might produce

inadequate antibiotic concentration in epithelial lining fluid (ELF) in patients with VAP caused by

pathogens with high MICs.

In one RCT involving 10 critically ill septic patients, Roberts et al., reported that CI of meropenem

maintains higher median Cmin compared to IB, in both plasma (CI; 7 mg/L versus IB; 0 mg/L, p =

0.02) and subcutaneous tissue (CI; 4 mg/L versus IB; 0 mg/L, p = 0.02) [86]. The authors also

concluded that CI of meropenem achieves superior cumulative fraction of response (CFR) against

less-susceptible microorganisms (P. aeruginosa and Acinetobacter spp.) in patients without renal

impairment.

3.2.4.3 Clinical outcomes

Although the PK/PD data of beta-lactams support the use of CI, there is little data to confirm that

this results in improved clinical outcomes. The published data on comparative clinical outcomes is

scarce and insufficient to support a global practice change from conventional IB to CI. Lack of

significance in the published results are likely to be due to the use of study designs that were not

sufficient to explore the effect of both dosing approaches on clinical outcomes as well as the

consistent, small sample sizes that resulted in insufficient power. Further to this, a single therapeutic

intervention in a critically ill setting rarely influences mortality and clinical cure in the setting of a

study [264].

Another possible contributor to a lack of clinical differences being measured between the methods

of administration is that treatment of infections caused by highly susceptible pathogens will always

result in similar outcomes for IB and CI. This is because even a low Cmin achieved during IB is still

likely to exceed the MIC for a sufficient period of each dosing interval. If studies include many

patients with highly susceptible pathogens, then the sample size required to show differences

between the respective dosing methods increases dramatically. For less susceptible organisms, the

likelihood of achieving target concentrations is less likely may risk therapeutic failure.

60

Below, we discuss the published clinical outcome data that have been reported in specific patient

populations.

3.2.4.3.1 Mortality

Several studies, mostly in critically ill patients, have sought to evaluate the mortality outcome

produced by beta-lactams administered via CI or IB (Table 5-3) [151, 172, 243, 248, 256, 274,

298]. It is important to note that the number of RCTs in this area is limited and these trials described

no significant mortality benefits achieved by either administration methods. The problem lies in the

fact that many studies are underpowered and the mortality is often studied as a secondary end-point.

A retrospective cohort study by Lorente et al., revealed similar mortality rate in 83 VAP patients

receiving either IB or CI of piperacillin/tazobactam (IB; 30.5% versus CI; 21.6%, p = 0.46) [274].

Another non-randomized study that’s worth a mention is by Lodise et al., where they reported a

significant lower 14-day mortality rate in patients with an APACHE II score ≥17 favouring EI

compared to IB of piperacillin/tazobactam in critically ill patients infected with P. aeruginosa (IB;

31.6% versus CI; 12.2%, p = 0.04) [298]. Intention-to-treat (ITT) analysis of an RCT by Roberts et

al., found no significant difference in the mortality rate of 57 ICU patients (CI; 10% versus IB; 0%,

p = 0.25) [243]. A recent systematic review of 14 randomized controlled trials performed by

Roberts et al., reported that CI of beta-lactams were not associated with a significant improvement

in mortality rate (odds ratio [OR]: 1.00, 95% confidence interval: 0.48-2.06, p = 1.00, I2 = 14.8%)

[217].

Hughes et al., compared 30-day mortality rate in patients receiving CI or IB of oxacillin for the

treatment of infective endocarditis caused by Methicillin-susceptible Staphylococcus aureus

(MSSA) [374]. The two groups were similar with respect to mortality rate (CI; 8% versus IB; 10%,

p = 0.7) whether synergistic gentamicin (11%) was or not added (5%) into the studied regimen (p =

0.2).

3.2.4.3.2 Clinical cure

Lorente et al., also compared the clinical cure rate in 83 VAP patients receiving either CI or IB of

piperacillin/tazobactam [274]. CI was associated with greater clinical cure rate (CI; 89.2% versus

IB; 56.5%, p = 0.001) and regression analysis further showed higher clinical cure of VAP by CI

when the offending pathogen had a MIC of 8 mg/L or 16 mg/L. A priori analysis by Roberts et al.,

found significant advantage favouring CI of ceftriaxone compared to IB administration in critically

ill septic patients receiving at least 4 days of therapy [243]. The authors also reported that low

61

APACHE II score was predictive of clinical cure. However, the systematic review by Roberts et al.,

found that the use of CI of a beta-lactam antibiotic was not associated with an improvement with

clinical cure rate (OR: 1.04, 95% confidence interval: 0.74-1.46, p = 0.83, I2 = 0%) [217]. Again,

the number of RCTs (Table 2-3) investigating this outcome is limited and most of them were

underpowered [172, 243, 255-257, 266, 274, 375].

The clinical utility of CI and IB in cystic fibrosis have been compared in several studies [364-366].

These studies reported similar clinical outcomes. These studies have also compared patient

improvements in pulmonary, inflammatory and nutritional parameters in both methods after

antibiotic administration. However, these improvements were short-lived and patients frequently

returned to pre-treatment values after cessation of therapy.

Riethmueller et al., compared anti-infectious properties of CI and thrice-daily administration of

ceftazidime in 56 cystic fibrosis patients in a randomized crossover study [364]. The authors found

no significant difference between the two methods in terms of decrease in leukocyte counts,

clinical, lung function and inflammatory parameters. Another randomized crossover study by

Rappaz et al., had similar findings where CI of ceftazidime produced better pulmonary,

inflammatory and nutritional improvements compared to IB [366]. However, the only significant

improvement was in pre-albumin concentration. Hubert et al. reported similar improvements in

forced expiratory volume in 1 second (FEV1) values between the two administration methods but

the benefit of CI was seen in patients with resistant P. aeruginosa isolates (p <0.05) [365]. The

interval between the next antibiotic administration was longer in CI compared to short infusion of

ceftazidime in cystic fibrosis patients (p = 0.04).

Van Zanten et al., reported similar clinical success rates in patients with acute exacerbations of

COPD receiving either CI or thrice-daily administration of cefotaxime [257]. Clinical cure was

achieved in 37/40 (93%) and 40/43 (93%) patients in the CI and IB dosing group respectively (p =

0.93). Bodey et al., randomized cancer patients with febrile neutropenia to receive either CI or IB of

cefamandole with carbenicillin [255]. Although no difference in clinical outcome was reported, a

sub-analysis result revealed that CI administration in comparison to IB produced clinical benefits in

patients with severe persistent neutropenia (CI; 65% versus IB; 21%, p = 0.03).

62

3.2.4.3.3 Severity of Illness

The rate of resolution of infection as described by improvements in the level of severity of illness in

critically ill patients has been used as a comparative index in some studies. In a study of 40

critically ill septic patients by Rafati et al., reduction in APACHE II scores was faster in a CI

compared to an IB group [248]. Significant difference in reduction of score was reported on Days 2,

3 and 4 of treatment.

3.2.4.3.4 Fever resolution/white blood cell normalization

Most studies (Table 3-3) that have investigated fever resolution or WCC normalization between

patients receiving CI or IB of beta-lactam antibiotics have found similar results [248, 254, 266, 364,

374]. However, an RCT by Nicolau et al., reported shorter defervescence time with CI compared to

IB of ceftazidime in 35 critically ill septic patients (CI; 3.1±2.1 days versus IB; 5.2±2.3 days, p =

0.015) [266]. Hughes et al., reported similar defervescence time in 107 patients with infective

endocarditis receiving either CI or IB dosing of oxacillin (CI; 3 days versus IB; 3 days, p = 0.8)

[374]. However, it is interesting to note that defervescence time was significantly different when

synergistic gentamicin was added, favouring the group without gentamicin addition.

Riethmueller et al., found a decrease in WCC favouring CI of ceftazidime in cystic fibrosis patients

[364]. However, the differences obtained in the randomized crossover study were insignificant

when compared to IB (CI; -2216 versus IB; 2209, p = 0.98).

3.2.4.3.5 Mechanical ventilation

The duration of mechanical ventilation has been compared in several studies (Table 3-3), mostly in

critically ill septic population but without significant differences favouring neither IB nor CI

method [172, 243, 254, 274, 375]. Roberts et al., postulated that as the duration of mechanical

ventilation is quite long, other confounding factors may influence the ventilation time in critically

ill patients [264].

3.2.4.3.6 Length of ICU/hospital stay

To date, no significant difference has been reported in length of hospital [243, 254, 298, 374, 375]

or ICU stay [172, 243, 254, 266, 274, 375] between patients receiving CI or IB of beta-lactam

antibiotics (Table 3-3). Studies are often underpowered to detect any significant difference and the

63

studied outcome is usually confounded by several factors other than the intervention given [264].

Whilst the data that describes the effect of CI on length of stay, data from studies which examined

the use of EI are worthy of noting. Among them is a retrospective cohort study by Lodise et al., who

reported a significant shorter hospital stay favouring EI of piperacillin/tazobactam compared to IB

in critically ill patients with P. aeruginosa infections (EI; 21 days versus IB; 38 days, p = 0.02)

[298].

3.2.4.3.7 Adverse events

Several studies (Table 3-3) have compared adverse events from CI and bolus administration of beta-

lactams, although no significant differences are evident [193, 256, 363-365, 375]. Interestingly,

some studies have reported no adverse events [193, 363, 364] while others have made multiple

identifications [256, 365, 375]. Hubert et al., reported 124 adverse events in a randomized crossover

study comparing the safety and efficacy of the two antibiotic protocols in a cystic fibrosis

population [365]. Fifty-six and 68 adverse events were reported during CI and IB respectively in the

study. However, only 2 were considered as severe (one in CI and one in IB) and the majority of the

adverse events were gastrointestinal related.

3.2.4.4 Other considerations

3.2.4.4.1 Stability Issues

Increasing the % fT>MIC for beta-lactams has been associated with increased therapeutic efficacy

and delaying the emergence of resistance and these benefits can be achieved with CI method.

However, carbapenems such as meropenem may be unsuitable for administration via CI due to

stability issues [284]. Meropenem is only stable for 8-12 hours at room temperature thus casting

doubts on any potential benefit of continuous delivery. This is still an important issue in tropical

countries where meropenem concentrations decreased by 4% and 12% when stored at room

temperature for 3 and 8 hours respectively [376] although 24-hour stability can be maintained if

meropenem’s temperature is kept below 4°C [369]. In tropical countries, EI (3-hour infusion) may

be a useful alternative to CI as it is still likely to produce superior PK/PD end-points compared to

IB dosing [376].

64

Table 3-3: Clinical outcome data for patients receiving bolus or continuous infusion/extended-dosing of beta-lactam antibiotics

Drug Population Study Clinical Outcome

Measure

CI IB Result

Cefepime

[172]

Critically ill, Gram-negative

infection

(n = 50)

RCT Mortality 12% 13% NS

Clinical cure 85% 67% NS

Duration of MV 24 ± 13 days 25.3 ± 10 days NS

LOS ICU 34 ± 17 days 40 ± 15 days NS

Ceftazidime

[254]

Trauma patients, NP

(n = 35)

RCT Duration of MV 22.9 ± 19.9 days 13.3 ± 6.1 days NS

LOS Hospital 41.7 ± 30.5 days 28.7 ± 15.9 days NS

LOS ICU 26.8 ± 20.1 days 15.5 ± 5.9 days NS

Duration of leucocytosis 7.8 ± 7.3 days 11.3 ± 4.7 days NS

Duration of pyrexia 7.9 ± 4.4 days 4.3 ± 4.7 days NS

Meropenem

[193]

Severe infection

(n = 15)

Randomized,

crossover

Adverse events None None NS

Ceftazidime

[363]

Critically ill, Gram-negative

infections

(n = 12)

Randomized,

crossover


Ceftazidime

[364]

Cystic fibrosis

(n = 56)

Randomized,

crossover

Decrease in WCC -2216 ± 2689 -2209 ± 3710 NS


Ceftazidime

[365]

Cystic fibrosis

(n = 49)

Randomized,

crossover

Change in FEV1 +7.6% +5.5% NS

Adverse events 1 severe event 1 severe event NS

Ceftazidime

[366]

Cystic fibrosis

(n = 14)

Randomized,

crossover

Pre-albumin

improvement

+0.11 +0.08 p =0.015

Cefamandole

[255]

Malignant disease with neutropenia

(n = 164)

RCT Clinical cure 64.8% 56.5% NS

Ceftriaxone Sepsis RCT Mortality 10% 0% NS

65

[243] (n = 57) Duration of MV 4.3 ± 4.5 days 3.4 ± 4.1 days NS

Clinical cure (a priori) 52% 20% p <0.04

LOS Hospital 42 ± 6.9 days 24 ± 2.1 days NS


Piperacillin

[248]

Critically ill patients, septicaemia

(n = 40)

RCT Mortality 30% 25% NS

Decrease in illness

severity

CI>IBa

Duration of pyrexia 2.4 ± 1.5 days 1.7 ± 0.7 days NS

WBC normalization 75% 83% NS

Pip-Tazo

[256]

Intra-abdominal infections

(n = 258)

RCT Mortality 0.76% 2.6% NS

Clinical cure 86.4% 88.4% NS

Adverse events 89.2% 87.1% NS

Ceftazidime

[151]

Septicaemic melioidosis

(n = 21)

RCT Mortality 20% 36.4% NS

Pip-Tazo

[274]

VAP, Gram-negative bacilli

(n = 83)

Retrospective,

cohort

Clinical cure 89.2% 56.5% p = 0.001

Mortality 21.6% 30.4% NS

Duration of MV 18.0 ± 10.2 days 21.7 ± 18.1 days NS


Pip-Tazo

[298]

P. aeruginosa, critically ill

(n = 194)

Retrospective,

cohort

Mortality 12.2% (EI) 31.6% p = 0.04

LOS Hospital 21 days (EI) 38 days p = 0.02

Oxacillin

[374]

Infective endocarditis

(n = 107)

Retrospective,

cohort

Mortality 8% 10% NS

LOS Hospital 20 days 25 days NS

Time to defervescence 3 days 3 days NS

Ceftazidime

[266]

NP, critically ill

(n = 35)

RCT Clinical cure 41% 33% NS

Duration of MV 7.9 ± 4.0 days 8.3 ± 4.3 days NS


66

Time to defervescence 3.1 ± 2.1 days 5.2 ± 2.3 days p = 0.015

WBC normalization 7.3 ± 3.0 x 109/l 5.5 ± 4.2 x 109/l NS

Ceftazidime

[375]

NP, critically ill

(n = 35)

RCT Clinical cure 41% 33% NS

LOS 11.8 ± 6.3 days 15.3 ± 9.6 days NS

Adverse events 9 13 NS

Cefotaxime

[257]

COPD

(n = 83)

RCT Clinical cure 93%

93% NS

Abbreviation: CI, continuous infusion; COPD, chronic obstructive pulmonary disorder; EI, extended-infusion; IB, intermittent bolus; ICU, intensive

care unit; LOS, length of stay; MV, mechanical ventilation; NP, nosocomial pneumonia; NS, non-significant; Pip-Tazo, piperacillin/tazobactam;

RCT, randomized controlled trial; VAP, ventilator-associated pneumonia; WCC, white cell counts.

Legend:

Significant difference in APACHE II scores on Days 2, 3 and 4.

67

3.2.5 Conclusions

Based on the data presented in this chapter, CI of beta-lactams may be meritorious. All of the

present pre-clinical and PK/PD simulation data supports CI. The available clinical data suggests that

CI and IB are associated with similar outcomes, even with the use of lower daily doses in CI. To

date, no data has conclusively shown any superiority of CI in terms of clinical outcomes, although

this is largely because existing studies were underpowered and unable to detect any significant

difference between the two approaches. Similarly, no data has ever demonstrated inferiority of CI

compared with IB. The available data in this chapter supports the undertaking of large scale

prospective clinical outcome studies, particularly in critically ill or immunocompromised patients to

confirm if these apparent advantages, do indeed translate into clinical superiority of CI.

68

3.3 Conclusion

Based on the published literatures that were presented in this chapter, it can be deduced that CI

administration of beta-lactam antibiotics will not be meritorious to all critically ill patients but may

potentially be advantageous to specific subset of patients with severe infections. Although all of the

present in vitro and PK/PD data supports CI administration, the current evidence also suggest

neither superiority nor inferiority of the approach compared to IB administration in terms of clinical

outcomes. Thus, the available data supports the undertaking of large-scale prospective clinical

outcome studies, particularly in patients with severe infections to confirm if these compelling

PK/PD advantages, do translate into clinical superiority favouring CI administration.

69

Chapter 4: Prolonged beta-lactam infusion in critically ill patients: a post

hoc analysis on a large dataset of critically ill patients

4.1 Synopsis

Sepsis remains one of the major problems for patients in the ICU. Given the intrinsic relationship

between infection and sepsis, optimizing antibiotic therapy has been suggested as one of the

approaches by which clinical outcomes in critically ill patients can be improved. However, optimal

antibiotic administration is not straightforward as critically ill patients may develop extreme PK

derangements that alter the exposure of the prescribed antibiotic. It is highly likely that

conventional antibiotic dosing does not account for these PK derangements and this may

consequently lead to therapeutic failure. Aiming to improve antibiotic treatment in the ICU, the

DALI study, a large multinational, PK point prevalence study, was undertaken to describe whether

conventional dosing of beta-lactam antibiotics attains drug concentrations associated with

therapeutic benefits in critically ill patients. The DALI study concluded that different dosing

approaches are required in critically ill patients as compared to non-critically ill patients, to ensure

optimal antibiotic exposures are achieved that can increase the opportunity for clinical success.

However, this large dataset of critically ill patients were not specifically analysed to investigate the

potential benefits of altered beta-lactam dosing in such patient population. Therefore, using the

database of the DALI study, this chapter aims to compare the PK/PD target attainment and clinical

outcomes between PI (i.e., CI and EI) and IB dosing of beta-lactam antibiotics in a large cohort of

critically ill patients. Additionally, the patient sub-groups who are most likely to benefit from

altered dosing approaches were also explored in this post hoc analysis.

70

4.2 Manuscript entitled “Is prolonged infusion of piperacillin/tazobactam and

meropenem in critically ill patients associated with improved

pharmacokinetic/pharmacodynamic and patient outcomes? An observation

from the Defining Antibiotic Levels in Intensive care unit patients (DALI)

cohort”

The manuscript entitled “Is prolonged infusion of piperacillin/tazobactam and meropenem in

critically ill patients associated with improved pharmacokinetic/pharmacodynamic and patient


(DALI) cohort” has been accepted for publication in the Journal of Antimicrobial Chemotherapy

(2016; 71(1): 196-207).


design was performed by Prof. Jason A. Roberts and Prof. Jeffrey Lipman. Literature review was

performed by the PhD candidate, Mohd-Hafiz Abdul-Aziz, under the guidance of Prof. Jason A.

Roberts, Prof. Jan J. De Waele and Prof. Jordi Rello. Data collection was performed by Dr. Murat

Akova, Prof. Matteo Bassetti, Prof. Jan J. De Waele, Dr. George Dimopoulos, Dr. Kirsi-Maija

Kaukonen, Dr. Despoina Koulenti, Prof. Claude Martin, Prof. Philippe Montravers, Prof. Jordi

Rello, Prof. Andrew Rhodes and Therese Starr. Sample bioanalysis was performed by the PhD

candidate, Mohd-Hafiz Abdul-Aziz, under the guidance of Dr. Steven C. Wallis. Data analysis was


Roberts and Dr. Joel M. Dulhunty. The PhD candidate took the leading role in manuscript

preparation and all co-authors reviewed and contributed to the final draft of the manuscript.





Permission has been granted by the publisher and copyright owner, Oxford University Press

(License no: 3886910071822), to reproduce the manuscript in this Thesis.

71

Is prolonged infusion of piperacillin/tazobactam and meropenem in critically ill patients

associated with improved pharmacokinetic/pharmacodynamic and patient outcomes? An

observation from the Defining Antibiotic Levels in Intensive care unit patients (DALI) cohort

Authors

Mohd H. Abdul-Aziz (1), Jeffrey Lipman (1, 2), Murat Akova (3), Matteo Bassetti (4), Jan J. De

Waele (5), George Dimopoulos (6), Joel Dulhunty (1, 2), Kirsi-Maija Kaukonen (7), Despoina

Koulenti (1, 6), Claude Martin (8, 9), Philippe Montravers (10), Jordi Rello (11), Andrew Rhodes

(12), Therese Starr (2), Steven C. Wallis (1), Jason A. Roberts (1, 2), DALI Study Authors†

Affiliations

(1) Burns Trauma and Critical Care Research Centre, The University of Queensland, Brisbane,

Australia.

(2) Royal Brisbane and Women’s Hospital, Brisbane, Australia.

(3) Hacettepe University, School of Medicine, Ankara, Turkey.

(4) Azienda Ospedaliera Universitaria Santa Maria della Misericordia, Udine, Italy.

(5) Ghent University Hospital, Ghent, Belgium.

(6) Attikon University Hospital, Athens, Greece.

(7) Helsinki University Central Hospital, Helsinki, Finland.

(8) Hospital Nord, Marseille, France.

(9) AzuRea Group, Paris, France.

(10) Centre Hospitalier Universitaire Bichat-Claude Bernard, AP-HP, Université Paris VII, Paris,

France.

(11) CIBERES, Vall d'Hebron Institut of Research, Universitat Autonoma de Barcelona, Barcelona,

Spain.

(12) St. George’s Healthcare NHS Trust and St. George’s University of London, London, England.

†All members of the DALI Study group are listed in the Acknowledgements section.

Running title: prolonged infusion vs. intermittent bolus dosing.

Keywords: antibiotic; beta-lactam; continuous infusion; extended infusion; bolus dosing;

pharmacokinetics, pharmacodynamics.

72

Address for correspondence:

Prof. Jason A. Roberts,

Burns Trauma & Critical Care Research Centre, The University of Queensland,

Level 3 Ned Hanlon Building, Royal Brisbane and Women’s Hospital,

Butterfield St, Brisbane, Queensland, Australia 4029

[email protected]


73

4.2.1 Abstract

4.2.1.1 Objectives

We utilized the database of the DALI study to statistically compare the PK/PD and clinical

outcomes between PI and IB dosing of piperacillin/tazobactam and meropenem in critically ill

patients using inclusion criteria similar to those used in previous prospective studies.

4.2.1.2 Methods

This was a post-hoc analysis of a prospective, multicentre PK point-prevalence study (DALI) which

recruited a large cohort of critically ill patients from 68 ICUs across 10 countries.

4.2.1.3 Results

Of the 211 patients receiving piperacillin/tazobactam and meropenem in the DALI study, 182 met

inclusion criteria. Overall, 89.0% (162/182) of patients achieved the most conservative target of

50% fT>MIC. Decreasing CLCR and the use of PI significantly increased the target attainment for

most PK/PD targets. In the sub-group of patients who had respiratory infection, patients receiving

beta-lactams via PI demonstrated significantly better 30-day survival when compared to IB patients

(86.2% [25/29] versus 56.7% [17/30]; p = 0.012). Additionally, in patients with a SOFA score of

≥9, administration by PI compared with IB dosing demonstrated significantly better clinical cure

(73.3% [11/15] versus 35.0% [7/20]; p = 0.035) and survival rates (73.3% [11/15] versus 25.0%

[5/20]; p = 0.025).

4.2.1.4 Conclusions

The analysis of this large dataset provides additional data of the niche benefits of administration of

piperacillin/tazobactam and meropenem by PI in critically ill patients, particularly for patients with

respiratory infections.

74

4.2.2 Introduction

Beta-lactam antibiotics are routinely prescribed for severe infections in the ICU. As time-dependent

antibiotics, the most important PK/PD index for its activity is fT>MIC [11]. IB dosing, the standard

method of beta-lactam administration, commonly produces sub-optimal drug concentrations in

critically ill patients with conserved renal function [86, 165, 169]. Such patients generally exhibit

extreme physiological derangements which may alter the beta-lactam PK and consequently, reduce

its exposure [6, 7]. Numerous PK/PD simulation studies suggest that optimal beta-lactam exposures

are readily obtained via CI or an extended 2 to 4-hour infusion (i.e., EI) [86, 165, 169, 187]. CI and

EI are jointly referred to as PI, with either approach considered to be potentially advantageous

compared to traditional IB administration.

Owing to persisting poor sepsis-related clinical outcomes in the ICU, there has been growing

concerns that conventional antibiotic dosing in critically ill patients is sub-optimal. If this notion is

true, global antibiotic prescribing practices may need to change accordingly. Aiming to improve

antibiotic treatment in the ICU, the DALI study [213], a large multinational, PK point prevalence

study, was undertaken to describe whether conventional dosing of beta-lactam antibiotics attains

drug concentrations associated with therapeutic benefits in critically ill patients. The implications of

the study are profound; 16% of the patients did not achieve the most conservative PK/PD target and

these patients were 32% more likely to demonstrate negative clinical outcomes. Although these data

concluded that different dosing strategies are needed in the ICU, they were not discretely analysed

to ascertain the potential merits of altered beta-lactam infusion in critically ill patients. Of note, with

the exception of piperacillin/tazobactam and meropenem, the other six beta-lactam antibiotics

included in the DALI study were almost exclusively administered by IB dosing, which signifies its

“authority” over PI dosing in current prescribing practices.

Despite compelling pre-clinical and PK/PD data, clinical comparative trials have failed to

demonstrate the perceived clinical advantage of PI over IB dosing [13]. Furthermore, most meta-

analyses of the clinical trials are still indecisive over the notion of PI clinical superiority over IB

dosing [217, 239, 240, 267-271, 377]. There are currently four recent meta-analyses which report

significant improvement in clinical cure [239, 268, 269] and survival [239, 268, 270] favouring PI

administration. However, their findings should be interpreted with caution as these meta-analyses

have included a considerable number of retrospective and non-randomized studies in their pooled

analysis. Given the above uncertainty, we utilized the database of the DALI study with the primary

aim of distinguishing the relative ability of PI and IB dosing of piperacillin/tazobactam and

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meropenem to achieve specific PK/PD exposure targets in relation to the offending pathogens MIC

during antibiotic therapy. Secondary aims were to describe clinical response and 30-day survival

for both administration approaches and which patient sub-groups were most likely to benefit from

this intervention.

4.2.3 Materials and methods

4.2.3.1 Study design

This is a post-hoc analysis of the DALI study which the detailed study protocol has been described

elsewhere [213, 378]. Briefly, during a single dosing interval on the investigation day, each patient

had two blood samples drawn for the beta-lactams they were receiving (mid-dose and a trough

concentration). Various demographic, clinical and treatment-related variables were collected on the

day of investigation. CLCR was estimated using the Cockcroft-Gault formula [341].

Patients were included if they received either piperacillin/tazobactam or meropenem, which were

administered by PI (either CI or EI) or IB dosing. We followed the inclusion criteria used in

previous randomized clinical trials of this intervention [166, 242, 243], which meant that patients

who received any form of extracorporeal renal support were excluded as patients with reduced drug

clearances are less likely to benefit from altered administration approaches [211, 244, 245]. For

clinical outcome assessment, only patients who received antibiotic for treatment of infection, as

opposed to prophylaxis, were included.

The lead site was The University of Queensland, Australia (ethical approval no. 201100283).

4.2.3.2 Sample integrity and bioanalysis

Blood samples were processed and stored per protocol prior to shipment to the BTCCRC, The

University of Queensland, Australia, where they were assayed. The details concerning bioanalysis

have been described in detailed elsewhere [379].

4.2.3.3 Pharmacokinetic/pharmacodynamic and clinical outcome measures

The primary end-point, which was PK/PD target attainment, is described in detail in Table 4-1.

Briefly, to assess the relative dosing adequacy of PI and IB administration, the observed unbound

antibiotic concentrations were compared against the causative pathogens actual or “surrogate” MIC.

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The secondary end-points, clinical response and 30-day survival, were assessed using definitions

described in Table 4-1. Additionally, to investigate clinical differences between PI and IB dosing

within the sub-group of patients with the highest illness severity, as described by Lodise et al.,

[298], we performed a Classification and Regression Tree (CART) analysis to further stratify

patients based on SOFA score to identify the patients who were at the greatest risk for clinical

failure and 30-day mortality.

Table 4-1: Definitions used for pharmacokinetic/pharmacodynamic end-points and clinical

outcome variables

Primary PK/PD end-pointsa,b Definition

50% fT>MIC Free drug concentration maintained above the MIC of the

pathogen for at least 50% of dosing interval.

50% fT>4 x MIC Free drug concentration maintained above a concentration four-

times the MIC of the pathogen for at least 50% of dosing

interval.

100% fT>MIC Free drug concentration maintained above the MIC of the

pathogen throughout the dosing interval.

100% fT>4 x MIC Free drug concentration maintained above a concentration four-

times the MIC of the pathogen throughout the dosing interval.

Secondary endpoints Definition and description

Clinical response

Clinical cure Completion of treatment course without change or addition of

antibiotic therapy, and with no additional antibiotics

commenced with 48 hours of cessation.

Clinical failure Any clinical outcome other than clinical cure.

30-day survival Survival at Day 30 following entry to the study.

Abbreviation: PK/PD, pharmacokinetic/pharmacodynamic; MIC, minimum inhibitory

concentration.

Legend:

aThe PK/PD exposure targets have all been identified in clinical studies recruiting critically ill

patients in which achieving these targets would increase the probability of clinical efficacy.

bActual MIC values, provided by the local microbiology laboratory, were used when available.

Where a pathogen was isolated but MIC was unavailable, the “surrogate” MIC was defined by the

EUCAST MIC90 data. Where no pathogen was formally identified, the MIC breakpoints for P.

aeruginosa (16 mg/L for piperacillin/tazobactam and 2 mg/L for meropenem) were inferred as the

“surrogate” MIC, which reflects the least susceptible pathogen that could be encountered during

beta-lactam therapy.

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4.2.3.4 Statistical analysis

Data are presented as median values with interquartile range (IQR) for continuous variables and

number and percentage for categorical variables. A multivariate logistic regression model (manual

entry and stepwise, backward elimination) was constructed to identify significant predictors

associated with the primary and secondary end-points with OR and 95% confidence interval

reported. Biologically-plausible variables with a p-value of ≤0.15 on univariate analysis were

considered for model building. However, the administered beta-lactam and the method of

administration were forced into the regression models regardless of the univariate analysis results.

Goodness-of-fit was assessed by the Hosmer-Lemeshow statistic. A two-sided p-value of <0.05 was

considered statistically significant in all analyses. Statistical analysis was performed using IBM

SPSS statistic 22 (IBM Corporation, Armonk, New York).

4.2.4 Results

A total of 211 patients received either piperacillin/tazobactam or meropenem and were considered

for study inclusion. Twenty-nine patients were further excluded as they received extracorporeal

renal support during ICU stay. The patient inclusion and exclusion process is depicted in Figure 4-1

and the baseline characteristics for the 182 included patients are presented in Table 4-2. For clinical

outcome assessment, 37 patients who were only receiving antibiotic prophylaxis were further

excluded.

Of the 182 included patients, 110 (60.4%) received piperacillin/tazobactam. Additionally, 60.4%

(110/182) of patients also received concomitant antibiotic therapy as part of their treatment. The

most common administration method was IB where 63.2% (115/182) of the patients received beta-

lactams via this approach. Among the 67 PI patients, 23 (34.3%) and 44 (65.7%) were CI and EI

patients, respectively. Figure 4-2 illustrates the preferred method of dosing by participating country.

Although most countries favoured IB dosing, two countries, Belgium and France, had more than

half of the patients receiving the beta-lactams by PI dosing.

Of 182 patients who received beta-lactams, 70 (38.5%) were prescribed for either presumed or

confirmed respiratory infection. Of the patients treated for infection (n = 145), 114 (78.6%) had at

least one causative pathogen isolated with 40.4% (46/114) of them had actual MIC values for the

causative pathogens identified. The number of patients with actual MIC data were similar between

PI and IB treatment arms (37.5% [18/48] versus 42.4% [28/66], respectively; p = 0.769). The

distribution of the isolated pathogens was similar between the treatment arms and most of the

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isolates were Gram-negative bacteria (PI 79.2% [38/48] versus IB 80.3% [53/66]; p = 0.881). Of the

114 isolated pathogens, the most prevalent Gram-negative and -positive pathogens were P.

aeruginosa (24/91; 26.4%) and S. aureus (6/23; 26.1%), respectively.

Figure 4-1: Study flowchart demonstrating the number of patients who were included and

excluded in each stage of the planned analysis

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Table 4-2: Baseline demographics and characteristics

Characteristic All patients

(n = 182)

PI

(n = 67)

IB

(n = 115)

Significance p-

valuea,b

Age (years) 61 (47-74) 56 (47-75) 64 (48-74) 0.417

Male, n (%) 113 (62.1) 44 (65.7) 69 (60.0) 0.447

Weight (kg) 73 (65-84) 73 (64-88) 74 (65-80) 0.646

APACHE II 18 (13-25) 20 (13-26) 18 (14-24) 0.215

SOFA 5 (3-8) 5 (3-8) 5 (3-8) 0.797

Serum creatinine concentration (µmol/L) 71 (52-125) 64 (48-140) 73 (53-119) 0.726

Cockcroft-Gault creatinine clearance (mL/min) 85 (46-131) 95 (42-141) 82 (48-130) 0.510

Pre-ICU hospital stay (days) 2 (1-9) 1 (1-9) 2 (1-9) 0.260

Duration of antibiotic therapy (days) 9 (4-14) 8 (4-13) 9 (4-14) 0.371

Concomitant antibiotics usage, n (%) 110 (60.4) 39 (58.2) 71 (61.7) 0.733

Surgery within 24 hours of antibiotic sampling, n (%) 33 (18.1) 14 (20.9) 19 (16.5) 0.460

Organisms identified, n (%) 121 (66.5) 50 (74.6) 71 (61.7) 0.103

Polymicrobial infection, n (%) 29 (15.9) 11 (16.4) 18 (15.7) 0.577

Primary infection site, n (%)

Respiratory 70 (38.5) 33 (49.3) 37 (32.2) 0.041

Abdominal 50 (27.5) 16 (23.9) 34 (29.6) 0.593

Blood 23 (12.6) 6 (9.0) 17 (14.8) 0.664

Urinary 21 (11.5) 6 (9.0) 15 (13.0) 0.231

Central nervous system 8 (4.4) 4 (6.0) 4 (3.5) 0.639

Others 10 (5.5) 2 (3.0) 8 (7.0) 0.082

Abbreviation: APACHE, Acute Physiology and Chronic Health Evaluation; IB, intermittent bolus; PI, prolonged infusion; SOFA, Sequential Organ

Failure Assessment.

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*Data are presented as median (interquartile range) or number (percentage).

Legend:

aRepresents the p-value between prolonged infusion versus intermittent bolus dosing and values in bold indicate significant difference between the

two dosing groups (p <0.05).

bLinear variables were compared using Mann-Whitney U test as data were non-normally distributed as were indicated by Kolmogorov-Smirnov test.

Dichotomous variables were compared using Pearson chi-square test or Fisher’s exact test as appropriate.

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Figure 4-2: Method of piperacillin/tazobactam and meropenem administration according to

participating countries

Abbreviation: IB, intermittent bolus; PI, prolonged infusion.

4.2.4.1 Pharmacokinetic/pharmacodynamic and clinical outcome measures

Overall, 89.0% (162/182) of patients achieved the lower PK/PD target of 50% fT>MIC. For higher

thresholds such as 100% fT>MIC and 100% fT>4xMIC, 63.2% (115/182) and 27.5% (50/182) of

patients, respectively, achieved these PK/PD targets. Although PI patients generally demonstrated

numerically higher target attainment rates as opposed to IB patients across all PK/PD indices, a

statistically significant difference was only observed at 100% fT>MIC; 50% fT>MIC (PI 91.0% [61/67]

versus IB 87.8% [101/115]; p = 0.532; 50% fT>4xMIC (PI 62.7% [42/67] versus IB 49.6% [57/115]; p

= 0.106; 100% fT>MIC (PI 73.1% [49/67] versus IB 57.4% [66/115]; p = 0.045; and 100% fT>4xMIC

(PI 31.3% [21/67] versus IB 25.2% [29/115]; p = 0.357. When only patients with actual MIC data

were analysed, those who received beta-lactams via PI dosing also demonstrated numerically higher

target attainment rates, albeit not statistically significant, compared to IB patients across all PK/PD

indices.

The clinical cure and 30-day survival rate of patients who received antibiotics for treatment of

infection (n = 145) was 73.1% (106/145) and 73.1% (106/145), respectively. Table 4-3 presents the

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differences in patient characteristics between those who demonstrated positive and negative clinical

outcomes in this study. The clinical outcomes were mostly similar between PI and IB patients

receiving antibiotics for treatment of infection (Figures 4-3 and 4-4). However, in sub-group of

patients who had respiratory infection (n = 59), patients receiving beta-lactams via PI dosing

demonstrated significantly better 30-day survival when compared to IB patients (86.2% [25/29]

versus 56.7% [17/30], respectively; p = 0.012).

Patients who had a SOFA score ≥9 were identified by CART analysis to have the greatest risk for

clinical failure (clinical cure rates were 80.0% [88/110] in patients with a SOFA score <9 versus

51.4% [18/35] in patients with a SOFA score ≥9; p = 0.004) and 30-day mortality (mortality rates

were 18.2% [20/110] in patients with a SOFA score <9 versus 54.3% [19/35] in patients with a

SOFA score ≥9; p = 0.001). In patients with a SOFA score ≥9 (n = 35), patients receiving beta-

lactams via PI dosing demonstrated significantly higher clinical cure (PI 73.3% [11/15] versus IB

35.0% [7/20]; p = 0.035) and 30-day survival rates (PI 73.3% [11/15] versus IB 25.0% [5/20]; p =

0.025).

4.2.4.2 Outcome measures predictors

Based on the most parsimonious model, decreasing CLCR values significantly increased the target

attainment for all PK/PD targets; 50% fT>MIC (OR 0.97; 95% confidence interval 0.98-0.99; p =

0.007); 50% fT>4xMIC (OR 0.97; 95% confidence interval 0.98-0.99; p = 0.014); 100% fT>MIC (OR

0.97; 95% confidence interval 0.98-0.99; p <0.001); and 100% fT>4xMIC (OR 0.97; 95% confidence

interval 0.96-0.98; p <0.001). The use of PI dosing, as opposed to IB dosing, significantly increased

the PTA for 100% fT>MIC (OR 2.78; 95% confidence interval 1.24-6.24; p = 0.013).

The results of all multivariate logistic regression models for clinical cure and 30-day survival are

available in Table 4-4. Based on the most parsimonious logistic regression model, SOFA score (OR

0.89; 95% confidence interval 0.80-0.99; p = 0.029) and concomitant antibiotic use (OR 0.31; 95%

confidence interval 0.10-0.96; p = 0.043) were identified as significant factors associated with

clinical cure whilst only SOFA score (OR 0.82; 95% confidence interval 0.73-0.92; p = 0.001) was

identified as the factor associated with 30-day survival.

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Table 4-3: Differences in patient characteristics and treatment-related variables between those who demonstrated positive and negative

clinical outcome

Variable Clinical cure Significance

p-valuea,b

30-day survival Significance

p-valuea,b Yes

(n = 106)

No

(n = 39)

Alive

(n = 106)

Deceased

(n = 39)

Age (years) 65 (50-75) 64 (51-79) 0.297 59 (47-74) 65 (56-77) 0.048c

Male, n (%) 67 (63.2) 24 (61.5) 0.929 66 (62.3) 25 (64.1) 0.890

Weight (kg) 73 (63-86) 75 (65-81) 0.927 75 (65-88) 71 (60-76) 0.074c

APACHE II score 19 (15-25) 18 (15-24) 0.643 18 (14-25) 21 (16-24) 0.499

SOFA score 5 (2-7) 7 (4-9) 0.029c 4 (2-7) 7 (4-10) 0.001c

Serum creatinine (µmol/L) 65 (51-144) 87 (53-130) 0.457 64 (48-130) 92 (64-143) 0.101

Cockcroft-Gault CLCR (mL/min) 86 (41-130) 78 (39-131) 0.445 93 (45-147) 59 (36-93) 0.014c

Duration of treatment (days) 9 (5-13) 7 (4-10) 0.030c 10 (5-14) 8 (4-12) 0.217

Pre-ICU hospital stay (days) 2 (1-8) 6 (2-12) 0.005c 2 (1-9) 3 (1-12) 0.046c

Surgery within 24 hours, n (%) 12 (11.3) 6 (15.4) 0.420 14 (13.2) 4 (10.3) 1.000

Culture positive, n (%) 83 (78.3) 31 (79.5) 0.759 85 (80.2) 29 (74.4) 0.387

Gram-negative pathogen, n (%) 61 (73.5) 30 (96.8) 0.036c 64 (75.3) 27 (93.1) 0.039c

Polymicrobial infection, n (%) 16 (19.3) 7 (22.6) 0.536 20 (23.5) 7 (24.1) 0.824


Respiratory 40 (37.7) 19 (48.7) 0.303 42 (39.6) 17 (43.6) 0.591

Abdominal 30 (28.3) 12 (30.8) 0.695 31 (29.2) 11 (28.2) 0.639

Blood 14 (13.2) 5 (12.8) 1.000 13 (12.3) 6 (15.4) 0.542

Urinary 14 (13.2) 0 (0.0) 0.035 11 (10.4) 3 (7.7) 0.515

Central nervous system 4 (3.8) 1 (2.6) 1.000 4 (3.8) 1 (2.6) 1.000

Others 4 (3.8) 2 (5.1) 1.000 5 (4.7) 1 (2.6) 1.000

Beta-lactam antibiotics, n (%)

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Piperacillin 60 (56.6) 26 (66.7) 0.295c 62 (58.5) 24 (61.5) 0.787

Meropenem 46 (43.4) 13 (33.3) 44 (41.5) 15 (38.5)

Concomitant antibiotics, n (%) 58 (54.7) 32 (82.1) 0.020c 60 (56.6) 30 (76.9) 0.023c

Dosing method, n (%)

Prolonged infusion 44 (41.5) 14 (35.9) 0.641c 47 (44.3) 12 (30.8) 0.156c

Intermittent bolus 62 (58.5) 25 (64.1) 59 (55.7) 27 (69.2)

PK/PD ratiod

50% fT>MIC 7.1 (2.2-13.0) 3.5 (2.1-10.0) 0.097c 5.3 (1.9-11.7) 8.1 (2.9-15.0) 0.383

100% fT>MIC 2.2 (0.6-7.1) 1.7 (0.5-3.1) 0.280 1.7 (0.5-5.3) 3.2 (1.1-7.2) 0.060c

Abbreviation: APACHE, Acute Physiology and Chronic Health Evaluation; CLCR = creatinine clearance; ICU, intensive care unit; MIC, minimum

inhibitory concentration; PK/PD, pharmacokinetic/pharmacodynamic; SOFA, Sequential Organ Failure Assessment.

Legend:

aLinear variables were compared using Mann-Whitney U test as data were non-normally distributed as were indicated by Kolmogorov-Smirnov test.


bBold values indicate statistical significance (p <0.05).

cRepresents variable that was included in the multivariate logistic regression model.

dThe pharmacokinetic/pharmacodynamic (PK/PD) ratios observed at 50% and 100% of the dosing interval. These indices were defined as the ratio

between the unbound plasma concentration (either piperacillin/tazobactam or meropenem) at 50% or 100% of the dosing interval and the causative

pathogens MIC. Actual MIC values were used when available. Where MIC was unavailable or no pathogen was formally identified, “surrogate” MIC

values were assumed.

85

Figure 4-3: Clinical cure rates comparison between prolonged infusion and intermittent bolus

dosing for patients who received antibiotics for treatment of infections, stratified according to

sub-groups

Abbreviation: IB, intermittent bolus; n, number; PI, prolonged infusion; SOFA, Sequential Organ

Failure Assessment.

Legend:

An asterisk indicates significant difference between prolonged infusion versus intermittent bolus

dosing (p <0.05).

86

Figure 4-4: Comparison of 30-day survival between prolonged infusion and intermittent bolus

dosing for patients who received antibiotics for treatment of infections, stratified according to

sub-groups.

Abbreviation: IB, intermittent bolus; n, number; PI, prolonged infusion; SOFA, Sequential Organ

Failure Assessment.

Legend:

An asterisk indicates significant difference between prolonged infusion versus intermittent bolus

dosing (p <0.05).

87

Table 4-4: Factors predicting clinical cure and 30-day survival for all patients who received antibiotics for treatment of infections (n =145)

Variable All factors included in the model Final model

Odds ratio

(95% CI)

Significance

(p-value)

Odds ratio

(95% CI)

Significance

(p-value)

Factors predicting clinical cure

SOFA score (per 1-point increase) 0.90 (0.80-1.01) 0.071 0.89 (0.80-0.99) 0.029

Concomitant antibiotic therapya 0.24 (0.07-0.84) 0.025 0.31 (0.10-0.96) 0.043

Duration of antibiotic therapy (per 1-day increase) 1.08 (0.98-1.18) 0.115 - -

Gram-negative pathogenb 0.35 (0.06-1.87) 0.218 - -

50% fT>MICc (per 1-point increase) 1.02 (0.97-1.08) 0.405 - -

Piperacillind 0.84 (0.28-2.46) 0.746 - -

Prolonged infusione 0.86 (0.31-2.43) 0.782 - -

Pre-ICU hospital stay (per 1-day increase) 1.00 (0.97-1.03) 0.966 - -

Goodness-of-fit

Hosmer-Lemeshow test X2 = 6.00, df = 8 0.647 X2 = 8.41, df = 8 0.394

Factors predicting 30-day survival

SOFA score (per 1-point increase) 0.83 (0.73-0.96) 0.009 0.82 (0.73-0.92) 0.001

Concomitant antibiotic therapya 0.24 (0.05-1.04) 0.056 - -

Piperacillind 2.70 (0.86-8.49) 0.090 - -

Age (per 1-year increase) 0.96 (0.92-1.01) 0.099 - -

Weight (per 1-kg increase) 1.03 (0.99-1.07) 0.119 - -

Gram-negative pathogenb 0.32 (0.05-2.05) 0.228 - -

Pre-ICU hospital stay (per 1-day increase) 0.98 (0.95-1.01) 0.232 - -

Estimated Cockcroft-Gault CLCR (per mL/min) 1.00 (0.99-1.01) 0.675 - -

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Prolonged infusione 1.10 (0.33-3.67) 0.878 - -

100% fT>MICf (per 1-point increase) 1.00 (0.92-1.08) 0.960 - -

Goodness-of-fit


Abbreviation: CI, confidence interval; CLCR, creatinine clearance; df, degree of freedom; MIC, minimum inhibitory concentration; SOFA, Sequential

Organ Failure Assessment; X2 = chi-square.

*When available, actual MIC values were used.

**Dashes indicate there was no variable output in the model.

Legend:

aOdds ratio compares concomitant antibiotic therapy relative to antibiotic monotherapy.

bOdds ratio compares Gram-negative relative to Gram-positive pathogens.

cThe ratio between the unbound plasma concentration (either piperacillin or meropenem) at 50% of the dosing interval and the causative pathogens

MIC (actual or assumed values).

dOdds ratio compares piperacillin relative to meropenem.

eOdds ratio compares prolonged infusion relative to intermittent bolus dosing.

fThe ratio between the unbound plasma concentration (either piperacillin or meropenem) at 100% of the dosing interval and the causative pathogens

MIC (actual or assumed values).

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4.2.5 Discussion

Altered beta-lactam PK is widely reported among ICU patients, potentially leading to suboptimal

antibiotic exposures when “standard” beta-lactam dosing is applied in the cohort [6, 7, 56]. In this

study, the majority of patients achieved a lower PK/PD target of 50% fT>MIC and the attainment

rates were similarly high across the two administration methods and antibiotics. However, clinical

data from critically ill patients have suggested that such exposure should be regarded as the

minimum, with larger exposures associated with improved outcomes [5, 20, 21, 28]. A more

prudent target of 100% fT>MIC should be considered and this was not achieved by one-third of the

study patients. Nonetheless, the patients in this cohort were three-times more likely to achieve

100% fT>MIC when receiving beta-lactams via PI dosing (OR 2.78; 95% confidence interval 1.24-

6.24; p = 0.013). Although such an observation was anticipated, our current work remains unique

given that the data were derived from a broad range of ICU environment across 10 countries and the

strength of association was established and supported by multivariate regression analyses.

As the beta-lactams are predominantly cleared by the kidney, elevated renal function as observed in

ARC may likely lead to suboptimal PK/PD target attainment [117, 120, 121]. In our cohort,

increasing values of the estimated CLCR significantly reduced the probability of target attainment

for all PK/PD indices. Moreover, the observed relationship between CLCR and sub-optimal PK/PD

exposure was relatively strong in both univariate and multivariate analysis for all PK/PD indices.

The probability of attaining 100% fT>MIC would be reduced by 3% with every 1 mL/min increase in

the estimated CLCR (OR 0.97; 95% confidence interval 0.98-0.99; p <0.001). The median CLCR of

patients who did not attain 100% fT>MIC was 132 mL/min and only 28.2% (11/39) of those with a

CLCR ≥132 mL/min achieved the target. Such patients who are at-risk, usually in those with

apparently “normal” renal function, need to be identified early so that appropriate dose modification

can occur. Young trauma patients (<60 years), without significant organ dysfunction (SOFA ≤4)

[109, 353], were more likely to develop ARC and these factors were also evident in our patients

who manifested elevated CLCR; median age was 45 (IQR: 35-57) and median SOFA was 4 (IQR: 2-

7).

The significance of illness severity for clinical outcome is also highlighted in this study. In this

context, higher SOFA scores were independently associated with greater likelihood of developing

clinical failure and death at 30-days post antibiotic sampling. An increase in SOFA score by 1-point

reduced the probability of clinical cure and survival by 11.0% and 18.0%, respectively (Table 4-4).

Accordingly, we also observed that patients with a SOFA score ≥9 were more likely to demonstrate

90

negative clinical outcomes and when only these patients were tested, those receiving beta-lactams

via PI dosing demonstrated significantly better outcomes as opposed to IB dosing (Figures 4-3 and

4-4). Higher survival rates favouring PI dosing were also seen in sub-group of patients with

respiratory infection and our finding further substantiate similar claims of earlier studies which

suggested potential benefits of PI administration in severely-ill patients with pneumonia [274, 275,

290]. As inappropriate antibiotic treatment has been associated with reduced survival in patients

with severe pneumonia [20, 21, 31, 380], prompt antibiotic administration, with an optimal dosing

schedule, is therefore an essential intervention in this population. In this respect, the application of

PI dosing could be meritorious by enhancing beta-lactam penetration into the interstitial fluid of the

infected lung tissues [85, 141, 211], where the antibiotic-bacteria interactions occur [77].

Furthermore, optimal antibiotic dosing is crucial in this population as it may be directly linked with

patient outcomes [381, 382], whilst for other infection sites such as intra-abdominal and surgical-

site infections, effective source control and the role of the surgeons are probably more crucial in

predicting positive outcomes.

However, it is also important to mention that the sample size of patients in these two sub-groups

was relatively small compared to the clinically evaluable patients (<60 versus 145, respectively)

and thus, the observed statistical significance could have been the result of random chance, although

they do agree with previous published data [298]. Furthermore, due to the relatively small number

of patients in the two sub-groups, logistic regression analyses could not be performed and therefore,

the clinical benefits of PI were concluded based on unadjusted analyses which does not consider the

influence of potential confounders. Hence, it is important to highlight the median pre-ICU days for

PI patients in the two sub-groups were significantly shorter compared to IB patients (PI 2; IQR: 1-8

versus IB 7; IQR: 2-12; p = 0.039), and the large difference might skew the results in favour of PI.

Indeed, our clinical findings provide further evidence that PI dosing of beta-lactam antibiotics may

not be beneficial for all but rather a specific subset of critically ill patients with severe infections.

Interestingly, no sub-group has worse outcomes with PI dosing, suggesting that widespread use of

such an intervention is not likely to have an inferior effect compared with the current standard

practice. We believe that this study generates an interesting “therapeutic” signal, signifying

potential clinical superiority of PI dosing in patients with higher SOFA scores and in patients with

respiratory infections. Accordingly, future clinical studies should focus and test the hypotheses

specifically in these patient groups. As what has been demonstrated by a recent RCT, Dulhunty et

al., [166] showed that CI demonstrated better PK/PD and clinical outcomes when compared to IB

dosing and these findings may stem from the strategic approach of only recruiting patients with a

higher acuity of illness and in patients not receiving RRT.

91

In this study, concomitant antibiotic therapy also reduced the probability of clinical cure by 69.0%

(Table 4-4). Although the reasons were unclear, we hypothesize that the more severely-ill the

patient was, the more likely for the patient to receive multiple antibiotics in an attempt to “reverse”

the impending poor prognosis associated with such patients. Our notion was corroborated by the

higher median SOFA score observed in patients who received concomitant antibiotics compared to

those who did not (6; IQR: 3-9 versus 4; IQR: 1-7, respectively; p = 0.048). Whilst data on

concomitant antibiotics were available, we did not specifically evaluate their duration of therapy

and also assess the PK/PD of those antibiotics, all of which could have confounded the findings in

this study.

This study has several limitations we would like to declare. It is imperative to clarify that in 60% of

the patients, “surrogate” MIC values were assumed from population estimates and such approach

could markedly inflate, or even deflate, the magnitudes of PK/PD target non-attainment observed in

this study. In addition, this approach would adversely affect the target attainment rates of IB

patients more than the PI patients if the “surrogate” MIC values were indeed higher than the actual

MIC values. However, when we employed actual MIC data in our analysis, the findings were

consistent with our main approach where PI patients demonstrated numerically higher target

attainment rates, albeit not statistically significant, compared to IB patients across all PK/PD

indices. Actual MIC values would have been preferable although we believe that our present

approach closely “mimics” the real-life clinical approach where the MIC of a pathogen is rarely

available upon antibiotic treatment initiation. We also acknowledge the limitation of Cockcroft-

Gault formula in estimating the measures of renal function in this cohort and measured CLCR would

be more appropriate, particularly in patients with ARC. The post hoc nature of this analysis also

limits our ability to establish a causal relationship between the methods of beta-lactam

administration and clinical outcomes. As the antibiotic dosing regimen and all subsequent patient

management was at the discretion of the treating physician, this might have introduced potential

bias towards a better patient management among PI patients in this study.

4.2.6 Conclusion

This study provides additional PK/PD and clinical outcome data to support the practice of

administration of piperacillin/tazobactam and meropenem by PI in critically ill patients, particularly

for patients with respiratory infections. However, future clinical studies should focus and test the

potential clinical superiority of the altered beta-lactam dosing approaches in a specific subset of

critically ill patients with severe infections and that are not receiving RRT.

92

4.2.7 Acknowledgements

4.2.7.1 Authors’ Contribution

MHAA drafted the manuscript, had full access to the data and took responsibility for the integrity of

the data and the accuracy of the data analysis. JAR and JL designed the study and wrote the initial

protocol. MHAA and JD performed the statistical analysis. JL, MA, MB, JDW, GD, KMK, DK,

CM, PM, JR, AR, TS and JAR helped conduct the trial. All authors provided input into the

interpretation of the data and critical revision of the manuscript for important intellectual content.

4.2.7.2 Members of the DALI Study group

Author name Affiliation

Jason A Roberts Burns Trauma and Critical Care Research Centre, The University of

Queensland, Brisbane, Australia;

Royal Brisbane and Women’s Hospital, Brisbane, Australia

Jeffrey Lipman Burns Trauma and Critical Care Research Centre, The University of

Queensland, Brisbane, Australia;

Royal Brisbane and Women’s Hospital, Brisbane, Australia

Therese Starr Royal Brisbane and Women’s Hospital, Brisbane, Australia

Steven C Wallis Burns Trauma and Critical Care Research Centre, The University of

Queensland, Brisbane, Australia

Sanjoy Paul Queensland Clinical Trials & Biostatistics Centre, School of

Population Health, The University of Queensland,

Brisbane, Australia

Antonio Margarit Ribas Hospital Nostra Senyora de Meritxell, Escaldes-Engordany, Andorra

Jan J. De Waele Ghent University Hospital, Ghent, Belgium

Luc De Crop Ghent University Hospital, Ghent, Belgium

Herbert Spapen Universitair Ziekenhuis Brussels, Brussels, Belgium

Joost Wauters Universitair Ziekenhuis Gasthuisberg, Leuven, Brussels

Thierry Dugernier Clinique Saint Pierre, Ottignies, Belgium

Philippe Jorens Universitair Ziekenhuis Antwerpen, Edegem, Belgium

Ilse Dapper Algemeen Ziekenhuis Monica, Deurne, Belgium

Daniel De Backer Erasme University Hospital, Brussels, Belgium

93

Fabio S. Taccone Erasme University Hospital, Brussels, Belgium

Jordi Rello Vall d'Hebron Institut of Research. Universitat Autonoma de

Barcelona, Spain Centro de Investigación

Biomedica En Red- Enfermedades Respiratorias (CibeRes)

Laura Ruano Vall d'Hebron Institut of Research. Universitat Autonoma de

Barcelona, Spain Centro de Investigación

Biomedica En Red- Enfermedades Respiratorias (CibeRes)

Elsa Afonso Hospital Universitari Vall d'Hebron. Vall d'Hebron Institut of

Research. Universitat Autonoma de

Barcelona, Spain Centro de Investigación Biomedica En Red-

Enfermedades Respiratorias (CibeRes)

Francisco Alvarez-Lerma Hospital Del Mar, Parc Salut Mar. Barcelona, Spain

Maria Pilar Gracia-

Arnillas

Hospital Del Mar, Parc Salut Mar. Barcelona, Spain

Francisco Fernández Centro Médico Delfos, Barcelona

Neus Feijoo Hospital General de L’Hospitalet, Barcelona, Spain

Neus Bardolet Hospital General de L’Hospitalet, Barcelona, Spain

Assumpta Rovira Hospital General de L’Hospitalet, Barcelona, Spain

Pau Garro Hospital General de Granollers, Barcelona, Spain

Diana Colon Hospital General de Granollers, Barcelona, Spain

Carlos Castillo Hospital Txagorritxu, Vitoria, Spain

Juan Fernado Hospital Txagorritxu, Vitoria, Spain

Maria Jesus Lopez Hospital Universitario de Burgos. Burgos, Spain

Jose Luis Fernandez Hospital Universitario de Burgos. Burgos, Spain

Ana Maria Arribas Hospital Universitario de Burgos. Burgos, Spain

Jose Luis Teja Hospital Universitario Marques de Valdecilla, Santander, Spain

Elsa Ots Hospital Universitario Marques de Valdecilla, Santander, Spain

Juan Carlos Montejo Hospital Universitario 12 de Octubre, Madrid, Spain

Mercedes Catalan Hospital Universitario 12 de Octubre, Madrid, Spain

Isidro Prieto Hospital Ramon y Cajal, Madrid, Spain

Gloria Gonzalo Hospital Ramon y Cajal, Madrid, Spain

Beatriz Galvan Hospital Universitario La Paz, Madrid, Spain

94

Miguel Angel Blasco Hospital Universitario Severo Ochoa, Madrid, Spain

Estibaliz Meyer Hospital Universitario Severo Ochoa, Madrid, Spain

Frutos Del Nogal Hospital Universitario Severo Ochoa, Madrid, Spain

Loreto Vidaur Hospital Universitario de Donostia, Donostia, Spain

Rosa Sebastian Hospital Universitario de Donostia, Donostia, Spain

Pila Marco Garde Hospital Universitario de Donostia, Donostia, Spain

Maria del Mar Martin

Velasco

Hospital Universitario Nuestra Señora de Candelaria, Spain

Rafael Zaragoza Crespo Hospital Universitario Dr. Peset, Spain

Mariano Esperatti Institut Clínic del Tòrax, Hospital Clinic, IDIBAPS, Barcelona,

Spain; Centro de Investigación Biomedica En

Red- Enfermedades Respiratorias (CibeRes).

Antoni Torres Institut Clínic del Tòrax, Hospital Clinic, IDIBAPS, Barcelona,

Spain; Centro de Investigación Biomedica En

Red- Enfermedades Respiratorias (CibeRes).

Philippe Montravers Centre Hospitalier Universitaire Bichat-Claude Bernard, AP-HP,

Université Paris VII, Paris, France

Olivier Baldesi Centre Hospitalier Pays D Aix, Aix en Provence, France and AzuRea

Group

Herve Dupont Centre Hospitalier Universitaire d'Amiens, Amiens, France

Yazine Mahjoub Centre Hospitalier-Universitaire d'Amiens, Amiens, France and

AzuRea Group

Sigismond Lasocki Centre Hospitalier-Universitaire d'Angers, Angers, France

Jean Michel Constantin Centre Hospitalier Universitaire de Clermont-Ferrand, Clermont-

Ferrand, France and AzuRea Group

Jean François Payen Centre Hospitalier-Universitaire Grenoble, Grenoble France and

AzuRea Group

Claude Martin Hopital Nord, Marseille, France; AzuRea Group, France

Jacques Albanese Hopital Nord, Marseille, France and AzuRea Group

Yannick Malledant Hôpital Pontchaillou, Rennes, France

Julien Pottecher University Hospital, Strasbourg, France and AzuRea Group

Jean-Yves Lefrant Centre Hospitalier-Universitaire Nimes, Nimes France and AzuRea

95

Group

Samir Jaber Hospitalier-Universitaire Montpellier, Montpellier, France and

AzuRea Group

Olivier Joannes-Boyau Centre Hospitalier-Universitaire Bordeaux, Bordeaux, France and

AzuRea Group

Christophe Orban Centre Hospitalier-Universitaire Nice, Nice, France and AzuRea

Group

Marlies Ostermann St Thomas' Hospital, London, United Kingdom

Catherine McKenzie St Thomas' Hospital, London, United Kingdom

Willaim Berry St Thomas' Hospital, London, United Kingdom

John Smith St Thomas' Hospital, London, United Kingdom

Katie Lei St Thomas' Hospital, London, United Kingdom

Francesca Rubulotta Charing Cross Hospital, Imperial Healthcare NHS Trust, London,

United Kingdom

Anthony Gordon Charing Cross Hospital, Imperial Healthcare NHS Trust, London,

United Kingdom

Stephen Brett Hammersmith Hospital, Imperial Healthcare NHS Trust, London,

United Kingdom

Martin Stotz St Mary's Hospital, Imperial Healthcare NHS Trust, London, United

Kingdom

Maie Templeton St Mary's Hospital, Imperial Healthcare NHS Trust, London, United

Kingdom

Andrew Rhodes St George's Hospital, St George's Healthcare NHS Trust, London,

United Kingdom

Claudia Ebm St George's Hospital, St George's Healthcare NHS Trust, London,

United Kingdom

Carl Moran St George's Hospital, St George's Healthcare NHS Trust, London,

United Kingdom

Kirsi-Maija Kaukonen Helsinki University Central Hospital, Helsinki, Finland

Ville Pettilä Helsinki University Central Hospital, Helsinki, Finland

George Dimopoulos Attikon University Hospital, Athens, Greece

Despoina Koulenti Attikon University Hospital, Athens, Greece

96

Aglaia Xristodoulou Attikon University Hospital, Athens, Greece

Vassiliki Theodorou University Hospital of Alexandroupolis, Alexandroupolis, Greece

Georgios Kouliatsis University Hospital of Alexandroupolis, Alexandroupolis, Greece

Eleni Sertaridou University Hospital of Alexandroupolis, Alexandroupolis, Greece

Georgios Anthopoulos 251 Air Force General Hospital of Athens, Athens, Greece

George Choutas 251 Air Force General Hospital of Athens, Athens, Greece

Thanos Rantis 251 Air Force General Hospital of Athens, Athens, Greece

Stylianos Karatzas General Hospital of Athens ‘Hippokrateion’, Athens, Greece

Margarita Balla General Hospital of Athens ‘Hippokrateion’, Athens, Greece

Metaxia Papanikolaou General Hospital of Athens ‘Hippokrateion’, Athens, Greece

Pavlos Myrianthefs ‘Aghioi Anargyroi’ Hospita, Athens, Greece

Alexandra Gavala ‘Aghioi Anargyroi’ Hospita, Athens, Greece

Georgios Fildisis ‘Aghioi Anargyroi’ Hospita, Athens, Greece

Antonia Koutsoukou Sotiria General Hospital, Athens, Greece

Magdalini

Kyriakopoulou

Sotiria General Hospital, Athens, Greece

Kalomoira Petrochilou Sotiria General Hospital, Athens, Greece

Maria Kompoti ‘Thriassio’ General Hospital of Eleusi, Athen, Greece

Martha Michalia ‘Thriassio’ General Hospital of Eleusi, Athen, Greece

Fillis-Maria Clouva-

Molyvdas

‘Thriassio’ General Hospital of Eleusi, Athen, Greece

Georgios Gkiokas Aretaieion University Hospital, Athens, Greece

Fotios Nikolakopoulos Aretaieion University Hospital, Athens, Greece

Vasiliki Psychogiou Aretaieion University Hospital, Athens, Greece

Polychronis Malliotakis University Hospital Herakleion, Crete, Greece

Evangelia Akoumianaki University Hospital Herakleion, Crete, Greece

Emmanouil Lilitsis University Hospital Herakleion, Crete, Greece

Vassilios Koulouras University Hospital of Ioannina, Ioannina, Greece

George Nakos University Hospital of Ioannina, Ioannina, Greece

Mihalis Kalogirou University Hospital of Ioannina, Ioannina, Greece

Apostolos Komnos General Hospital of Larisa, Larisa, Greece

97

Tilemachos Zafeiridis General Hospital of Larisa, Larisa, Greece

Christos Chaintoutis General Hospital of Larisa, Larisa, Greece

Kostoula Arvaniti General Hospital of Thessaloniki ‘G. Papageorgiou’, Thessaloniki,

Greece

Dimitrios Matamis General Hospital of Thessaloniki ‘G. Papageorgiou’, Thessaloniki,

Greece

Christos Chaintoutis General Hospital of Thessaloniki ‘G. Papageorgiou’, Thessaloniki,

Greece

Christina Kydona General Hospital of Thessaloniki ‘Hippokrateion’, Thessaloniki,

Greece

Nikoleta Gritsi-

Gerogianni

General Hospital of Thessaloniki ‘Hippokrateion’, Thessaloniki,

Greece

Tatiana Giasnetsova General Hospital of Thessaloniki ‘Hippokrateion’, Thessaloniki,

Greece

Maria Giannakou Ahepa University Hospital, Thessaloniki, Greece

Ioanna Soultati Ahepa University Hospital, Thessaloniki, Greece

Ilias chytas Ahepa University Hospital, Thessaloniki, Greece

Eleni Antoniadou General Hospital ‘G. Gennimatas’, Thessaloniki, Greece

Elli Antipa General Hospital ‘G. Gennimatas’, Thessaloniki, Greece

Dimitrios Lathyris General Hospital ‘G. Gennimatas’, Thessaloniki, Greece

Triantafyllia Koukoubani General Hospital of Trikala, Trikala, Greece

Theoniki Paraforou General Hospital of Trikala, Trikala, Greece

Kyriaki Spiropoulou General Hospital of Trikala, Trikala, Greece

Vasileios Bekos Naval Hospital of Athens, Athens, Greece

Anna Spring Naval Hospital of Athens, Athens, Greece

Theodora Kalatzi Naval Hospital of Athens, Athens, Greece

Hara Nikolaou ‘Aghia Olga-Konstantopouleion’ General Hospital, Athens, Greece

Maria Laskou ‘Aghia Olga-Konstantopouleion’ General Hospital, Athens, Greece

Ioannis Strouvalis ‘Aghia Olga-Konstantopouleion’ General Hospital, Athens, Greece

Stavros Aloizos General Hospital of Athens ‘NIMITS’, Athens, Greece

Spyridon Kapogiannis General Hospital of Athens ‘NIMITS’, Athens, Greece

Ourania Soldatou General Hospital of Athens ‘NIMITS’, Athens, Greece

98

Matteo Bassetti Azienda Ospedaliera Universitaria Santa Maria della Misericordia,

Udine, Italy

Chiara Adembri Azienda Ospedaliero Universitaria Careggi, Florence, Italy

Gianluca Villa Azienda Ospedaliero Universitaria Careggi, Florence, Italy

Antonio Giarratano Università degli Studi di Palermo, Palermo, Italy

Santi Maurizio Raineri Università degli Studi di Palermo, Palermo, Italy

Andrea Cortegiani Università degli Studi di Palermo, Palermo, Italy

Francesca Montalto Università degli Studi di Palermo, Palermo, Italy

Maria Teresa Strano Università degli Studi di Palermo, Palermo, Italy

V. Marco Ranieri San Giovanni-Battista Molinette, Turin, Italy

Claudio Sandroni Catholic University School of Medicine, Rome, Italy

Gennaro De Pascale Catholic University School of Medicine, Rome, Italy

Alexandre Molin University of Genoa, Genoa, Italy

Paolo Pelosi University of Genoa, Genoa, Italy

Luca Montagnani Universitaria San Martino, Genova, Italy

Rosario Urbino Universitaria S.Giovanni Battista della Città di Torino, Torino, Italy

Ilaria Mastromauro Universitaria S.Giovanni Battista della Città di Torino, Torino, Italy

Francesco G. De Rosa Universitaria S.Giovanni Battista della Città di Torino, Torino, Italy

V. Marco Ranieri Universitaria S.Giovanni Battista della Città di Torino, Torino, Italy

Teresa Cardoso Hospital de Santo António, Porto, Portugal

Susana Afonso Hospital de St António dos Capuchos, Lisbon, Portgual

João Gonçalves-Pereira Hospital de São Francisco Xavier, Lisbon, Portugal

João Pedro Baptista Hospital de Universidade de Coimbra, Coimbra, Portugal

Murat Akova Hacettepe University School of Medicine, Ankara, Turkey

Arife Özveren Hacettepe University School of Medicine, Ankara, Turkey

4.2.7.3 Funding information

This project has received funding from the European Society of Intensive Care Medicine's

European Critical Care Research Network (ESICM ECCRN), and the Royal Brisbane and Women's

Hospital Research Foundation. Neither organization had a role in study design, analysis or drafting

of the manuscript.

99

4.2.7.4 Transparency declarations

Prof. Roberts is funded by a Career Development Fellowship from the National Health and Medical

Research Council of Australia (APP1048652). All other authors: none to declare.

100

4.3 Conclusion

This chapter supports the notion that altered beta-lactam dosing strategies may not be meritorious to

all critically ill patients but rather in a specific subset of patients with severe infections. Similar to

other previous small-scale studies, data from this chapter suggest that the critically ill patients who

are most likely to benefit from altered dosing strategies are those with severe pneumonia and not

receiving RRT. The information on patient groups which are more likely to benefit from altered

dosing approaches is vital to determine if PI is truly more advantageous than IB dosing. With this

data, future clinical studies should focus and test the potential clinical superiority of PI

administration in this specific subset of critically ill patients.

101

Chapter 5: The ideal characteristics of a clinical trial investigating

continuous infusion versus intermittent bolus dosing of beta-lactam

antibiotics

5.1 Synopsis

Superior bacterial killing of beta-lactam antibiotics via CI compared with traditional IB dosing has

been demonstrated in pre-clinical studies. Superior PK/PD profiles favouring CI administration

have also been reported in studies involving critically ill septic patients. Despite all the theoretical

advantages, to date, no study has conclusively shown any superiority of CI compared to IB dosing

in terms of patient clinical outcomes. Furthermore, recent meta-analyses of published literature

found no significant difference between CI and IB dosing with regards to clinical cure or patient

survival. However, a particularly noteworthy feature in these studies has been the inclusion of non-

critically ill patients, which may mask any potential benefits of either dosing approaches in

critically ill patients with severe sepsis. This chapter describes the methodological shortcomings

that are associated with current clinical studies in the comparison of CI and IB administration of

beta-lactam antibiotics. Several intriguing issues and problems surrounding the interpretation of

results obtained from these clinical studies are also discussed in the chapter. Based on these

discussions, a description of a methodologically robust, definitive clinical trial is proposed.

102

5.2 Manuscript entitled “Continuous beta-lactam infusion in critically ill

patients: the clinical evidence”

The manuscript entitled “Continuous beta-lactam infusion in critically ill patients: the clinical

evidence” has been accepted for publication in the Annals of Intensive Care (2012; 16(2): 37).



Jason A. Roberts and Prof. Jeffrey Lipman. Literature review was performed by the PhD candidate,

Mohd-Hafiz Abdul-Aziz, under the guidance and supervision of Prof. Jason A. Roberts and Prof.

Rinaldo Bellomo. The PhD candidate, Mohd-Hafiz Abdul-Aziz took the leading role in manuscript

preparation and writing with the supervision and guidance of Prof. Jason A. Roberts, Prof. Jeffrey

Lipman, Prof. Rinaldo Bellomo and Dr. Joel M. Dulhunty. All co-authors reviewed and contributed

to the final draft of the manuscript.





Permission has been granted by the publisher and copyright owner, BioMed Central Ltd., to

reproduce the manuscript in this Thesis.

103

CONTINUOUS BETA-LACTAM INFUSION IN CRITICALLY ILL PATIENTS: THE

CLINICAL EVIDENCE

Mohd H. Abdul-Aziz (1), Joel M. Dulhunty (1, 2), Rinaldo Bellomo (3), Jeffrey Lipman (1, 2),

Jason A. Roberts (1, 2, 4)

Affiliation:

(1) Burns, Trauma & Critical Care Research Centre, University of Queensland, Brisbane, Australia.

(2) Department of Intensive Care Medicine, Royal Brisbane and Woman’s Hospital, Brisbane,

Australia.

(3) Department of Intensive Care, Austin Hospital, Melbourne.

(4) Pharmacy Department, Royal Brisbane and Woman’s Hospital, Brisbane, Australia.

Keywords:

Beta-lactam antibiotic; continuous infusion; critically ill; pharmacokinetic; pharmacodynamic;

treatment outcome.


Dr. Joel Dulhunty,

Department of Intensive Care Medicine,

Royal Brisbane and Women’s Hospital,

Herston, QLD 4029, Australia.

Ph: +6 1 7 3636 8111 Fax: +6 1 7 3636 3542

104

5.2.1 Abstract

Beta-lactam antibiotics display time-dependant PD whereby constant antibiotic concentrations

rather than high peak concentrations are most likely to result in effective treatment of infections

caused by susceptible bacteria. CI has been suggested as an alternative strategy, to conventional IB

dosing, to optimize beta-lactam PK/PD properties. With the availability of emerging data, we

elected to systematically investigate the published literature describing the comparative PK/PD and

clinical outcomes of beta-lactam antibiotics administered by CI or IB dosing. We found that the

studies have been performed in various patient populations including critically ill, cancer and cystic

fibrosis patients. Available in vitro PK/PD data conclusively support the administration of beta-

lactams via CI administration for maximizing bacterial killing from consistent attainment of PD

end-points. In addition, clinical outcome data supports equivalence, even with the use of a lower

dose by CI. However, the present clinical data is limited with small sample sizes common with

insufficient power to detect advantages in favour of either dosing strategy. With abundant positive

pre-clinical data as well as document in vivo PK/PD advantages, large multicentre RCTs are needed

to describe whether CI administration of beta-lactams is truly more effective than IB dosing.

105

5.2.2 Introduction

The mortality rate of severe sepsis and septic shock in critically ill patients remains high despite

recent therapeutic advances. Swift and judicious antibiotic use in these patients is vital and any

delays are associated with increases in mortality [4, 357]. Beta-lactam antibiotics are used

commonly and are regarded as a cornerstone in the management of critically ill patients with severe

sepsis in ICUs around the world [357, 383, 384]. However, the occurrence of severe

pathophysiological changes, namely the fluid shift phenomenon [64] and ARC [385], in critically ill

patients may alter the PK of the antibiotics. Thus, appropriate dosing modifications should be

applied to prevent inadequate antibiotic concentrations and therapeutic failure [8, 56, 64].

Antibiotic PD is the discipline that attempts to relate PK parameters to the ability of an antibiotic to

kill or inhibit the growth of bacterial pathogens [11]. Antibiotics can be classified based on these

PD characteristics. Generally, antibiotics are classified into three categories based on their mode of

bacterial killing: (a) concentration-dependent; (b) time-dependent; or (c) both (Figure 5-1). The first

category includes antibiotics, such as aminoglycosides, where the best predictor of efficacy is

Cmax/MIC [386, 387]. Some antibiotics, such as fluoroquinolones and glycopeptides, are more

complex and exhibit both a concentration and time-dependent kill characteristics where the best

predictor of efficacy is AUC0-24/MIC. Therefore, increasing the dose or/and concentration for these

antibiotics can be logically expected to enhance the rate and extent of bacterial killing [388, 389]. In

contrast, higher beta-lactam concentrations do not significantly influence their efficacy. Based on

numerous in-vitro and in-vivo experimental data, it is the duration of effective antibiotic exposure

that is more important for these time-dependent antibiotics [12, 24, 390, 391].

The debate persists about whether traditional IB dosing or CI administration is clinically preferable

for administration of beta-lactam antibiotics. This is despite the fact that beta-lactam PD data

suggest advantages for CI compared with IB [79, 85, 247, 253, 330, 362, 363], showing time-

dependent activity and demonstrating that the fT>MIC best describes its bacterial kill characteristics

[12] (Figure 5-1). Thus, administration via CI should be advantageous, because it inevitably

produces higher and sustained antibiotic concentrations above the MIC. It also is noteworthy that IB

yields unnecessary high peak and low trough concentrations below MIC for much of the dosing

interval [67, 174, 175, 250] (Figure 5-2 and Figure 5-3). The constant and sustainable antibiotic

concentrations provided by CI are particularly important for pathogens with high MIC values. Such

pathogens are relatively common in the ICU [14, 86, 264].

106

Figure 5-1: Study flowchart demonstrating the number of patients who were included and

excluded in each stage of the planned analysis

Abbreviation: AUC0-24, area under the concentration-time curve during a 24-hour time period; Cmax,

maximum plasma antibiotic concentration; T>MIC, time that a drug’s plasma concentration remains

above the minimum inhibitory concentration (MIC) for a dosing period.

Figure 5-2: The simulated concentration-time profile of a beta-lactam when administered by

intermittent bolus dosing or continuous infusion (Vd = 0.22 L/kg; T½ = 2.45 hr)

Legend: Continuous infusion (dotted lines); intermittent bolus dosing (solid lines).

107

Figure 5-3: Observed steady state plasma and tissue concentrations for meropenem

administered to critically ill patients with sepsis by intermittent bolus dosing and continuous

infusion (adapted from Roberts et al., 2009, J Antimicrob Chemother)

Abbreviation: CI, continuous infusion; ISF, interstitial fluid.

Legend:

Continuous infusion (CI) meropenem plasma concentration (solid dark lines); IB meropenem

plasma concentration (dotted grey lines); IB meropenem interstitial fluid (ISF) concentration (solid

grey lines); CI meropenem ISF concentration (dotted dark lines).

Despite these theoretical advantages, a global practice shift towards CI of beta-lactam antibiotics

has not taken place. Although CI has been shown to be superior to IB dosing during in in vitro [152,

219] and in vivo [231, 233, 235, 392] experimental studies, comparative clinical studies have so far

failed to demonstrate significant differences in patient outcome. Furthermore, three recent meta-

analyses of these clinical trials have found similar outcomes between CI and IB, in heterogeneous

hospitalized patient populations [217, 267, 377]. This dissociation between pre-clinical data and

clinical reports raises uncertainty for the treating clinician. Additionally, most trials have important

methodological flaws and have used inconsistent methods and therapeutic end-points [14]. There

also is a lack of general consensus about which patient groups should be investigated and the

appropriate methodology that should be employed to identify whether clinical outcome differences

between these two dosing approaches exist in all hospitalized patients. The possible advantages and

disadvantages from the two dosing methods are further summarized in Table 5-1.

108

Table 5-1: Possible advantages and disadvantages of employing continuous or intermittent

administration of beta-lactam antibiotics

Administration method Advantages Disadvantages

Continuous infusion More predictable antibiotic

pharmacokinetic profiles

Relatively new antibiotic

administration method thus

requiring intensive educational

effort to update clinical staff on

the administration method prior to

implementation

Lower antibiotic daily dose

may be appropriate with

continuous infusion

May increase the cost of treatment

Reduced drug acquisition

costs when lower antibiotic

doses are used

Some beta-lactams

(e.g., meropenem) are not stable

under prolonged exposure at room

temperature and may produce and

enhance degradation products that

cause hypersensitivity reactions

Effective resource

consumption

(e.g., reduce the time

required for pharmacists or

nurses to prepare and

administer antibiotic)

Risk of drug wastage is high with

this approach (e.g., when

treatment ceased before infusion

bag completed)

Intermittent bolus Simple. Pharmacokinetic and

pharmacodynamic targets may not

be achieved (especially in

critically ill patients)

Does not require dedicated

line access for drug

administration

(incompatibility issues

unlikely)

Neurological adverse effects are

theoretically more possible with

high Cmax

Less likely to have

unexpected device failures

and dosing delivery rate

errors

109

The purpose of this review is to describe the published clinical trials and their associated

methodological shortcomings in their comparison of CI and IB administration in hospitalized

patients. Several intriguing issues or problems involved in the interpretation of results obtained

from the available studies also will be highlighted. Finally, based on these discussions, description

of a methodologically robust, definitive clinical trial will be proposed.

5.2.3 PK/PD considerations

The % fT>MIC during a dosing interval is regarded as the optimal PD index for beta-lactam

antibiotics and as such, maintaining effective drug concentration above the MIC should be the

priority when this antibiotic class is used. Specifically, the % fT>MIC needed for bacteriostasis and

bactericidal is 35-40% and 60-70% for cephalosporins, 30% and 50% for penicillins, 20% and 40%

for carbapenems, respectively [10, 11, 152, 393]. However, it is imperative to note that these

indices should be regarded as the minimum PD end-points and that they may not be adequate to

treat severe infections and to prevent the development of antibiotic resistance [394]. Furthermore,

emerging retrospective clinical data for critically ill patients suggest patients’ benefits with higher

and longer antibiotic exposures than those described for the in vitro and in vivo experimental studies

[28, 298]. Thus, it has been suggested that maintaining concentrations above the MIC for 90-100%

of the dosing interval is a rational PD end-point to ensure that the above minimum targets are

achieved [153]. Combining the above data, beta-lactams should be more effective when delivered

continuously to achieve a concentration above the MIC throughout treatment.

Alternatively, prolonging the infusion time via EI dosing, also has been suggested to maximize the

fT>MIC for this antibiotic class without some of the CI-associated drawbacks outlined in Table 5-1

[190, 242]. Both CI and EI may be particularly advantageous in the treatment of severe infections.

5.2.3.1 Inconsistent PD end-points for comparison

Different PD end-points have been used in published studies which make comparison between CI

and IB difficult. However, several reviews have suggested that prolonged antibiotic exposures will

achieve better PD profile [56, 395, 396]. Apparent benefits with regards to maximum bacterial

killing also were reported in several studies when antibiotic concentrations were maintained above

the MIC for extended periods, ideally four- to five-times the MIC especially when less susceptible

microorganisms were involved [25, 28, 82, 152, 221, 397]. In combination with other PK/PD data,

it is suggested that therapeutic targets for CI therapy should be a Css that is at least 4 x MIC [152].

Thus, future comparative PK/PD studies should evaluate the relative ability of IB to achieve a Cmin

110

greater than the 4 x MIC of the offending pathogen for 40-70% of a dosing interval and for CI, a Css

greater than 4 x MIC to prevent biased comparisons. It follows that the real challenge for IB is to

obtain a Cmin greater than 4 x MIC in a severely ill patient who is infected with a pathogen with

high MIC.

5.2.3.2 The role of post-antibiotic effect

Another consideration for optimizing antibiotic pharmacokinetic exposure is the PAE i.e., the

suppression of bacterial growth even with antibiotic concentrations below the MIC [12, 154, 157,

158]. Although all antibiotics demonstrate PAE against susceptible Gram-positive pathogens (i.e.,

staphylococci and streptococci), only some antibiotics, such as the aminoglycosides and

fluoroquinolones produce prolonged PAE for Gram-negative pathogens [12]. In contrast, beta-

lactams except for the carbapenems, produce minimal or no PAE against Gram-negative pathogens.

It follows that the reduced % fT>MIC required for carbapenems bacteriostatic (20%) and bactericidal

(40%) activity may relate to the antibiotics PAE [154, 158, 160-162, 398]. Therefore, the need for

frequent dosing and continuous administration is deemed supplemental when antibiotics such as

carbapenems display significant PAE.

5.2.3.3 Revision in antibiotic breakpoints

The recent revision in antibiotic breakpoints to indicate if an organism is susceptible or resistant to

different antibiotics, as classified by EUCAST and CLSI, have had an impact on how clinicians

view and manage infections worldwide [14]. These new rules also are applicable for interpretation

of antibiotic PK/PD studies. Due to these changes, future studies need to be interpreted in light of

the new susceptibility breakpoints [361]. These new rules may mean that the present dosing

approaches are more, or less likely to achieve PK/PD targets.

5.2.3.4 The role of optimal PK/PD targets in the prevention of antibiotic resistance

Antibiotic resistance patterns have significantly changed during the past 15 years with increasing

resistance currently regarded as a major health crisis [399, 400]. Furthermore, the rate at which the

pathogens are currently developing antibiotic resistance is likely to far outpace the rate of

development of new antibiotics. Thus, optimizing the use of new or existing antibiotics via PK/PD

principles may prolong their life span in clinical practice [10, 398]. Although numerous studies

have been performed to determine the optimal PK/PD targets for clinical and bacteriological

success, very little data exist that describe their roles in the prevention of bacterial resistance.

111

However, extensive research in this area has been conducted with fluoroquinolones and more

importantly, the corresponding optimal PD targets (i.e., AUC/MIC breakpoints) for resistance

prevention has been described for this antibiotic class [349, 401, 402]. The success with

fluoroquinolones further emphasizes that PK/PD principles are not only relevant in bacterial

eradication but also should be considered to minimize the development of bacterial resistance. For

the beta-lactams, however, limited data are currently available, with the exception of several in vitro

[365, 403] and in vivo experimental studies [404], which suggest the optimal PD targets for the

prevention of resistance. Thus, appropriate targets are initially needed for this antibiotic class before

a dosing regimen that minimizes resistance development can be recommended. Until convincing

evidence becomes available, antibiotic dosing that targets concentrations greater than 4-6 x MIC for

an extended interval should be aimed at to prevent resistance [149, 152, 405]. It also follows that

once the targets are defined, it will then be possible to evaluate the relative ability of CI versus IB in

reducing the emergence of resistance associated with the use of beta-lactam antibiotics. However,

several reviews have suggested that the currently proposed PK/PD target is probably best achieved

by using CI or EI [14, 153].

5.2.4 Controversies surrounding data interpretation

Since the initial availability of antibiotics, methods to optimize antibiotic dosing have been explored

[391, 406]. Numerous trials have been conducted with beta-lactams testing various dosing strategies

in various patient populations [82, 151, 171-173, 243, 248, 254-258, 261, 262, 266, 305, 407]. The

characteristics and findings of these relevant clinical trials are described in Tables 5-2 and 5-3,

respectively. However, these studies have not defined whether altered dosing approaches are

advantageous and which patient groups may benefit. Most of these trials were conducted in North

America and Europe between 1979 and 2008 with all but two studies published after the year 2000

[255, 262]. A number of articles also have discussed the potential advantages and disadvantages of

CI [14, 15, 17, 153, 264]. Yet, the limitations of the existing studies have not been analysed in

detail and require further elaboration. Figure 5-4 briefly summarizes the current limitations

associated with the available clinical trials.

112

Table 5-2: Characteristics of previously published studies of continuous versus bolus dosing of beta-lactam antibiotics

Study Setting

(Country)

Antibiotic Critically ill Population Sample

size

Agea Allocation

sequence

generator

Allocation

concealment

Masking Concomitant

antibiotic CI IB

Angus et al.,

[151]

Not specified

(Thailand)

Ceftazidime Yes Septicaemic

melioidosis

21 48

(29-58)

43

(27-73)

Not specified Not specified Not specified Various

Bodey et al.,

[255]

Non-ICU

(USA)

Cefamandole No Malignant diseases

with neutropenia

204 Not specified Adequate Adequate Not specified Carbenicillin

Buck et al.,

[173]

Non-ICU

(Germany)

Piperacillin/tazobactam No Hospitalized

infections

24 60-88b 32-76b Not specified Adequate No Nil stated

Georges et al.,

[172]

ICU

(France)

Cefepime Yes Critically ill with

Gram-negative

infections

50 50±17 46±24 Not specified Not specified No Amikacin

Hanes et al.,

[254]

ICU

(USA)

Ceftazidime Yes Critically ill trauma 32 33.5±12.5 36.1±12.8 Not specified Not specified No Nil stated

Lagast et al.,

[262]

Not specified

(Belgium)

Cefoperazone No Gram-negative

septicaemia

45 37-77b Not specified Not specified No Nil stated

Lau et al.,

[256]

ICU

(USA)

Piperacillin/tazobactam No Complicated intra-

abdominal infections


Lubasch et al.,

[258]

Not specified

(Germany)

Ceftazidime No Hospitalized patients

with COPD

exacerbation

81 65.3±10.1 Not specified Not specified No Nil stated

Nicolau et al.,

[266]

ICU

(USA)


with sepsis

41 46±16 56±20 Adequate Not specified No Tobramycin

Pedeboscq et al.,

[261]

ICU

(France)

Piperacillin/tazobactam Yes Severe sepsis 7 58±12 Not specified Not specified No Ofloxacin

Rafati et al.,

[248]

ICU

(Iran)

Piperacillin Yes Critically ill patients

with sepsis

40 50.1±22.2 48.0±20.7 Not specified Not specified No Amikacin

Roberts et al.,

[243]

ICU

(Australia)

Ceftriaxone Yes Critically ill patients

with sepsis

57 43±19 52±16 Adequate Adequate Adequatec Multiple

depending on

indication

Sakka et al.,

[171]

ICU

(Germany)

Imipenem/cilastatin Yes Critically ill patients

with sepsis

20 62±16 59±16 Not specified Adequate No Nil stated

Van Zanten et al.,

[257]

Not specified

(Netherlands)

Cefotaxime No Hospitalized patients

with COPD

exacerbation


Abbreviation: CAP, community-acquired pneumonia; CI, continuous infusion; COPD, chronic obstructive pulmonary disease; CVVH, continuous venovenous haemofiltration; IB, intermittent bolus; ICU, intensive care unit.

Legend:

aValues are reported according to published results as mean (±SD) or median (interquartile range).

bValues are reported as range.

cOnly outcome assessment was blinded.

113

Table 5-3: Antibiotics dosage and outcome data of previously published studies for CI versus IB dosing of beta-lactam antibiotics

Study Types of infection Number of patients

(APACHE II scorea)

Antibiotic dosage regimen Concurrent

PK/PD analysis

Clinical outcome

measures

CI IB p-valueb

CI IB CI IB

Angus et al.,

[151]

Septicaemic

melioidosis

10 (15) 11 (21) 12 mg/kg LD, then 4

mg/kg every 1 hr

40 mg/kg every 8 hrs Yes Mortality 20% 36.4% 0.89

Bodey et al.,

[255]

Pneumonia, UTI &

neutropenic fever

167 (ND) 162 (ND) 3 g LD, then 12 g/24

hrs


Buck et al.,

[173]

Pneumonia, IAI & fever

of unknown origin

12 (ND) 12 (ND) 2 g LD, then 8 g/24 hrs 4 g every 8 hrs Yes Clinical response 67% 67% ND

Georges et al.,

[172]

Pneumonia & blood

stream infection

24 (45)c 23 (44)c 2 g/12 hrs twice daily 2 g every 12 hrs No Clinical cure 85% 67% ND

Mortality 12% 13% ND

Duration of MV 24 days 25 days ND

ICU LOS 34 days 40 days ND

Hanes et al.,

[254]

Pneumonia 17 (13) 14 (11) 2 g LD, then 60 mg/kg

every 24 hrs

2 g every 8 hrs Yes Duration of leukocytosis 8 days 11 days 0.35

Duration of pyrexia 8 days 4 days 0.06




Lagast et al.,

[262]

Blood stream infection 20 (ND) 25 (ND) Day 1: 1 g LD, then 3

g/24 hrs

Day 2 +: 4 g/24 hrs


ICU mortality 70% 80% ND

Lau et al.,

[256]

IAI 81 (8) 86 (8) 2 g LD, then 12 g /24

hrsg

3 g every 6 hrsg No Clinical cure 86% 88% 0.817


Lubasch et al.,

[258]

Pneumonia 41 (ND) 40 (ND) 2 g LD, then 2 g/7 hrs

twice daily

2 g every 8 hrs Yes Clinical cure 90% 90% ND

Bacteriological cure 90% 88% ND

Nicolau et al.,

[266]

Pneumonia 17 (14) 18 (16) 1 g LD, then 3 g/24 hrsh 2 g every 8 hrsh No Clinical cure 41% 33% 0.592


Days to defervescence 3 days 5 days 0.015

Days to WCC

normalization

7 days 6 days 0.259

LOS ICU 9 days 9 days 0.691

Pedeboscq et al.,

[261]

IAI 3 (ND) 4 (ND) 12 g/24 hrs 4 g every 8 hrs Yes Mortality 0% 0% ND

Rafati et al.,

[248]

Pneumonia, IAI, UTI,



20 (16) 20 (14) 2 g LD, then 8 g/24 hrs 3 g every 6 hrs Yes Mortality 30% 25% 0.72

Decrease in illness

severity

CI>ITd

Duration of pyrexia 2 days 1 day 0.08

WCC normalization 75% 83% ND

114

Roberts et al.,

[243]

Pneumonia, IAI, UTI,



29 (19) 28 (16) 0.5 g LD, then 2 g/24

hrs

Day 1: 2.5 g/24 hrs

Day 2: 2 g/24 hrs

No Clinical curee 52% 20% 0.04

Mortality 10% 0% 0.25




Sakka et al.,

[171]

Pneumonia 10 (26) 10 (28) 1 g LD, then 2 g /24 hrs 1 g every 8 hrs Yes Mortality 10% 20% ND

Van Zanten et al.,

[257]

COPD exacerbation 40 (ND) 43 (ND) 1 g LD, then 2 g/24 hrs 1 g every 8 hrs Yes Clinical cure 93% 93% 0.93

Abbreviation: APACHE, Acute Physiology and Chronic Health Evaluation; CI, continuous infusion; CNS, central nervous system; CRP, C-reactive protein; IAI, intra-abdominal infection; IB, intermittent bolus; ICU,

intensive care unit; LD, loading dose; LOS, length of stay; MV, mechanical ventilation; ND, not described; PK/PD, pharmacokinetic/pharmacodynamic; SOFA, Sequential Organ Failure Assessment; SSTI, skin and skin-

structure infection; UTI, urinary tract infection; WCC, white cell counts.

Legend:

aValues are reported as mean or median.

bBold values indicate statistical significance at p <0.05.

cValues are SAPS scores.

dStatistically significant difference in APACHE II scores on Days 2, 3 and 4.

eA priori analysis.

115

Figure 5-4: The summary of the current limitations and flaws associated with the available

clinical trial

5.2.4.1 Heterogeneous patient populations

Most of the relevant trials recruited hospitalized patients from different populations, especially the

non-critically ill patient groups (Table 5-2). The diverse range of patient groups include critically ill

patients with sepsis [151, 172, 243, 248, 261, 262, 266], trauma patients (86), patients with

abdominal infections [256, 407], COPD patients [257, 258], cancer [255] and non-specific

hospitalized infections [173]. Thus, meta-analyses have evaluated heterogeneous patient groups and

any potential benefits of CI or IB that may exist in a particular patient group were not assessed. This

issue was previously discussed by Roberts et al., in their meta-analysis, where large CI were

observed suggesting clinical differences may exist between CI and IB administration if more

stringent and rigorous inclusion criteria were used in clinical studies [217].

5.2.4.2 Inclusion of patients with a low level of illness severity

Detecting significant difference between CI and IB is difficult because the potential benefits may be

masked by the inclusion of low-risk patients who have much lower mortality rates than reported in

epidemiological studies. This selection bias was further described in two recent meta-analyses [217,

116

377]. For example, two of the nine ICU studies that were meta-analysed by Roberts et al., reported

a mortality rate ≤10% when the mortality rate for severe sepsis is usually reported between 40% and

50% [33, 408, 409] (Table 6-3). Other studies also recruited patients with low illness severity

whereby more than 70% of the cohort presented with an APACHE II score of only 10 [256]. This is

a problem because any differences between CI and IB are more likely emerge in more severely ill

patients [151, 298]. Critically ill patients with severe sepsis are more likely to benefit from CI,

because they commonly develop severe pathophysiological changes which may reduce effective

antibiotic exposure [129]. Furthermore, these patients are usually infected with pathogens that are

less susceptible to antibiotic therapy. Thus, in combination, the two important factors may reduce

PK/PD target attainment in severely ill patients. In contrast, it has been shown that IB dosing of

beta-lactam antibiotics achieves adequate PK/PD target for bacterial eradication in patients with low

level of illness severity.

5.2.4.3 Inconsistent antibiotic dosing regimen

Most of the studies included in the three meta-analyses utilized higher IB doses than the CI

treatment arm, potentially favouring the former [151, 171, 173, 248, 254, 256, 257, 266] (Table 5-

3). This treatment bias might have skewed the results of these meta-analyses towards the null

hypothesis. Another logical conclusion is that a lower dose in the CI group was able to achieve

equivalent outcomes to a higher dose in the IB group. A significant difference in clinical outcomes

might emerge if the two approaches utilized the same daily dose. This notion has been supported by

a meta-analysis, whereby clinical failures were less frequent in the CI group, when separate

analyses were performed in trials which used the same total daily dose in the two treatment arms

[267]. Furthermore, dosing inconsistency with regards to initial bolus administration of antibiotic

was reported in several studies [172, 261, 407] (Table 5-3). An initial loading dose was not

provided to the CI protocol in these studies. This approach delays attainment of target antibiotic

concentrations compared with the IB group. To make the two dosing protocols comparable, an

initial and equal loading dose of beta-lactam antibiotic should be provided to both groups.

5.2.4.4 Pathogens with low MIC values

The offending pathogens isolated in most of the clinical trials have MIC values that make them

highly susceptible. Simulation data suggests that there will be little difference in the achievement of

PK/PD targets for IB and CI if the pathogens involved are in the susceptible range. When less

susceptible pathogens are present, the true potential benefits of CI may be seen because treatment

failures are more likely with IB [28, 151, 174, 398]. This limitation has been highlighted in the two

117

most recent meta-analyses and has been proposed as one of the contributing reasons why clinical

differences between CI and IB of beta-lactams have not been found. This notion is supported by one

RCT [151] and two retrospective, observational studies [274, 298] which were conducted in

critically ill patients infected with Gram-negative organisms. These studies reported clinical cure

and mortality benefits favouring CI for pathogens with high MIC values.

5.2.4.5 Concomitant administration of other antibiotics

Another noteworthy limitation is that patients included in the available clinical trials were

frequently prescribed concomitant antibiotics that, unrelated to the method of beta-lactam

administration, may influence clinical outcome [267, 377]. Such additional antibiotics

(aminoglycosides and fluoroquinolones) provide adequate antimicrobial coverage for most Gram-

negative pathogens. Therefore, the exclusive contribution of beta-lactam antibiotics to patient

outcomes will be poorly defined in these trials. However, in reality, beta-lactam antibiotics are

usually administered in conjunction with an aminoglycosides especially when treating patients with

severe infections. It follows that regardless of the beta-lactam administration method, the

aminoglycosides or fluoroquinolones may be “protecting” patients from Gram-negative pathogens

during periods of inadequate beta-lactams concentration. A plausible explanation could be that the

method of administering beta-lactams is not that important when additional Gram-negative

coverage (i.e., aminoglycosides or fluoroquinolones) is used.

5.2.4.6 Insufficient sample sizes

The lack of significance in the published results also may be attributed to the consistently small

sample sizes that have been used to explore the effect of CI versus IB. The typical study cohort size

has varied from 10 to 531 patients but the majority of these trials studied less than 60 patients [82,

171-173, 243, 248, 254, 262, 266, 407] (Table 5-2). The small sample sizes and heterogeneous

patient background in the clinical studies contribute to insufficient power to investigate the value of

both dosing methods. Further to this, if the population of interest is critically ill patients, a single

intervention in this setting is unlikely to influence mortality and clinical cure [264] and, as a

consequence, a much larger sample size is needed to show significance [172, 267, 330]. For

instance, Roberts et al., calculated that a sample size of 560 patients in each dosing protocol would

be needed to detect difference in bacteriological outcomes [243]. Considering the difficulties in

achieving these numbers in critically ill patients, perhaps it is time for clinicians to fully

acknowledge the importance of surrogate end-points in the setting of a study. Clinical cure and

118

ICU-free days are suitable surrogate end-points and may be used as primary outcomes in a phase II

study of this intervention.

5.2.5 Other relevant concerns

Apart from the discussion above, there are several other plausible reasons why clinical differences

have not been established between CI and IB in previous trials. It is important to note that some

patients, especially in the ICU, may have some degree of renal impairment on admission or during

their hospital stay [136, 410, 411]. Whereas a commonly prescribed beta-lactam dose may not be

sufficient in patients with mild or no renal impairment, target antibiotic concentrations are more

easily achieved in patients with moderate to advanced renal impairment [211]. Similarly, beta-

lactam exposure will still be adequate in patients with significant renal impairment as antibiotic CL

is reduced, regardless of the drug administration method [253]. Finally, one of the strongest bodies

of evidence suggesting the superiority of CI has been derived from animal studies. However, the

metabolic pathways and tissue distribution patterns of an antibiotic in animals may differ from

humans. In addition, more often than not, these animal models fail to mimic human sepsis [412,

413].

Based on the discussion above, clearer insights regarding CI and IB administration in patients

receiving beta-lactam antibiotics are emerging. Importantly, the results from previous clinical

studies suggest that CI of beta-lactam antibiotics is unlikely to be advantageous for all hospitalized

patients but may be important in specific patient cohorts. Thus, in an attempt to elucidate the true

benefits, we contend that the patient population most likely to adequately test the putative benefits

of CI of beta-lactam antibiotics must involve: (a) critically ill patients; (b) patients with higher level

of illness severity (i.e., APACHE II score ≥15); (c) patients infected with less susceptible

microorganisms; and (d) patients with Gram-negative infections.

5.2.6 Methodology concerns and the proposed characteristics of an “ideal” trial

Several reviews have suggested the importance of designing and conducting a methodologically

sound clinical trial in the investigation of CI versus IB antibiotic administration benefits in critically

ill patients [14, 217, 267, 377]. These recommendations cannot be overemphasized due to frequent

reports of low methodological quality clinical studies. It also is noteworthy that a previous study,

which utilized the most rigorous and stringent methods was the only study to demonstrate a clinical

cure advantage in favour of CI administration of beta-lactams [243]. The characteristics of an

119

“ideal,” randomized, clinical trial to compare CI versus IB administration of beta-lactam antibiotics

in critically ill patients are described in Table 5-4.

Table 5-4: Description of a randomized clinical trial that should be performed to investigate

CI versus IB of beta-lactam antibiotics

Criteria Comments

Population Should only include patients with sepsis or severe sepsis

Intervention Antibiotic dosing regimen should be similar between CI and IB group

a. A loading dose should be given to continuous infusion group to

ensure rapid attainment of target antibiotic concentration

b. An equal daily antibiotic dose should be given to continuous and

bolus administration group

c. Antibiotic doses should be specified according to the patient’s body

weight

d. Concomitant administration of other non-beta-lactam antibiotics

should be allowed

PK/PD analysis Concurrent PK/PD analysis should be performed to support any findings

a. Measurements of antibiotic concentrations should be performed as

long as contributing sites have necessary infrastructure to ensure apt

sampling

b. PK/PD analysis should evaluate the relative ability of IB to achieve a

Cmin greater than 4 x MIC of the offending pathogen for 40-70% of

the dosing interval while for CI, a Css greater than 4 x MIC

Methods Design

Preferably multicenter in nature and recruits participants from different

regions to improve generalizability of results

Patients

Define eligibility criteria for participants to be included into trial

a. Definition of sepsis and severe sepsis should be described in detail

b. Inclusion and exclusion criteria used should be explained

Randomization

Detailed explanation on allocation sequence generation development

Detailed allocation concealment mechanism

Blinding/masking

Outcome evaluators for the trial should be blinded to treatment allocation

End-points

a. End-points selection should include primary (clinical outcome) and

secondary (PK/PD; adverse event) end-points

b. Data collection on the observed bacterial resistance in the two

treatment arms should occur

120

Most studies did not address the methods for allocation sequence generation and concealment

further increasing the chance for selection bias [172, 173, 248, 254, 256-258, 261, 262, 266, 305,

407] (Table 5-2). In many studies, masking or blinded assessment of the study end-points were not

adequately addressed causing detection bias [151, 171-173, 248, 254-258, 262, 266, 305, 407]

(Table 5-2). In addition, most of the available studies have failed to have blinded clinicians to assess

the clinical and bacteriological outcomes. Each of these issues increases the possibility of

systematic errors in these studies.

Ideally, the antibiotic dosing regimen in each treatment arm (i.e., CI and IB) should be comparable

in terms of the provision of an initial loading dose with an equal daily antibiotic dose. Alternatively,

a suitable surrogate end-point, such as a cost-effective analysis, may be used to compare these two

dosing approaches when unequal antibiotic doses are used between them. Concomitant

administration of other non-beta-lactam antibiotics, such as the aminoglycosides or

fluoroquinolones, in the setting of a study is appropriate considering that a single empirical therapy

is unlikely to occur during antibiotic initiation in ICU patients [357, 384]. Furthermore, the

concomitant administration of other antibiotics should be regarded as a limitation rather than a

major flaw in future trials, because it reflects real clinical practice. However, the number of

concomitant antibiotics that are used and their administration sequences in relation to the main

study antibiotic should at least be described in the trials.

Only a number of studies measured antibiotic concentrations and included a concurrent PK/PD

evaluation to confirm whether the dosing approaches were actually meeting their respective PK/PD

end-points (Table 5-3) [82, 171, 248, 254, 256, 257]. Hence, it is difficult to relate clinical

outcomes to the respective antibiotic exposure obtained via the two approaches. It is imperative to

note the difference in PK/PD end-points with regards to CI and IB. In a comparison that reflects

current practice, CI has to achieve a Css greater than 4 x MIC to be microbiologically more effective

than IB. On the other hand, IB has to achieve an antibiotic Cmin greater than 4 x MIC during the

typical 40-70% of the dosing interval [14, 151, 152, 358]. Therefore, concentration measurement

and concurrent PK/PD analysis needs to be done in light of this information or the extent of

antibiotic exposure may not occur as predicted and therefore the influence on clinical cure and

mortality will remain unclear. Concurrent analysis should be considered “compelling” in future

trials as long as contributing clinical sites have the necessary infrastructure to ensure appropriate PK

sampling.

121

Considering the rampant development of bacterial resistance, the exact role of altered dosing

approaches to reduce the problem should be addressed. To date, studies investigating the impact of

various beta-lactams dosing approaches and their associated risk of bacterial resistance are scarce

[149]. However, it is interesting to note the findings of a recent prospective, multicenter,

randomized study that compared the clinical benefits of EI doripenem versus IB imipenem patients

with VAP [305]. The authors reported that only 18% of patients treated with EI developed

resistance of P. aeruginosa compared with 50% who received the conventional imipenem dosing.

This is one of the few recent studies to evaluate the relative ability of the two dosing approaches in

the prevention of resistance; similar studies, particularly involving critically ill patients, should

ensue. Although there are not enough prior clinical data to power a study in the ICU and describe

the appropriate methodology, data collection on the observed resistance should be performed in

future clinical trials investigating the two dosing approaches.

Previously published studies have mostly been single-center in design. To our knowledge, only

three studies were conducted as a multicenter study, and only two of the three studies were able to

include more than 200 patients [256, 258, 305]. The need for more multicenter studies should be

emphasized, because these studies will provide a stronger basis for subsequent generalization of any

findings. Participation from different regions and countries in such studies also should be

encouraged to facilitate generalization even more to an extent of a possible global practice change.

Because of the cost of large-scale trials, a step-wise approach to consider potential problems and

feasibility is desirable. An initial pilot study before proceeding with a larger multicenter trial is

beneficial. In this regard, the BLING I feasibility study has now led to the design of large clinical

outcome study, BLING II. BLING I was a prospective, multicenter, double-blind, double dummy,

pilot RCT enrolling 60 critically ill patients from 5 ICUs across Australia and Hong Kong [166].

The primary end-point of the study was to establish the PK separation between CI and IB in terms

of achieving plasma antibiotic concentrations above the MIC of causative pathogens. The PK

findings in BLING I demonstrated significant differences in plasma antibiotic concentrations above

MIC favouring the CI group (CI; 81.8 % versus IB; 28.6 %, p = 0.001) thus supporting the notion of

PK/PD superiority associated with CI administration. Clinical cure also was superior in the CI

group (CI; 70.0 % versus IB; 43.3 %, p = 0.037). Other relevant findings include the feasibility of

the proposed randomization and blinding process used by the BLING I investigators and the

suggestion of appropriate surrogate end-points for survival to be utilized in a multicenter study.

Thus, based on the findings from BLING I, BLING II was designed with rigorous and stringent

methods to answer the ultimate question of whether administration of beta-lactam antibiotics by CI

122

will result in improved outcomes for patients with severe sepsis. BLING II is a phase II,

multicenter, double-blinded, RCT that will recruit critically ill patients with severe sepsis in several

ICUs in New Zealand as well as Australia and Hong Kong. The Australian National Health and

Medical Research Council (NHMRC)-funded clinical trial aims to compare the effects of two

approaches to the administration of beta-lactam antibiotics (i.e., CI versus IB) on ICU-free days up

to day 28.

5.2.7 Conclusion

Although numerous PK/PD data from various in vitro and in vivo experimental studies favour the

use of CI dosing, the current clinical data are less convincing and insufficient to instigate a global

shift from conventional bolus dosing. However, this lack of convincing data may be due to several

methodological flaws and inconsistencies among the available studies, thus contributing towards

insufficient power to detect any significant differences between CI and IB, if they exist. Based on

the published literature, it can be concluded that CI of beta-lactams will not be beneficial to all

patients, but may potentially be beneficial in specific subsets of patients. If any patient group is

likely to benefit from CI, it may be critically ill patients with severe infections. If benefits from CI

do exist in critically ill patients, a large-scale, prospective, multinational trial with a robust design is

required. A step-wise approach to conduct such clinical trials has begun and already shows promise.

A phase II study involving 420 patients is about to start and will provide high quality information to

confirm or refute the need for a pivotal phase III double-blinded RCT of CI versus IB dosing of

beta-lactam antibiotics in critically ill patients with sepsis.

123

5.3 Conclusion

This chapter describes numerous limitations associated with previous studies in this area, which has

reduced the quality of any findings related to whether CI or IB administration of beta-lactam

antibiotics should be preferred in critically ill patients with severe sepsis. The data presented in this

chapter also highlighted that previous studies lacked a design that was sufficient to explore the

effect of both dosing approaches with regards to clinical outcomes, and some involved small patient

numbers. Other methodological flaws associated with previously published studies include an

absence of allocation sequence generation and allocation concealment, possibly leading to selection

bias. Masking or blinding of health care providers was also not adequately addressed making

detection bias a possibility in most of these studies. Thus, it is critical for future clinical studies to

address these limitations in order to conduct a methodologically sound and robust RCT. In addition

to these methodological flaws, most previous studies recruited participants with low burden of

disease and with highly susceptible microorganisms. Such subject selection may mask the potential

advantages of CI of beta-lactams in critically ill patients with severe sepsis where PK alterations

will be more pronounced. There are no apparent benefits of one approach over the other in the

management of highly susceptible pathogens. If many patients with highly susceptible pathogens

are included in a study, the sample size required to show a clinical difference between CI and IB

dosing will rise dramatically. Hence, future studies should focus on recruiting critically ill patients

with severe sepsis that are at risk of infection by less-susceptible pathogens to determine if true

differences exist between the two dosing approaches.

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Chapter 6: Continuous beta-lactam infusion in critically ill patients with

severe sepsis: A prospective, two-centre, open-labelled, randomized

controlled trial

6.1 Synopsis

Although CI has been suggested as one of the methods to optimize beta-lactams dosing in critically

ill patients, most clinical outcome studies have failed to demonstrate a clinical advantage over

conventional IB dosing in terms of clinical cure and patient survival. Meta-analyses of these

outcome studies have also not found any significant clinical benefits favouring CI over IB dosing.

However, the efficacy of CI administration in critically ill patients has not been investigated in

high-quality RCTs. Most of the available studies recruited heterogeneous patient groups and have

important methodological inconsistencies that may mask any possible merits of CI dosing, if they

exists in critically ill patients. However, three recent RCTs which utilized a more rigorous and

stringent methodology have reported some clinical outcome advantages favouring CI administration

of beta-lactam antibiotics. Hence, this chapter aims to address all the methodological limitations of

previous studies by performing a methodologically sound and robust prospective RCT to

investigate the clinical and PK/PD outcomes associated with CI and IB dosing of beta-lactam

antibiotics in a cohort of critically ill patients with severe sepsis.

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6.2 Manuscript entitled “BLISS: Beta-Lactam Infusion in Severe Sepsis: a

prospective, two-centre, open-labelled, randomized controlled trial of

continuous versus intermittent beta-lactam infusion in critically ill patients with

sepsis”

The manuscript entitled “BLISS: Beta-Lactam Infusion in Severe Sepsis: a prospective, two-centre,

open-labelled, randomized controlled trial of continuous versus intermittent beta-lactam infusion in

critically ill patients with sepsis” has been accepted for publication in the Intensive Care Medicine

(2016).


design was performed by the PhD candidate, Mohd-Hafiz Abdul-Aziz, Dr. Helmi Sulaiman, Dr.

Mohd-Basri Mat-Nor, under the guidance of Prof. Jason A. Roberts. Literature review was


Roberts. Data collection was performed by the PhD candidate, Mohd-Hafiz Abdul-Aziz, Dr. Helmi

Sulaiman, Dr. Vineya Rai, Dr. Kang K. Wong, Dr. Mohd. S. Hasan and Azrin N. Abd Rahman.

Sample bioanalysis was performed by the PhD candidate, Mohd-Hafiz Abdul-Aziz, and Janattul-

Ain Jamal, under the supervision of Dr. Steven C. Wallis. Data analysis was performed by the PhD

candidate, Mohd-Hafiz Abdul-Aziz, under the supervision of Prof. Jason A. Roberts. The PhD

candidate took the leading role in manuscript preparation and all co-authors reviewed and

contributed to the final draft of the manuscript.





Permission has been granted by the publisher and copyright owner, Springer Science + Business

Media (License no: 3886900914112), to reproduce the manuscript in this Thesis.

126

BLISS: Beta-Lactam Infusion in Severe Sepsis: a prospective, two-centre, open-labelled,

randomized controlled trial of continuous versus intermittent beta-lactam infusion in

critically ill patients with severe sepsis

Authors

Mohd H. Abdul-Aziz (1, 2), Helmi Sulaiman (3), Mohd-Basri Mat-Nor (4), Vineya Rai (5), Kang K.

Wong (5), Mohd S. Hasan (5), Azrin N. Abd Rahman (2, 6), Janattul A. Jamal (7), Steven C. Wallis

(1), Jeffrey Lipman (1, 8), Christine E. Staatz (6, 9), Jason A. Roberts (1, 6, 8)

Affiliation

(1) Burns, Trauma & Critical Care Research Centre, The University of Queensland, Brisbane,

Australia.

(2) School of Pharmacy, International Islamic University of Malaysia, Kuantan, Pahang, Malaysia.

(3) Infectious Diseases Unit, Department of Medicine, Faculty of Medicine, University of Malaya,

Kuala Lumpur, Malaysia.

(4) Department of Anaesthesiology and Intensive Care, School of Medicine, International Islamic

University of Malaysia, Kuantan, Pahang, Malaysia.

(5) Department of Anaesthesiology, Faculty of Medicine, University of Malaya, Kuala Lumpur,

Malaysia.

(6) School of Pharmacy, The University of Queensland, Brisbane, Australia.

(7) Department of Pharmacy, Hospital Tengku Ampuan Afzan, Kuantan, Malaysia.

(8) Department of Intensive Care Medicine, Royal Brisbane and Women’s Hospital, Brisbane,

Australia.

(9) Australian Centre of Pharmacometrics, Brisbane, Australia.

Running title: Continuous beta-lactam infusion.

Keywords: antibiotics, critically ill, intermittent bolus, pharmacokinetics, pharmacodynamics,

prolonged infusion.

Corresponding author:


Burns, Trauma & Critical Care Research Centre, The University of Queensland,


Herston, Queensland, 4029 Australia

127

Ph +61736361847; Fax +61736463524


Alternate corresponding author:

Mohd H. Abdul-Aziz

Burns, Trauma and Critical Care Research Centre, The University of Queensland,


Herston, Queensland, 4029 Australia

Ph +61736361847; Fax +61736463524




128

6.2.1 Abstract

6.2.1.1 Purpose

This study aims to determine if CI is associated with better clinical and PK/PD outcomes compared

to IB dosing in critically ill patients with severe sepsis.

6.2.1.2 Methods

This was a two-centre, RCT of CI versus IB dosing of beta-lactam antibiotics, which enrolled

critically ill participants with severe sepsis who were not on RRT. The primary outcome was

clinical cure at 14 days after antibiotic cessation. Secondary outcomes were PK/PD target

attainment, ICU-free days and ventilator-free days at day 28 post-randomization, 14- and 30-day

survival, and time to WCC normalization.

6.2.1.3 Results

One-hundred and forty (140) participants were enrolled with 70 participants each allocated to CI

and IB dosing. CI participants had higher clinical cure rates (56% versus 34%, p = 0.011) and

higher median ventilator-free days (22 days versus 14 days, p <0.043) than IB participants. PK/PD

target attainment rates were higher in the CI arm at 100% fT>MIC than the IB arm on Day 1 (97%

versus 70%, p <0.001) and Day 3 (97% versus 68%, p <0.001) post-randomization. There was no

difference in 14-day or 30-day survival between the treatment arms.

6.2.1.4 Conclusions

In critically ill patients with severe sepsis not receiving RRT, CI demonstrated higher clinical cure

rates and had better PK/PD target attainment compared to IB dosing of beta-lactam antibiotics.

Continuous beta-lactam infusion may be mostly advantageous for critically ill patients with high

levels of illness severity and not receiving RRT.

Malaysian National Medical Research Register ID: NMRR-12-1013-14017.

129

6.2.2 Introduction

Mortality due to severe infections remains persistently high worldwide, ranging from 30-50% in

patients with severe sepsis and 40-80% in those with septic shock [1]. Optimized antibiotic therapy

is an intervention likely to improve treatment outcomes in severe sepsis [7].

Beta-lactam antibiotics display time-dependent activity where bacterial killing and treatment

efficacy correlates with fT>MIC [12]. Based on this characteristic, maximal beta-lactam effects are

considered more likely with CI rather than traditional IB dosing. IB dosing may produce beta-

lactam concentrations below the MIC for much of the dosing interval [13], particularly in the ICU

where pathogens with higher MIC values are relatively common [5].

Although CI has been shown to be superior to IB dosing in numerous pre-clinical and PK/PD

simulation studies [13], most clinical comparative trials have failed to demonstrate a clinical

advantage of CI dosing in terms of clinical cure and/or patient survival [151, 172, 248, 254, 256-

258, 266]. Meta-analyses of prospective studies have also not found any significant clinical benefits

favouring CI over IB dosing [217, 240, 267]. However, most of the studies recruited heterogeneous

patient groups and have important methodological flaws, potentially masking any possible benefits

of CI dosing in critically ill patients [217, 240]. Three recent RCTs have demonstrated some clinical

outcome advantages favouring CI administration of beta-lactam antibiotics when only critically ill

patients were recruited [166, 242, 243]. As most of the current evidence was derived from Western

countries, the wider applicability of CI dosing remains largely unexplored in some regions which

are plagued by more resistant pathogens and patients with higher levels of sickness severity [332].

Data from such areas, particularly from the South East Asian countries, are vital in order to support

a global practice change if subsequent studies identify CI benefits in critically ill patients. The

primary aim of the Beta-Lactam Infusion in Severe Sepsis (BLISS) study was to determine if CI of

beta-lactam antibiotics is associated with improved clinical outcomes compared to IB dosing in a

large cohort of critically ill patients with severe sepsis in a Malaysian ICU setting.

Findings of the BLISS study were presented, in part, at the 55th Interscience Conference on

Antimicrobial Agents and Chemotherapy (ICAAC), San Diego, CA, September 18-21, 2015 [414].

130

6.2.3 Methods

6.2.3.1 Study design

The BLISS study was a prospective, two-centre, open-labelled, RCT of CI versus IB dosing of beta-

lactam antibiotics in critically ill patients with severe sepsis from the two following Malaysian

ICUs: (1) Tengku Ampuan Afzan Hospital (HTAA), Kuantan; and (2) University Malaya Medical

Centre (UMMC), Kuala Lumpur. Institutional ethics approval was obtained at each participating

site. Written informed consent to participate in the study was obtained from each participant or their

legally-authorized representative prior to study enrolment. The study was registered with the

Malaysian National Medical Research Register (ID: NMRR-12-1013-14017).

6.2.3.2 Participants and randomization

ICU patients were eligible for inclusion if they met all of the following criteria: (a) adult (≥18

years); (b) developed severe sepsis (defined as presumed or confirmed infection with new organ

dysfunction) [24] in the previous 48 hours; (c) indication for cefepime, meropenem or

piperacillin/tazobactam with <24 hours therapy at time of assessment; (d) and expected ICU stay

greater than 48 hours. Patients were excluded if they: (a) were receiving RRT; (b) had impaired

hepatic function (defined as total bilirubin >100 µmol/mL); (c) were receiving palliative treatment;

(d) had inadequate central venous catheter access; (e) or death was deemed imminent.

Participants currently receiving, or about to receive, cefepime, meropenem or

piperacillin/tazobactam were randomly allocated to either a CI (intervention arm) or IB (control

arm) treatment arm. Randomization was performed using a computer program

(http://www.randomization.com) based on blocks of four with an allocation ratio of 1:1 stratified by

participating sites. Following study enrolment, an unblinded pharmacist on-duty who was

responsible for preparing medications, determined treatment allocation by opening sequentially-

numbered opaque, sealed and stapled envelopes. The tamper-evident envelopes were prepared by an

unblinded investigator and were provided to each participating site.

6.2.3.3 Intervention

Each antibiotic dose was prepared by an unblinded ICU pharmacist on-duty in accordance with

standard pharmacy practice. The dosing regimen was determined by the treating intensivist, with

guidance from a local dosing protocol (Table 6-1). To ensure early achievement of therapeutic beta-

http://www.randomization.com/

131

lactam exposures in the intervention arm, a single loading dose infused over 30 minutes was given

at initiation of antibiotic therapy meaning that the CI group received a larger antibiotic dose on Day

1 post-randomization compared to those in the IB arm (Table 6-1). The study antibiotic was

administered until, (a) the treating intensivist decided to cease the drug; (b) the participant withdrew

from the study; (c) ICU discharge; or (d) ICU death. All subsequent patient management including

addition of other antibiotics and non-study drugs was at the treating intensivist’s discretion.

Table 6-1: Antibiotic dosing protocol according to treatment arm in the BLISS study

Antibiotic and treatment arm Dosing regimen

Cefepime

Intervention arm

(continuous infusion)

Day 1: 2 g IV loading dose (infused over 30 minutes)

followed by 2 g IV (infused over 480 minutes) every 8

hours

Day 2 onwards: 2 g IV (infused over 480 minutes)

every 8 hours

Control arm

(intermittent bolus dosing)

2 g IV (infused over 30 minutes) every 8 hours

Meropenem

Intervention arm


Day 1: 1 g IV loading dose (infused over 30 minutes)

followed by 1 g IV (infused over 480 minutes) every 8

hours

Day 2 onwards: 1 g IV (infused over 480 minutes)

every 8 hours

Control arm


1 g IV (infused over 30 minutes) every 8 hours


Intervention arm


Day 1: 4 g/0.5 g IV loading dose (infused over 30

minutes) followed by 4 g/0.5 g IV (infused over 360

minutes) every 6 hours

Day 2 onwards: 4 g/0.5 g IV (infused over 360 minutes)

every 6 hours

Control arm


4 g/0.5 g IV (infused over 30 minutes) every 6 hours

Abbreviation: IV, intravenous.

132

6.2.3.4 Outcomes and measurements

The primary end-point investigated in this study was clinical cure at 14 days after antibiotic

cessation. Clinical cure was rated as either: (a) Resolution: complete disappearance of all signs and

symptoms related to infection; (b) Improvement: a marked or moderate reduction in disease severity

and/or number of signs and symptoms related to infection; or (c) Failure: insufficient lessening of

the signs and symptoms of infection to qualify as improvement, death or indeterminate for any

reason. Clinical cure was scored as a “Yes” for resolution and a “No” for all other findings (i.e.,

sum of 2 and 3 above). Secondary end-points investigated in this study include: (a) PK/PD target

attainment; (b) ICU-free days at day 28; (c) ventilator-free days at day 28; (d) survival at day 14; (e)

survival at day 30; and (f) time to WCC normalization. The definitions used to assess these end-

points are described in Table 6-2.

Table 6-2: Definitions used for primary and secondary clinical end-points

Primary end-pointa Definition and description

Clinical cure Clinical cure was evaluated at 14 days after cessation of study

antibiotic and was rated as:

1. Resolution: complete disappearance of all signs and

symptoms related to infection.

2. Improvement: a marked or moderate reduction in

disease severity and/or number of signs and symptoms

related to infection.

3. Failure: insufficient lessening of the signs and

symptoms of infection to qualify as improvement,

including death or indeterminate (i.e. no evaluation

possible, for any reason).

Clinical cure was scored as a “Yes” for resolution and a “No”

for all other findings (i.e., sum of 2 and 3 above).

Secondary end-pointsb,c,d Definition and description

PK/PD – 50% fT>MIC Free (unbound) drug concentration maintained above the MIC

of the causative pathogen for at least 50% of dosing interval

(i.e., mid-interval drug concentration). For CI participants, this

was the first sample taken over a 24-hour interval.

133

PK/PD – 100% fT>MIC Free (unbound) drug concentration maintained above the MIC

of the causative pathogen for at least 100% of dosing interval

(i.e., trough drug concentration or steady-state drug

concentration). For CI participants, this was the second sample

taken over a 24-hour interval.

ICU-free days at day 28 The number of days the participant was ICU-free after

successful transfer to a general ward in the first 28 days post-

randomization. ICU-free days were 0 if a patient died or stayed

in the ICU for ≥28 days.

Ventilator-free days at day 28 The number of days the participant was ventilator-free (for at

least 48 consecutive hours) in the first 28 days post-

randomization. Ventilator-free days were 0 if a patient died or

required mechanical ventilation for ≥28 days.

14-day survival Survival at day 14 post-randomization.

30-day survival Survival at day 30 post-randomization

Time to WCC normalization The number of days from randomization to the first identified

date when WCC was ≥4.0x109/L and ≤10.0x109/L (for at least

48 consecutive hours) in participants who had values outside

this range.

Abbreviation: CI, continuous infusion; ICU, intensive care unit; MIC, minimum inhibitory

concentration; PK/PD, pharmacokinetic/pharmacodynamic; WCC, white cell count.

Legend:

aClinical cure was evaluated by a blinded clinician if the participant was still in the ICU or by

blinded review of the medical records if the participant was discharged from the ICU.

bPharmacokinetic/pharmacodynamic (PK/PD) analysis only included participants with complete

pharmacokinetic data (i.e., those who had both trough and mid-interval concentrations collected on

both sampling days).

cPK/PD analysis was performed on Days 1 and 3 post-randomization.

dWhere a pathogen was isolated, the “surrogate MIC” was defined by the European Committee on

Antimicrobial Susceptibility Testing (EUCAST) MIC90 data. Where no pathogen was formally

identified, the MIC breakpoints for P. aeruginosa (8 mg/L for cefepime, 2 mg/L for meropenem

and 16 mg/L for piperacillin/tazobactam) were inferred as the “surrogate MIC”. Participants who

were infected with beta-lactam resistant pathogens were excluded from PK/PD analysis.

134

For the secondary end-point of PK/PD target attainment, assessment was made by comparing the

unbound (free) beta-lactam concentrations against the “surrogate MIC” of the pathogen. This MIC

was inferred from EUCAST database. PK/PD target attainment was evaluated as a dichotomous

variable and scored as a “Yes” if measured drug concentration exceeded pathogens “surrogate

MIC”. Only participants with complete PK data were included in the analysis (i.e., those who had

both trough and mid-interval drug concentrations collected on Days 1 and 3 post-randomization).

Participants who were infected with beta-lactam resistant pathogens were excluded from the PK/PD

analysis.

Independent investigators who were blinded to treatment allocation, patient care and management

assessed the end-points of interest. These investigators were not working in the participating ICUs

during this study.

Demographic, clinical and treatment-related variables were collected. Microbiological cultures were

collected from the most likely infection site immediately before or during antibiotic treatment. CLCR

was estimated using the Cockcroft-Gault formula [341]. APACHE II [340] and SOFA [52] scores

were calculated and recorded within 24 hours of ICU admission. Comorbidity was scored using the

Charlson comorbidity index [415]. Adverse events during the study period were recorded and

evaluated as “almost certainly”, “probably”, “possibly”, or “unlikely” to be caused by study

antibiotics [416]. Data were collected until participants were discharged from hospital or death.

6.2.3.5 Pharmacokinetic sampling and bioanalysis

PK sampling was coordinated by unblinded investigators and was performed on Days 1 and 3 post-

randomization. Blood (5 mL) was collected into lithium-heparinised tubes. For participants in the

IB arm, mid-dosing interval and trough concentrations were collected. For participants in the CI

arm, two blood samples were taken at least 12 hours apart. All blood samples were immediately

refrigerated at 4°C and within 1 hour, centrifuged at 3000 rpm for 10 minutes to separate plasma.

Plasma samples were frozen at -80°C within 24 hours of collection. Frozen plasma samples were

shipped on dry ice by a commercial courier and assayed at the BTCCRC, the University of

Queensland, Australia.

Beta-lactam concentration in plasma was measured, after protein precipitation, by a validated HPLC

method with ultraviolet detection [417], on a Shimadzu Prominence (Shimadzu Corporation, Kyoto,

Japan) instrument. Samples were assayed in batches, alongside calibration standards and quality

135

control replicates at high, medium and low concentrations. All bioanalysis techniques were

conducted in accordance with regulatory standards [342]. Observed concentrations were corrected

for protein binding using published protein binding values (20% for cefepime, 2% for meropenem

and 30% for piperacillin) [99].

6.2.3.6 Sample size calculations

A sample size of 120 participants (60 in each treatment arm) was estimated to demonstrate a

statistical significant difference in the primary end-point (power 0.8, alpha 0.05). For clinical cure,

75% of patients in the intervention arm versus 45% in the control arm were estimated to achieve

clinical cure [166]. The final study sample size was increased to 140 participants (70 in each arm)

factoring in a 15-20% drop-out rate.

6.2.3.7 Statistical analysis

Statistical analyses were primarily performed on the ITT population. A mITT analysis was also

performed in all participants who received at least one dose of study antibiotic. A per-protocol (PP)

analysis was performed in all participants who received study antibiotic for ≥4 days.

Data are presented as median values with IQR for continuous variables and number and percentage

for categorical variables. Differences in free plasma antibiotic concentration and free plasma

antibiotic concentration to MIC ratio in the ITT population were analysed using a Mann-Whitney U

test and are graphically presented as box (median and IQR) and whisker (10-99 percentile) plots.

Primary and secondary end-points were compared between the two treatment arms using a

Pearson’s chi-square test or a Mann-Whitney U test as appropriate. For the primary end-point, sub-

group analyses (determined a priori) were performed according to the study beta-lactams used,

concomitant antibiotic treatment, infection sites and A. baumannii or P. aeruginosa infection. For

ICU-free days and ventilator-free days, results are presented for ICU survivors. A Kaplan-Meier

survival curve was constructed to compare survival trends at Day 14 and Day 30 in the ITT

population. Comparison of survival between the two treatment arms was performed using a log-

rank test with the hazard ratio (HR) and 95% confidence interval reported. A multivariate logistic

regression was constructed to identify significant predictors associated with cure, with OR and 95%

confidence interval reported. Biologically-plausible variables with a p-value ≤0.15 on univariate

analysis were considered for model building. A two-sided p-value of <0.05 was considered

statistically significant in all analyses. Statistical analysis was performed using IBM SPSS Statistics

22 (IBM Corporation, Armonk, New York).

136

6.2.4 Results

6.2.4.1 Baseline demographics and clinical characteristics

Participants were recruited from April, 2013 to July, 2014. The sites enrolled 55 and 85

participants, respectively. Two hundred and twenty patients were assessed for eligibility of whom

140 were randomized and 134 received at least one dose of the study antibiotic. One hundred and

twenty-six participants received ≥4 days of randomized treatment. The BLISS study CONSORT

flow diagram is presented in Figure 6-1 and details that the most common reason for patient

exclusion was presence of RRT on assessment (n = 32). The baseline characteristics of the ITT

population are presented in Table 6-3.

Figure 6-1: The BLISS study CONSORT flow diagram

137

Table 6-3: Baseline demographic and clinical characteristics of the intention-to-treat

population

Characteristic Intervention

(n = 70)

Control

(n = 70)

Age (years) 54 (42-63) 56 (41-68)

Male, n (%) 46 (66) 50 (71)

Body weight (kg) 70 (59-80) 65 (59-75)

Body mass index (kg/m2) 27 (23-30) 24 (22-29)

APACHE II 21 (17-26) 21 (15-26)

SOFA 8 (6-10) 7 (5-9)

Charlson comorbidity index 3 (1-5) 4 (2-6)

Serum creatinine concentration (µmol/L) 111 (73-118) 92 (59-158)

Cockcroft-Gault creatinine clearance (mL/min) 64 (43-98) 72 (41-122)

Pre-randomization ICU stay (days) 2 (2-5) 3 (2-6)

Pre-randomization antibiotic therapy, n (%) 52 (74) 56 (80)

Pre-randomization appropriate antibiotic therapy, n (%)a 38 (79) 41 (73)

Post-randomization ICU stay (days) 8 (5-10) 6 (4-13)

Duration of randomized treatment (days) 7 (5-9) 7 (5-9)

Mechanically-ventilated, n (%) 66 (52) 61 (48)

Post-randomization renal replacement therapy, n (%) 15 (21) 12 (17)

White cell count (x 109/L) 17 (13-25) 15 (13-20)

Study antibiotic, n (%)

Piperacillin/tazobactam 38 (54) 47 (67)

Meropenem 21 (30) 21 (30)

Cefepime 11 (16) 2 (3.0)

Pharmacokinetic sampling, n (%)b

Piperacillin/tazobactam 35 (92) 37 (79)

Meropenem 19 (91) 17 (81)

Cefepime 9 (82) 2 (100)

Concomitant antibiotic, n (%) 33 (47) 33 (47)

Azithromycin 13 (19) 12 (17)

Vancomycin 6 (9) 12 (17)

Metronidazole 6 (9) 10 (6)

Clindamycin 2 (3) 4 (6)

Aminoglycosides 3 (4) 3 (4)

Colistin 1 (1) 1 (1)

Otherc 7 (10) 5 (7)


Lung 46 (66) 36 (51)

138

Intra-abdominal 11 (16) 15 (21)

Blood 4 (6) 6 (9)

Urinary tract 2 (3) 3 (4)

Skin or skin structure 6 (9) 7 (10)

Central nervous system 1 (1) 3 (4)

Organ dysfunction, n (%)

Respiratory 46 (66) 44 (63)

Cardiovascular 40 (57) 37 (53)

Hematologic 18 (26) 12 (17)

Renal 17 (24) 10 (14)

Metabolic acidosis 4 (6) 3 (4)

Abbreviation: APACHE, Acute Physiology and Chronic Health Evaluation; ICU, intensive care

unit; SOFA, Sequential Organ Failure Assessment.


Legend:

aAppropriate antibiotic therapy was assumed if a participant received at least one antibiotic (24

hours before study inclusion) which was effective against the isolated pathogen(s). Only

participants who had at least one organism identified was assessed (n = 104; intervention = 48,

control = 56).

bParticipants who had complete pharmacokinetic data i.e., those who had mid-dose and trough

concentrations on both sampling occasions.

cIncludes cloxacillin (n = 7), doxycycline (n = 2), co-trimoxazole (n = 2) and ciprofloxacin (n = 1).

139

The allocation of beta-lactam antibiotics was comparable between the treatment arms except for

cefepime where 11 participants were allocated to the intervention arm and only 2 to the control arm.

The median 24-hour antibiotic dose was not different between the intervention and control arms:

cefepime 6 g (IQR: 6-6) versus 6 g (2 participants), meropenem 3 g (IQR: 3-3) versus 3 g (IQR: 3-

3) and piperacillin/tazobactam 18 g (IQR: 18-18) versus 18 g (IQR: 9-18), respectively. The median

antibiotic treatment course was 7 days (IQR: 5-9) in both treatment arms. Thirty-three participants

(47%) in both treatment arms received concomitant antibiotic therapy as part of their treatment. The

median ICU stay was 8 days (IQR: 5-10) for participants in the intervention arm and 6 days (IQR:

4-13) in the control arm (p = 0.544). The median ventilator days were 6 (IQR: 3-7) and 5 (IQR: 3-

11) for participants in the intervention and control arms (p = 0.662), respectively. There was no

difference between the groups of proportion of patients with appropriate initial therapy.

Microbiological characteristics of the ITT population are shown in Table 6-4. Forty-eight

participants (69%) in the CI arm and 56 participants (80%) in the IB arm had at least one causative

pathogen identified before or during the course of treatment. Eighteen participants (34%) in the CI

arm and 26 participants (46%) in the IB arm had polymicrobial infections during the course of

treatment. The most prevalent Gram-negative pathogens in the intervention arm were P. aeruginosa

(37%) and A. baumannii (25%) and for the control arm, A. baumannii (31%) and Klebsiella

pneumoniae (23%). There were 9 participants (6%) who had a non-susceptible pathogen identified

as the primary causative organism: intervention arm 6 participants (9%) versus control arm 3

participants (4%). The median “surrogate MIC” values were similar in both treatment arms: 8 mg/L

(IQR: 4-8) for cefepime, 2 mg/L (IQR: 2-2) for meropenem, and 16 mg/L (IQR: 8-16) for

piperacillin/tazobactam.

140

Table 6-4: Microbiological characteristics of the intention-to-treat population

Characteristic Intervention

(n = 70)

Control

(n = 70)

Participants who had organisms identified, n (%) 48 (69) 56 (80)

Gram-positive, n (%) 12 (20) 25 (33)

Staphylococcus aureus 5 (42) 11 (44)

Staphylococcus epidermidis 4 (33) 6 (24)

Enterococcus faecalis 0 (0) 3 (12)

Streptococcus intermedius 1 (8) 2 (8)

Streptococcus pneumoniae 2 (17) 1 (4)

Mycoplasma pneumoniae 0 (0) 2 (8)

Enterococcus faecium 0 (0) 1 (4)

Streptococcus anginosus 0 (0) 1 (4)

Streptococcus constellatus 0 (0) 1 (4)

Gram-negative, n (%) 49 (80) 52 (68)

Acinetobacter baumannii 12 (25)a 16 (31)b

Pseudomonas aeruginosa 18 (37) 10 (19)

Klebsiella pneumoniae 9 (18)c 12 (23)

Escherichia coli 5 (10)d 5 (10)

Proteus mirabilis 2 (4) 2 (4)

Bulkholderia cepacia 1 (2) 1 (2)

Chlamydophila pneumoniae 0 (0) 2 (4)

Stenotrophomonas maltophilia 1 (2) 1 (2)

Bulkholderia pseudomallei 1 (2) 0 (0)

Enterobacter aerogenes 0 (0) 1 (2)

Morganella morganii 0 (0) 1 (2)

Serratia marcescens 0 (0) 1 (2)

Polymicrobial infection, n (%) 18 (38) 26 (46)

Legend:

aFour isolates were multi-drug resistant A. baumannii.

bThree isolates were multi-drug resistant A. baumannii.

cOne isolate was extended-spectrum beta-lactamase (ESBL) K. pneumoniae.

6.2.4.2 Outcome measures

Primary and secondary end-points in the ITT population and the clinical outcome for the sub-groups

of interest are presented in Table 6-5. Participants in the intervention arm had higher clinical cure

rates and shorter median time to WCC normalization. The number needed to treat with CI to

improve the likelihood of clinical cure is three patients. Additionally, CI administration

141

demonstrated higher clinical cure rates than IB dosing in participants who had respiratory infection,

participants who received piperacillin/tazobactam and in those without concomitant antibiotic

treatment (Table 6-5). Differences in PK/PD target attainment rates were significantly higher in the

intervention group at 100% fT>MIC on Day 1 and Day 3 post-randomization. At 28 days, there was

no difference in median ICU-free days but median ventilator-free days were significantly higher in

the participants of the intervention arm. There was no difference in survival at 14 days or 30 days

between the treatment arms (Figure 6-2).

Findings in the mITT and PP population were similar to those reported in the ITT population and

the primary and secondary end-points for these groups are presented in Tables 6-6 and 6-7.

6.2.4.3 Outcome measures predictors

Significant predictors associated with clinical cure in the ITT population are presented in Tables 6-8

and 6-9. Based on the most parsimonious logistic regression model, CI administration of beta-

lactam antibiotics (OR 3.21, 95% confidence interval 1.48-6.94; p = 0.003), pre-randomization

antibiotic therapy (OR 2.85, 95% confidence interval 1.12-7.23; p = 0.028), non-bacteraemia

related infection (OR 11.73, 95% confidence interval 1.30-105.94; p = 0.028), lower APACHE II

score (OR 0.95, 95% confidence interval 0.90-0.99; p = 0.036), and meropenem (OR 6.54, 95%

confidence interval 1.48-28.90; p = 0.013) or piperacillin/tazobactam administration (OR 4.21, 95%

confidence interval 1.06-16.64; p = 0.041) (as opposed to cefepime administration) were all

statistically significant predictors for clinical cure.

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Table 6-5: Primary and secondary end-points by treatment arm in the intention-to-treat population and the sub-groups of interest

Primary end-point Intervention

(n = 70)

Control

(n = 70)

Absolute difference

(95% CI)

Significance

(p-value)a,b

Clinical cure for ITT population, n (%) 39 (56) 24 (34) 22 (-0.4 to -0.1) 0.011

Clinical cure by antibiotic, n (%)c

Piperacillin/tazobactam 22 (58) 15 (32) 26 (-0.4 to -0.1) 0.016

Meropenem 14 (67) 8 (38) 29 (-0.5 to 0.1) 0.064

Cefepime 3 (27) 1 (50) 23 (-0.3 to 0.7) 1.000

Clinical cure by concomitant antibiotic treatment, n (%)d

Yes 14 (42) 13 (39) 3 (-0.3 to 0.2) 0.802

No 25 (68) 11 (30) 38 (-0.6 to -0.2) 0.001

Clinical cure by site of infection, n (%)e

Lung 27 (59) 12 (33) 25 (-0.4 to -0.1) 0.022

Clinical cure by A. baumannii or P. aeruginosa infection, n

(%)f

Yes 13 (52) 6 (25) 27 (-0.5 to 0.1) 0.052

No 10 (44) 12 (38) 6 (-0.3 to 0.2) 0.655

Secondary end-points Intervention

(n = 70)

Control

(n = 70)

Absolute difference

(95% CI)

Significance

(p-value)a,b

PK/PD target attainment, n (%)g

50% fT>MIC on day 1 56 (98) 49 (93) 5 (-0.2 to 0.1) 0.194

100% fT>MIC on day 1 55 (97) 37 (70) 27 (-0.4 to -0.1) <0.001

50% fT>MIC on day 3 56 (98) 49 (93) 5 (-0.2 to 0.1) 0.194

100% fT>MIC on day 3 55 (97) 36 (68) 29 (-0.4 to -0.1) <0.001

143

ICU-free days 20 (12-23) 17 (0-24) 3 (-4 to 1) 0.378

ICU survivorsh 21 (19-23) 21 (14-24) (-2 to 2) 0.824

Ventilator-free days 22 (0-24) 14 (0-24) 8 (-7 to 0) 0.043

ICU survivorsi 23 (21-25) 21 (0-25) 2 (-6 to 0) 0.076

14-day survival, n (%) 56 (80) 50 (71) 9 (-0.2 to 0.1) 0.237

30-day survival, n (%) 52 (74) 44 (63) 11 (-0.3 to 0.1) 0.145

WCC normalization days 3 (2-7) 8 (4-15) 5 (1 to 5) <0.001

Abbreviation: CI, confidence interval; ICU, intensive care unit; ITT, intention-to-treat; PK/PD, pharmacokinetic/pharmacodynamic; WCC, white cell

count; 50% fT>MIC, unbound (free) plasma concentration at 50% of the dosing interval (mid-interval concentration) was above the causative pathogens

MIC; 100% fT>MIC, unbound (free) plasma concentration at 100% of the dosing interval (trough concentration) was above the causative pathogens

MIC.

Legend:

aRepresents the p-value between the intervention arm versus the control arm and values in bold indicate significant difference between the two

treatment arms (p <0.05).

bContinuous variables were compared using Mann-Whitney U test as data were non-normally distributed as indicated by Kolmogorov-Smirnov test.


cNumber of participants analysed: (1) piperacillin/tazobactam (n = 85; intervention = 38, control = 47), (2) meropenem ( n = 42; intervention = 21,

control = 21), and (3) cefepime (n = 13; intervention = 11, control = 2).

dNumber of participants analysed: (1) patients who received concomitant antibiotics ( n = 66; intervention = 33, control = 33) and (2) patients who did

not receive concomitant antibiotics (n = 74; intervention = 37, control = 37).

eNumber of participants analysed: lung (n = 82; intervention = 46, control = 36).

fNumber of participants analysed: (1) A. baumannii or P. aeruginosa infection (n = 49; intervention = 25, control = 24) and (2) other infections (n =

55; intervention =23, control = 32).

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gOnly participants with complete pharmacokinetic data (n = 119; intervention = 63, control = 56) and those who were infected with beta-lactam

susceptible pathogens (n = 110; intervention = 57, control = 53) were included in the analysis.

hOnly participants who survived at ICU discharge was included in this sub-analysis (57 and 53 participants in the intervention and control arm,

respectively).

iOnly mechanically-ventilated participants who survived at ICU discharge was included in this sub-analysis (53 and 46 participants in the intervention

and control arm, respectively).

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Table 6-6: Primary and secondary end-points by treatment arm in the modified intention-to-treat population


(n = 68)

Control

(n = 66)

Absolute difference

(95% CI)

Significance

(p-value)a,b

Clinical cure for mITT population, n (%)

Clinical cure, n (%) 39 (57.4) 23 (34.8) 22.5 (-0.4 to -0.1) 0.009


(n = 68)

Control

(n = 66)

Absolute difference

(95% CI)

Significance

(p-value)a,b

PK/PD target attainment, n (%)c

50% fT>MIC on day 1 54 (98.2) 48 (94.1) 4.1 (-0.1 to 0.1) 0.350

100% fT>MIC on day 1 53 (96.4) 37 (72.5) 23.9 (-0.4 to -0.1) 0.001

50% fT>MIC on day 3 54 (98.2) 48 (94.1) 4.1 (-0.1 to 0.1) 0.350

100% fT>MIC on day 3 53 (96.4) 36 (70.6) 25.8 (-0.4 to -0.1) <0.001

ICU-free days 20 (11-23) 16 (0-23) 4 (-4 to 0) 0.287

ICU survivorsd 21 (19-23) 21 (12-24) 0 (-3 to 1) 0.565


ICU survivorse 23 (21-25) 20 (0-25) 3 (-6 to 0) 0.050

14-day survival, n (%) 54 (79.4) 47 (71.2) 8.2 (-0.2 to 0.1) 0.271

30-day survival, n (%) 50 (73.5) 42 (63.6) 9.9 (-0.2 to 0.1) 0.217

WCC normalization days 3 (2-7) 8 (4-15) 5 (1-5) <0.001

Abbreviation: CI, confidence interval; ICU, intensive care unit; mITT, modified intention-to-treat population; PK/PD,

pharmacokinetic/pharmacodynamic; WCC, white cell count; 50% fT>MIC, unbound (free) plasma concentration at 50% of the dosing interval (mid-

interval concentration) was above the causative pathogens MIC; 100% fT>MIC, unbound (free) plasma concentration at 100% of the dosing interval

(trough concentration) was above the causative pathogens MIC.

146

Legend:





cOnly participants with complete pharmacokinetic data (n = 115; intervention = 61, control = 54) and those who were infected with beta-lactam


dOnly participants who survived at ICU discharge was included in this sub-analysis (55 and 50 participants in the intervention and control arm,

respectively).

eOnly mechanically-ventilated participants who survived at ICU discharge was included in this sub-analysis (52 and 43 participants in the intervention


147

Table 6-7: Primary and secondary end-points by treatment arm in the per-protocol population


(n = 66)

Control

(n = 60)

Absolute difference

(95% CI)

Significance

(p-value)a,b

Clinical cure for PP population, n (%)

Clinical cure, n (%) 39 (59.1) 20 (33.3) 25.8 (-0.4 to -0.1) 0.004


(n = 66)

Control

(n = 60)

Absolute difference

(95% CI)

Significance

(p-value)a,b

PK/PD target attainment, n (%)

50% fT>MIC on day 1 54 (98.2) 42 (93.6) 4.6 (-0.2 to 0.1) 0.332

100% fT>MIC on day 1 53 (96.4) 34 (72.3) 24.1 (-0.4 to -0.1) 0.001

50% fT>MIC on day 3 54 (98.2) 42 (93.6) 4.6 (-0.2 to 0.1) 0.332

100% fT>MIC on day 3 53 (96.4) 34 (72.3) 24.1 (-0.4 to -0.1) 0.001

ICU-free days 20 (12-23) 17 (0-23) 3 (-4 to 0) 0.276

ICU survivorsd 21 (19-23) 21 (14-24) 0 (-3 to 1) 0.662


ICU survivorse 23 (21-25) 19 (1-25) 4 (-7 to 0) 0.027

14-day survival, n (%) 53 (80.3) 42 (70.0) 10.3 (-0.3 to 0.1) 0.180

30-day survival, n (%) 49 (74.2) 38 (63.3) 10.9 (-0.3 to 0.1) 0.186

WCC normalization days 3 (2-6) 8 (5-15) 5 (2 to 5) <0.001

Abbreviation: CI, confidence interval; ICU, intensive care unit; PK/PD, pharmacokinetic/pharmacodynamic; PP, per-protocol; WCC, white cell

count; 50% fT>MIC, unbound (free) plasma concentration at 50% of the dosing interval (mid-interval concentration) was above the causative pathogens

MIC; 100% fT>MIC, unbound (free) plasma concentration at 100% of the dosing interval (trough concentration) was above the causative pathogens

MIC.

148





cOnly participants with complete pharmacokinetic data (n = 110; intervention = 60, control = 50) and those who were infected with beta-lactam


dOnly participants who survived at ICU discharge was included in this sub-analysis (54 and 45 participants in the intervention and control arm,

respectively).

eOnly mechanically-ventilated participants who survived at ICU discharge was included in this sub-analysis (51 and 40 participants in the intervention


149

Table 6-8: Differences in clinical characteristics and treatment-related variables between participants who demonstrated clinical cure

and clinical failure in the ITT population

Variable Cure (n = 63) Failure (n = 77) p-valuea,b

Age (years) 55 (45-63) 53 (40-68) 0.774

Male, n (%) 46 (73.0) 50 (64.9) 0.306

Body weight (kg) 70 (56-80) 68 (60-75) 0.875

Body mass index (kg/m2) 25 (22-30) 25 (22-29) 0.793

APACHE II 19 (16-22) 23 (17-28) 0.009*

SOFA 7 (6-9) 8 (5-10) 0.695

Charlson comorbidity index 3 (2-5) 4 (2-6) 0.126*

Serum albumin (g/dL) 26 (21-30) 22 (17-28) 0.037*

Serum creatinine concentration (µmol/L) 94 (63-176) 120 (66-165) 0.697

Cockcroft-Gault creatinine clearance (mL/min) 68 (50-115) 59 (38-97) 0.268

Pre-randomization ICU stay (days) 2 (2-5) 3 (2-6) 0.580

Pre-randomization antibiotic therapy, n (%) 24 (28.1) 34 (44.2) 0.469

Pre-randomization appropriate antibiotic therapy, n (%) 34 (82.9) 45 (71.4) 0.180

Duration of randomized treatment (days) 7 (6-9) 6 (4-8) 0.040*

Mechanically-ventilated, n (%) 57 (90.5) 70 (90.9) 0.930

Post-randomization renal replacement therapy, n (%) 7 (11.1) 20 (26.0) 0.027*

Surgery within 24 hours of study inclusion, n (%) 24 (38.1) 34 (44.2) 0.469

White cell count (x 109/L) 16 (13-21) 16 (14-21) 0.769

Pre-randomization antibiotic therapy, n (%) 44 (69.8) 64 (83.1) 0.063*

Study antibiotic, n (%)

Piperacillin/tazobactam 37 (58.7) 48 (62.3) 0.357

Meropenem 22 (34.9) 20 (26.0)

Cefepime 4 (6.3) 9 (11.7)

150

Concomitant antibiotic use, n (%) 27 (42.9) 39 (50.6) 0.358

Treatment

Continuous infusion 39 (61.9) 31 (40.3) 0.011*

Intermittent bolus 24 (38.1) 46 (59.7)


Lung 39 (61.9) 43 (55.8) 0.469

Intra-abdominal 13 (20.6) 13 (16.9) 0.570

Blood 1 (1.6) 9 (11.7) 0.023*

Urinary tract 3 (4.8) 2 (2.6) 0.657

Skin or skin structure 6 (9.5) 7 (9.1) 0.930

Central nervous system 1 (1.6) 3 (3.9) 0.627

Organ dysfunction, n (%)

Respiratory 40 (63.5) 50 (64.9) 0.859

Cardiovascular 37 (58.7) 40 (51.9) 0.422

Hematologic 13 (20.6) 17 (22.1) 0.836

Renal 13 (20.6) 14 (18.2) 0.714

Metabolic acidosis 4 (6.3) 3 (3.9) 0.701

Participants who had organisms identified, n (%) 41 (65.1) 63 (81.8) 0.024*

Gram-negative infections, n (%) 35 (85.4) 45 (71.4) 0.099*

PK/PD ratio

Concentration at 50% of the dosing interval to MIC D1 5.8 (3.4-15.0) 6.5 (3.6-16) 0.547

151

Concentration at 100% of the dosing interval to MIC D1 4.5 (2.1-12.4) 4.7 (2.1-10.1) 0.823



Abbreviation: APACHE, Acute Physiology and Chronic Health Evaluation; ICU, intensive care unit; MIC, minimum inhibitory concentration;

PK/PD, pharmacokinetic/pharmacodynamic; SOFA, Sequential Organ Failure Assessment.


Legend:

aBold values indicate statistical significance (p <0.05).

bRepresents variable that was included in the multivariate logistic regression model.

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Table 6-9: Factors predicting clinical cure in the ITT population

Variable All factors included in the model Final model

Odds ratio

(95% CI)

Significance

(p-value)

Odds ratio

(95% CI)

Significance

(p-value)

Factors predicting clinical cure

Continuous infusiona 3.08 (1.38-6.94) 0.007 3.21 (1.48-6.94) 0.003

Bacteremiab 0.10 (0.01-0.92) 0.042 0.09 (0.09-0.770) 0.028

Pre-randomization antibiotic therapyc 2.74 (1.02-7.32) 0.045 2.85 (1.12-7.23) 0.028

APACHE II score (per 1-point increase) 0.95 (0.90-1.00) 0.060 0.95 (0.90-0.99) 0.036

Study drugd 0.075 0.047

Piperacillin/tazobactam 4.15 (1.01-17.01) 0.049 4.21 (1.06-16.64) 0.041

Meropenem 6.04 (1.28-28.47) 0.023 6.54 (1.48-28.90) 0.013

Cefepime 1.0 - 1.0 -

Causative organism identifiede 0.54 (0.22-1.33) 0.180 - -

Duration of randomized treatment (per 1-day increase) 1.04 (0.98-1.09) 0.208 - -

Albumin (per 1 g/dL increase) 1.02 (0.96-1.08) 0.597 - -

Charlson comorbidity index (per 1-point increase) 0.98 (0.85-1.13) 0.781 - -

Goodness-of-fit


Abbreviation: APACHE, Acute Physiology and Chronic Health Evaluation; CI, confidence interval; df, degree of freedom; X2, chi-square.

*Bold values indicate statistical significance (p <0.05).

Legend:

aOR compares continuous infusion relative to IB dosing of beta-lactam antibiotics.

bOR compares bacteraemia relative to other sites of infections.

cOR compares those who received pre-randomization antibiotic therapy relative to those who did not.

153

dOR compares piperacillin/tazobactam and meropenem relative to cefepime.

eOR compares those who had at least one causative organism identified relative to those who did not.

154

6.2.4.4 Pharmacokinetic/pharmacodynamic data

The data describing free (unbound) plasma antibiotic concentration and free (unbound) plasma

antibiotic concentration to MIC ratio are presented in Figures 6-2 and 6-3, respectively. Plasma

antibiotic concentrations measured at 50% and 100% of the dosing interval were relatively higher in

the intervention group on Day 1 and Day 3 post-randomization (Figure 6-2). The ratio of plasma

antibiotic concentration to MIC was also relatively higher in the intervention group on both

sampling days for all study antibiotics (Figure 6-3).

Figure 6-2: Free plasma antibiotic concentration by beta-lactam antibiotics and treatment

groups measured at (a) 50% of the dosing interval on Day 1 (b) 100% of the dosing interval

on Day 1 (c) 50% of the dosing interval on Day 3 and (d) 100% of the dosing interval on Day 3

Abbreviation: CI, continuous infusion; IB, intermittent bolus.

*Median, interquartile range and range are presented.

**An asterisk indicates a significant difference between continuous infusion and intermittent bolus

dosing (p <0.05).

155

Figure 6-3: Free plasma antibiotic concentration to minimum inhibitory concentration (MIC)

ratio by beta-lactam antibiotics and treatment groups measured at (a) 50% of the dosing

interval on Day 1 (b) 100% of the dosing interval on Day 1 (c) 50% of the dosing interval on

Day 3 and (d) 100% of the dosing interval on Day 3

Abbreviation: CI, continuous infusion; IB, intermittent bolus.

*Median, interquartile range and range are presented.

**An asterisk indicates a significant difference between continuous infusion and intermittent bolus

dosing.

***PK/PD ratio is defined as the ratio between the measured plasma antibiotic concentration at

50% or 100% of the dosing interval and the causative pathogen’s “surrogate MIC” (i.e., not actual

MIC values), as defined in Table 6-2. Note that a ratio of 1 at 100% of the dosing interval is

generally considered to be a minimum PK/PD target during beta-lactam therapy.

6.2.4.5 Adverse events

No adverse events occurred during study participation. A total of 18 deaths occurred during receipt

of the study drug: CI arm 7 participants versus IB arm 11 participants.

156

6.2.5 Discussion

In this RCT, we found that continuous beta-lactam infusion demonstrated higher clinical cure rates

and better PK/PD target attainment compared to IB dosing in critically ill patients with severe

sepsis. Other significant benefits for CI participants in two other surrogate clinical end-points were

increased ventilator-free days and a reduced time to WCC normalization. Given that these results

were derived from a population of ICU patients with severe sepsis, who were not on extra-corporeal

renal support, our findings provide further evidence that CI of beta-lactam antibiotics are likely to

be beneficial for patients with a high level of illness severity not receiving RRT. Although three

recent RCTs have also reported similar findings [166, 242, 243], our current work remains unique

considering that we recruited patients from a different geographical region, one which is rarely

investigated but commonly associated with higher illness severity, than those commonly reported.

Clinical evidence supporting improved patient outcome with CI of beta-lactams has been mixed,

varying from no significant effect [151, 172, 241, 256-258] to significant patient benefits [166, 242,

243, 248, 254, 266]. We would note that there is yet to be a report suggesting inferior patient

outcomes when CI is used. Meta-analyses of the above prospective clinical studies have failed to

comprehensively demonstrate the superiority of CI over IB dosing in terms of clinical cure and

patient survival [217, 240, 267]. However, a particularly noteworthy feature in most of these studies

has been the inclusion of non-critically ill patients, whereas the patients who may be most likely to

benefit from CI dosing are critically ill patients with high illness severity [166, 242]. Critically ill

patients, particularly those with severe sepsis, commonly develop extreme physiological

derangements, which may severely reduce antibiotic exposure, particularly when IB dosing is

employed [7, 291]. Patients that received beta-lactams via CI dosing in our study were ten-times

more likely to achieve 100% fT>MIC on Day 1 (p <0.001) and nine-times more likely to achieve

100% fT>MIC on Day 3 (p <0.001). As maintaining 100% fT>MIC in critically ill patients is associated

with improved patient outcomes [28], we believe that the observed clinical cure difference in the

ITT analysis (absolute difference of 22%) favouring CI dosing may be partly explained by the

relative ability of CI dosing to achieve the target PK/PD exposure more consistently than IB dosing

in patients with severe sepsis [164, 291]. Importantly, CI participants in this study were three-times

more likely to achieve clinical cure when compared with IB participants, even after controlling for

confounding variables (OR 3.21, 95% confidence interval 1.48-6.94; p = 0.003).

Significant advantages of CI over IB for beta-lactam antibiotics were also observed in two recent

RCTs of critically ill patients with severe sepsis. In a prospective, multicentre, double-blind, RCT

157

(BLING I; n = 60), Dulhunty et al., [166] showed that participants in the CI treatment arm

demonstrated greater fT>MIC (82% versus 29%; p = 0.001) and higher clinical cure rates (77%

versus 50%; p = 0.032) compared to the IB arm. In a single-centre RCT which recruited 240

critically ill Czech participants, Chytra et al., [242] reported higher microbiological cure rates in the

CI treatment arm as opposed to the IB arm (91% versus 78%; p = 0.020). Neither study

demonstrated significant mortality advantages.

Despite these results, disease severity is only one of the many variables which can influence the

outcome of CI versus IB dosing in critically ill patients. This was recently highlighted in a

multicentre, double-blind, RCT (BLING II; n = 420) [241]. Despite recruiting only patients with

severe sepsis, Dulhunty et al., found no significant difference between participants in both treatment

arms, in all five clinical end-points evaluated. In their study, the absolute difference in clinical cure

between CI and IB participants was 3% in favour of CI dosing compared with the 22% in the

present BLISS study. In contrast to BLISS, the BLING II trial included patients receiving RRT

(~25% of participants) and this inclusion criterion may reduce PK/PD exposure differences between

CI and IB dosing because patients with reduced drug clearances are less likely to manifest sub-

therapeutic antibiotic exposures [244, 245] and consequently, are less likely to benefit from altered

dosing approaches such as CI administration. Interestingly, all five clinical studies which

demonstrated patient benefits with CI dosing only recruited critically ill patients with conserved

renal function [166, 242, 243, 248, 254].

Other than recruiting participants with a low burden of disease, most clinical studies have also

isolated pathogens which are highly susceptible to the study antibiotics [166, 172, 241-243, 248,

254, 256-258, 266]. PK/PD principles states that IB dosing will be just as likely as CI to achieve

target exposures when MICs are low [13] with treatment failures more likely with IB dosing when

less susceptible pathogens are present [151, 290, 293]. In the present study, although actual MIC

values were not available, 41% of the causative pathogens were either A. baumannii or P.

aeruginosa which mostly have higher MICs to the study antibiotics [418], thereby reducing the

likelihood of achieving therapeutic concentrations with IB dosing. However, it should also be

highlighted that benefits of CI may not be apparent in some geographical regions with different

microbiology and antibiotic resistance patterns. Importantly, use of combination therapy to treat

infections caused by Gram-negative pathogens was infrequent in this study, which may differ from

practices in other centres.

158

This study has several limitations. Participants were only recruited from two centres in one country

which may limit the generalizability of the findings to other treatment settings. Despite the baseline

characteristics of the treatment arms being relatively well balanced, CI participants manifested

higher median SOFA scores on admission compared to IB participants. Even though this typically

translates into a reduced likelihood of survival, it is possible that CI participants may have been

selectively provided with additional monitoring in the ICU to account for their illness severity,

which may influence clinical outcomes. Furthermore, clinical outcomes were evaluated by an

independent investigator and unlike a specialized review committee, the former strategy may be

more likely to introduce biased observations towards one of the treatment allocations. However, the

possibility of bias in this study should be very low as the assessor had no knowledge of treatment

allocation now role in patient management and was not working in the participating centres during

the study period. We also acknowledge the limitation of the Cockcroft-Gault formula in estimating

renal function in this cohort, and that measured CLCR would be more accurate [419]. Neither

unbound plasma concentrations nor concentrations at the sites of infections were measured in this

study, although all drugs have relatively low protein binding [99]. As MIC reporting is rare in

Malaysia, we have used “surrogate MIC” values, using EUCAST MIC breakpoints, in our primary

end-point analyses. Accordingly, this approach will exaggerate the magnitudes of PK/PD target

non-attainment in the IB treatment arm relative to the CI arm if actual MIC values were used.

Although actual MIC values would have been preferable, we believe that our approach resembles

the real-life clinical approach where the MIC of a pathogen is rarely available upon antibiotic

commencement [27]. Although data on concomitant antibiotics were available, we did not evaluate

the PK/PD of those antibiotics. This study was not powered to test the effect of CI versus IB dosing

on survival but has provided useful information that can be used for sample size determination of a

larger multicentre RCT seeking to quantify any survival benefits of CI dosing.

6.2.6 Conclusion

In critically ill patients with severe sepsis not receiving RRT, CI administration was associated with

higher clinical cure rates and better PK/PD target attainment compared to IB dosing for three

common beta-lactam antibiotics. Our findings suggest that beta-lactam CI may be most beneficial

for critically ill patients with a high level of illness severity, who are infected with less susceptible

microorganisms and that are not receiving RRT. A large-scale, prospective, multinational clinical

study is required to ascertain whether the potential benefits of continuous beta-lactam infusion do

indeed translate into survival benefit in critically ill patients with severe sepsis.

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6.3 Conclusion

The findings in this chapter showed that CI of beta-lactam antibiotics demonstrated higher clinical

cure rates and better PK/PD target attainment as opposed to IB dosing in a large cohort of critically

ill patients with severe sepsis. Furthermore, data from the BLISS study further corroborates data

from previous studies which suggest that CI may not improve outcomes for all critically ill patients,

but only certain sub-populations. Based on the findings presented in this chapter, CI of beta-lactam

antibiotics are likely to be advantageous for critically ill patients with a high level of illness severity

who are not receiving RRT. Additionally, this alternative dosing strategy may improve the

outcomes from severe infections which are more likely to be associated with less susceptible

pathogens. Although the BLISS study was not powered to investigate survival benefit between the

two dosing approaches, its data provides useful information that can be used for the design of a

large-scale, prospective, multinational RCT to ascertain whether the perceived benefits of CI do

indeed translate into mortality reduction in critically ill patients with severe sepsis.

160

Chapter 7: Optimizing antibiotic treatment in critically ill patients via

pharmacokinetic/pharmacodynamic principles

7.1 Synopsis

The patterns of antibiotic resistance have significantly changed over the last few decades with

increasing antibiotic resistance currently being regarded as one of the major health crises.

Organisms such as E.coli and K. pneumoniae, which were previously considered relatively

innocuous, are frequently becoming resistant to currently available antibiotics and therefore,

treating these infections has become a challenge for clinicians world-wide. Furthermore, it was

predicted that these worrying trends of increasing resistance will continue to progress with the

biggest threats arising from Gram-negative pathogens. The rate at which these pathogens develop

resistance is likely to far outpace the rate of development of new antibiotics. Abuse and overuse of

antibiotics in hospitals, particularly in the ICU, has caused a dramatic increase in antibiotic

resistance and this phenomenon currently threatens to shorten the clinical life-span of the existing

antibiotic armamentarium. Clinicians now are forced to find new methods that optimize the use of

presently available antibiotics. Although more commonly explored to maximize patient outcomes,

emerging data are suggesting that the PD-based dosing approach is equally crucial to prevent the

emergence of resistance by avoiding sub-optimal antibiotic dosing. The aims of this chapter are to

describe the relevance of PK/PD characteristics of different antibiotic classes on the development of

antibiotic resistance and to suggest alternative treatment strategies that can be employed not only to

maximize patient outcomes but also to minimize the emergence of resistance.

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7.2 Manuscript entitled “Applying pharmacokinetic/pharmacodynamic

principles in critically ill patients: optimizing efficacy and reducing resistance

development”

The manuscript entitled “Applying pharmacokinetic/pharmacodynamic principles in critically ill

patients: optimizing efficacy and reducing resistance development” has been accepted for

publication in the Seminars in Respiratory and Critical Care Medicine (2015; 36(1): 136-153).



Jason A. Roberts, Prof. Jeffrey Lipman and Prof. Johan W. Mouton. Literature review was


Roberts, Prof. Johan W. Mouton and Prof. William W. Hope. The PhD candidate took the leading

role in manuscript preparation and all co-authors reviewed and contributed to the final draft of the

manuscript.





Permission has been granted by the publisher and copyright owner, Thieme, to reproduce the

manuscript in this Thesis.

162

Applying pharmacokinetic/pharmacodynamic principles in critically ill patients: optimizing

efficacy and reducing resistance development

Authors

Mohd H. Abdul-Aziz (1), Jeffrey Lipman (1, 2), Johan W. Mouton (3, 4), William W. Hope (5),

Jason A. Roberts (1, 2, 5).

Affiliation

(1) Burns, Trauma & Critical Care Research Centre, The University of Queensland, Brisbane,

Australia.

(2) Department of Intensive Care Medicine, Royal Brisbane & Women’s Hospital, Brisbane,

Australia.

(3) Department of Medical Microbiology, Radboud University, Nijmegen Medical Centre,

Nijmegen, The Netherlands.

(4) Department of Medical Microbiology and Infectious Diseases, Erasmus MC, Rotterdam, The

Netherlands.

(5) Department of Molecular and Clinical Pharmacology, University of Liverpool, Liverpool,

United Kingdom.

Keywords: antibacterial; resistance; pharmacodynamics; pharmacokinetics.



Burns, Trauma & Critical Care Research Centre,

The University of Queensland,


4029 Butterfield Street, Brisbane, Queensland,

Australia.

Ph: +61736464108; Fax: +61736463542



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7.2.1 Abstract

The recent surge in MDR pathogens combined with the diminishing antibiotic pipeline has created a

growing need to optimize the use of our existing antibiotic armamentarium, particularly in the

management of ICU patients. Optimal and timely PK/PD target attainment has been associated with

an increased likelihood of clinical and microbiological success in critically ill patients. Emerging

data, mostly from in vitro and in vivo studies, suggest that optimization of antibiotic therapy should

not only aim to maximize clinical outcomes but to also include the suppression of resistance. The

development of antibiotic dosing regimens that adheres to the PK/PD principles may prolong the

clinical lifespan of our existing antibiotics by minimizing the emergence of resistance. This present

article summarizes the relevance of PK/PD characteristics of different antibiotic classes on the

development of antibiotic resistance. Based on the available data, we propose dosing

recommendations that can be adopted in the clinical setting, in order to maximize therapeutic

success and limit the emergence of resistance in the ICU.

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7.2.2 Introduction

Severe infections leading to severe sepsis and septic shock are prominent causes of morbidity and

mortality in critically ill patients. In a large multicentre point prevalence study involving 1265 ICUs

across 75 countries, 51% of ICU patients were classified as infected on the day of study with a

mortality rate of 25.3% [31]. Data from a large European ICU study has further corroborated the

diagnosis of severe sepsis as a global healthcare crisis, whereby the condition accounted for 26.7%

of ICU admissions [33]. In this study, the corresponding mortality in patients with severe sepsis and

septic shock were concerning with rates of 32.2% and 54.1%, respectively [33]. Despite an

emerging trend for improved survival over recent years [29, 30, 32], the mortality rate in this patient

cohort remains unacceptably high worldwide [1]. In the context of the financial burden incurred, the

United States itself is currently spending between $121 and $263 billion annually on critically ill

patients, which represents more than 8% of the country’s total healthcare expenditure [46].

To address these persisting poor patient outcomes, significant amounts of research have been

directed towards optimizing the provision of care for the critically ill patient. Indeed improving

antibiotic therapy is a core focus of treatment of infection-driven pathologies like sepsis. There is

strong evidence to suggest that optimal antibiotic therapy may have a greater impact on patients’

survival when compared to novel treatment strategies such as the use of activated protein C [408],

antithrombin III [420], and intensive insulin therapy in these patients [4, 421-423]. However, the

process of optimizing antibiotic therapy can be a daunting challenge in the ICU for a variety of

reasons. Extreme physiological derangements that can occur from either pharmacological

interventions or the natural course of critical illness may alter antibiotic concentrations and

consequently reduce antibiotic exposure in critically ill patients [6]. In addition, pathogens that are

usually isolated in the ICU differ from the general wards, as they are commonly less susceptible to

common antibiotics [334, 335]. Indeed, antibiotic dosing that does not account for these features is

likely to lead to sub-optimal antibiotic exposure and therapeutic failures. In addition, sub-optimal

antibiotic exposure is also highly implicated as a contributing factor to the escalation of antibiotic

resistance. Resistance to antibiotics certainly is considered a global healthcare crisis which currently

threatens the advances of modern medicine [148].

The recent surge in MDR pathogens combined with the diminishing antibiotic pipeline has created a

growing need to optimize the use of the existing antibiotic armamentarium, particularly in the ICU.

Although critically ill patients constitute fewer than 10% of all hospital admissions, their antibiotic

consumption is 10-times greater compared to patients in all other wards [383, 424, 425]. The

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rampant antibiotic use (or misuse) has therefore, in part, contributed to the alarming increase in the

MDR pathogens such as the ESBL and carbapenemase-producing Gram-negative pathogens.

Notably, Gram-negative pathogens such as A. baumannii and P. aeruginosa, as well as members of

the Enterobacteriaceae family such as E. coli and K. pneumoniae, which were previously considered

relatively innocuous, have impressively out-manoeuvred our current antibiotics. Previously simple

infections have become increasingly difficult to treat over a short period of time [399]. Moreover,

infections caused by these pathogens frequently result in poor clinical outcomes, including higher

mortality and prolonged hospitalization [426-428]. The healthcare community concerns are

legitimate, as the emergence of resistance is likely to far outpace the rate of development of new

antibiotics. In light of these grim prospects, clinicians are currently forced to reintroduce older

antibiotics as treatment options (e.g., colistin and fosfomycin) and vigorously search for new

strategies that can optimize the use of our presently available antibiotics.

The aim of this review is to describe the relevance of PK exposure and PD characteristics of

different antibiotic classes on the development of antibiotic resistance. We will discuss the relevant

antibiotic resistance descriptors and review how target drug exposures differ between predicting

treatment success and suppressing resistance development. Based on the current data, we will also

suggest dosing strategies that ultimately exploit antibiotic PD, which increase the likelihood of

treatment success as well as minimizing the emergence of resistance.

7.2.3 Applied clinical pharmacology of antibiotics

Pharmacology is the science of drugs including the study of drug actions. Two principle areas of

pharmacology are PK and PD. Traditionally, antibiotic dosing and administration were only

optimized, in accordance to the PK/PD principles, for clinical efficacy (i.e., clinical and

microbiological cure) with an associated collateral damage being the selection of resistant

pathogens. Emerging data are suggesting that the PD-based dosing approach should not only aim to

maximize clinical outcomes but to also include the suppression of resistance. Indeed, the

application of PK/PD principles have been shown to minimize the risk of emergence of resistance

by avoiding ineffective antibiotic exposure, which consequently exerts a selective pressure to

pathogens, rather than to eradicate them [149]. This selective pressure causes the elimination of

highly susceptible, but not the more resistant phenotypes, leading to future colonization and

potential infection with poorly susceptible pathogens.

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7.2.3.1 Pharmacokinetic considerations

PK refers to the study of concentration changes of a drug over a given time period. This branch of

pharmacology describes the rates and processes from absorption to distribution of drugs to

elimination mechanism via metabolism or excretion. Some of the examples of important PK

parameters are; (a) Vd, (b) CL, (c) Cmax, (d) Cmin and, (e) AUC0-24. Among these however,

alterations in the primary PK parameters, namely Vd and CL, are probably the most influential in

determining altered antibiotic dosing and exposure. Changes in antibiotic Vd and CL have been

commonly observed in critically ill patients and the relevance of the two phenomena in influencing

effective antibiotic exposure has been reviewed in detail elsewhere [7].

7.2.3.2 Pharmacodynamic considerations

PD describes the relationship between PK exposure and pharmacological effect. For antibiotics, PD

relates the antibiotic concentration to the ability of an antibiotic to kill or inhibit the growth of a

pathogen. Generally, this relationship is often described by linking the concentration of an antibiotic

with the corresponding MIC of the offending pathogen. For an antibiotic, it is the free or unbound

concentration that is responsible for the antibacterial activity [429]. Numerous studies have

demonstrated that different antibiotics have different PD properties and can be readily categorized

as the following; (a) fT>MIC, (b) Cmax/MIC and, (c) AUC0-24/MIC. These fundamental PK/PD indices

for antibiotics’ activity are further illustrated in Figure 7-1. It should be noted, that the AUC/MIC

was never considered in earlier studies, and that many data retrieved from older literature only

established the relationship between Cmax/MIC and effect parameter. From a theoretical point of

view most of the antibiotics should show a relationship with AUC and effect rather than Cmax.

Based on the PK/PD indices, antibiotics can be classified into three categories that by and large

reflect their modes of bacterial killing [12, 24, 430]. The first category includes antibiotics where

the difference between the maximum effect and minimum effect is relatively large, and increasing

concentrations result in progressively increased killing. These are therefore also sometimes called

concentration dependent antibiotics, and include aminoglycosides and quinolones. For these

antimicrobials AUC/MIC describes their antibiotic activity best, and, mainly because AUC/MIC is

closely correlated to Cmax/MIC, Cmax/MIC as well [386, 431]. On the other hand, time-dependent

antibiotics’ activity, such as the beta-lactams, is strongly correlated with fT>MIC and as such,

prolonging the duration of effective drug exposure should be the priority when this antibiotic class

is used [11, 28]. However, some antibiotics such as the glycopeptides are more complex where they

are found to display both concentration- and time-dependent kill characteristics [11]. For these

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Figure 7-1: The graphical illustration of fundamental pharmacokinetic and pharmacodynamic parameters of antibiotics on a hypothetical

concentration-time curve

Abbreviation: AUC, area under the concentration-time curve; Cmax, maximum drug concentration; Cmin, minimum drug concentration; MIC,

minimum inhibitory concentration; T>MIC, duration of time that drug concentration remains above MIC.

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antibiotics, the ratio of AUC0-24/MIC describes their antibiotic activity best and higher thresholds

are closely related with successful clinical outcome [432].

7.2.4 Pharmacokinetic/pharmacodynamic considerations and the resistance

descriptors

Most of the earlier research on optimizing antibiotic dosing was only focused on maximizing

clinical and microbiological cure and not minimization of the emergence of antibiotic resistance. To

date, most of the data describing PK/PD and its association with antibiotic resistance comes from

pre-clinical, albeit advanced, PK/PD infection models. However, the antibiotic exposure required

for clinical efficacy and resistance suppression is markedly different. For instance, the antibiotic

exposure-response relationship for clinical efficacy is monotonic or can also be described as a

sigmoidal relationship in which, no measurable antibiotic effect is expected at lower drug exposures

whilst larger exposures are expected to augment the bactericidal effect up to a certain threshold. In

contrast, the relationship between antibiotic exposure and the selection of resistant mutants is

markedly non-monotonic and has the shape of an inverted “U” where resistant mutants are

amplified with initial antibiotic exposure and then slowly decline with increasing exposure up to an

optimal threshold that ultimately prevents resistance amplifications [433-436]. The inverted U-

shape seems to follow a log normal distribution [437]. Additionally, Jumbe et al., found that an

AUC0-24/MIC of ≥110 for levofloxacin, which was twice that was necessary for optimal bactericidal

effect, was required to suppress drug-resistant population of P. aeruginosa in a mouse-thigh

infection model [401]. This information, among other similar observations, has indicated that the

magnitude of the PK/PD indices for resistance suppression is generally different and higher than the

thresholds required for clinical success [405, 434, 438, 439]. Therefore, antibiotic dosing that only

aims to optimize clinical efficacy may potentially amplify resistance formation by selecting mutant

bacterial strains with reduced drug susceptibility. With enhanced knowledge on antibiotic PK/PD

over recent years, important hypotheses and concepts, such as the mutant selection window (MSW)

and mutant prevention concentrations (MPC), have been proposed to provide potential explanations

as to how sub-optimal antibiotic exposure may amplify the selection of resistant bacterial strains.

Additionally, the dynamics of bacterial population under various dosing regimen can be described

using mixture models, where changes in susceptible and resistant sub-populations in relation to

drug concentrations are quantified [401, 435, 438, 440, 441].

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7.2.4.1 Mutant selection window

The term “selective window” (SW) which was firstly coined by Baquero [442, 443] refers to a

critical range of antibiotic concentrations in which drug-resistant bacterial mutants could be

selectively enriched and amplified when exposed to concentrations in this zone. Subsequent in vitro

studies, utilizing mycobacteria treated with fluoroquinolones, were able to define the boundaries for

the critical zone of antibiotic concentrations and this concept was later renamed as the MSW [444-

446]. The studies that attempted to describe MSW further suggested that these concentration zones

are those between the MIC of the susceptible pathogens and that of the least susceptible mutants.

Figure 7-2 graphically illustrate the concept of MSW and its relevance in the development of

resistant mutants. The MSW describes the range of antibiotic concentrations where resistant

mutants may be selectively amplified and these concentration zones are those between the MIC of

the susceptible pathogens and that of the least susceptible mutants i.e., MPC. In area (A) of Figure

7-2, which is below the MIC, no resistant mutants are expected to grow, as there is no selective

pressure in this area. In area (C) of Figure 7-2, which is above the MPC, the growth of resistant

mutants is severely restricted and highly unlikely as the exposure in the area is able to suppress the

growth of the least susceptible pathogens. On the contrary, the selection of resistant mutants would

be most intense in area (B) of Figure 7-2, which is also known as MSW. Conversely, the longer the

time spent by an antibiotic in this concentration zone, the greater the opportunity for resistant

mutants to be selected and amplified. In addition to this, the formation of the resistant mutants was

observed to be most intense in the bottom portion as opposed to the upper portion of the selection

window [447]. The existence of such “dangerous” concentration zones was further corroborated by

several in vitro [436, 448-450] and in vivo experimental studies [451-454].

The MSW hypothesis is potentially important, as contemporary antibiotic dosing tends to produce

drug concentrations within the critical zone where they selectively amplify the growth of resistant

mutants. Essentially, the higher the percentage of time (t) spent by an antibiotic within the MSW

(tMSW), the greater the opportunity for resistant mutants to be selected and amplified. Furthermore,

the continuous and prolonged “careless” practice of “dosing to only cure” in the ICU eventually

leads to the resistant mutants being the dominant bacterial population and it is only at this point that

surveillance studies would be alerted to the emergent resistant isolates. The MSW has been defined

for many of the fluoroquinolones and some of the beta-lactams against various microorganisms

[455-457]. Nevertheless, this concept is currently considered as a relatively new idea and has not

been investigated in many infective pathologies, nor its relevance at the site of infection. Hence, its

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clinical relevance in optimizing antibiotic dosing to avoid the MSW remains unclear and warrants

further investigation.

Figure 7-2: Graphical illustration of the mutant selection window and mutant prevention

concentration on a hypothetical concentration-time curve

Abbreviation: Cmax, maximum drug concentration; Cmin, minimum drug concentration; MIC,

minimum inhibitory concentration; MPC, mutant prevention concentration; MSW, mutant selection

window.

7.2.4.2 Mutant prevention concentration

The concept of MPC, which was derived from the MSW hypothesis, refers to the antibiotic

concentration that corresponds to the MIC of the least susceptible mutants in a colony [444, 446].

While MIC refers to the lower boundary, the MPC essentially represents the upper boundary of

concentrations in the MSW in which the enrichment of resistant mutants are expected to be severely

hindered. Conversely, antibiotic dosing that aims to achieve concentrations higher than the MPC, as

opposed to MIC, theoretically provides both an optimal bactericidal effect as well as resistance

suppression. Furthermore, the ratio of AUC0-24 to MPC (AUC0-24/MPC) as opposed to AUC0-24/MIC

is also suggested as a predictor of the development of resistance in several in vitro and in vivo

evaluations as MIC quantifications generally ignore mutant sub-populations [433, 455, 458, 459].

The argument has been mostly tested in in vitro studies for fluoroquinolones where the mutant-

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restrictive thresholds of AUC0-24/MPC were approximately one-third of those AUC0-24/MIC values

[436, 460].

The MPC has been described mostly for fluoroquinolones, although data for other classes of

antibiotics are emerging [455, 461, 462]. Quantifying MPC thresholds for individual antibiotics

should be one of the priorities in the development of dosing guidelines especially earlier in the

process of evaluation and screening of new compounds. Although the concept seems appealing, the

application however is not straightforward as the doses needed to achieve the MPC are usually

higher than those for curing patients and exceed those that are registered for those antibiotics. There

are also examples where these concentrations are unattainable for some antibiotic-pathogen

combination [445, 462]. In addition, a trade-off between an increased risk of adverse effects with

minimizing antibiotic resistance is a difficult consideration in clinical practice. In such cases,

combining two or three antibiotics with overlapping PD properties may be warranted.

7.2.4.3 Application of experimental mixture models

A mixture models examine resistance development by describing the population dynamics of

antibiotic-susceptible and -resistant bacteria during the course of treatment. Susceptible and

resistant sub-populations respond differently to different antibiotic concentrations. In a murine-

thigh infection model, Jumbe et al., investigated the impact of bacterial inoculum on the required

levofloxacin exposure in the eradication of total P. aeruginosa population [401]. The mice were

inoculated with either 107 or 108 bacteria per thigh and levofloxacin was initiated after 2 hours. The

investigators demonstrated that the exposure intensity which is required for maximal levofloxacin

activity increases (by 2-5 fold) as the size of the inoculum increases by 1-log. This phenomenon

occurs as a larger bacterial challenge constitutes larger population of resistant mutants, which are

less susceptible to antibiotic therapy. The investigators also employed a complex mathematical

model to analyse their findings simultaneously in order to calculate an exposure that would amplify

resistant population and also, exposure that would restrict the enrichment of the population. A free

AUC/MIC ratio of 110 and 36 was predicted to prevent the emergence and amplify resistant P.

aeruginosa mutants in the study, respectively.

7.2.5 Specific antibiotic classes

This section discusses individual antibiotic classes and their pharmacodynamic characteristics,

which influence antibiotic activity and the prevention of resistance. The relevant PD indices that

have been shown to correlate with both outcomes are presented in Table 7-1.

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7.2.5.1 Quinolones

Quinolones are mostly lipophilic antibiotics and display largely concentration-dependent kill

characteristics but with some time-dependent effects. Previous in vitro studies have shown that the

achievement of a Cmax/MIC ratio of at least 8-12 is important for its optimal bactericidal activity

[463, 464]. Given the half-life of most quinolones, this corresponds to AUC0-24/MIC values that

correlate to efficacy. More importantly however, is that the index has also been associated with the

reduction of resistant mutants in several experimental studies [389, 465, 466].

Several studies found that the ratio of AUC0-24/MIC is important for its bactericidal effect, as an

even more significant index as compared to the Cmax/MIC ratio, and a ratio of ≥125 and ≥30 has

been advocated for clinical success in the treatment of Gram-negative and -positive infections,

respectively [389, 467-471]. In the context of antibiotic resistance, an inverse relationship has been

described between this index and the probability of developing resistance [402]. Accordingly,

quinolone dosing regimens that ensure higher ratios of AUC0-24/MIC are currently recommended to

maximize bactericidal exposure as well as minimizing the development of resistance [401, 402,

435]. Several investigators have further elucidated the critical AUC0-24/MIC thresholds as being

between >100 to 200 in order to suppress the formation of resistant mutants when these antibiotics

are used for Gram-negative infections [401, 402, 472]. However, due to intrinsic differences

between various quinolones in selecting resistant strains, the suggested AUC0-24/MIC ratio for

resistance suppression may vary between individual agent [389, 473].

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Table 7-1: Optimal pharmacokinetic/pharmacodynamic indices for antibiotic activity and the magnitudes associated with maximal therapeutic outcomes and resistance suppressiona

Antibiotic class Optimal PK/PD index PK/PD magnitude for bacterial killingb PK/PD magnitude for clinical efficacyc Optimal PK/PD index for

resistance suppression

PK/PD magnitude for

resistance suppressiond

Aminoglycosides AUC0-24/MIC AUC0-24/MIC: 80-160

[229, 474, 475]

AUC0-24/MIC: 50-100

[476]

Cmax/MIC Cmax/MIC ≥20

[477]

Cmax/MIC -

Cmax/MIC ≥8

[431, 461, 478]

Cmax/MIC ≥30

[477]

Penicillins T>MIC ≥40-50% T>MIC

[11, 12]

≥40-50% T>MIC T>MIC ≥40-50% T>MIC

[457]

Cephalosporins T>MIC ≥60-70% T>MIC

[11, 12]

≥45-100% T>MIC

[20, 21]

tMSW ≤40% tMSW

[479]

Carbapenems T>MIC ≥40% T>MIC

[11]

≥50-75% T>MIC

[25, 152]

T>MIC ≥40% T>MIC

[480]

tMSW ≤45% tMSW

[481]

Fluoroquinolones AUC0-24/MIC AUC0-24/MIC: 30-200

[430, 470, 471]

AUC0-24/MIC: 35-250

[389, 467-469]

AUC0-24/MIC AUC0-24/MIC: 100-200

[401, 435]


[463, 464, 466]

Cmax/MIC ≥8

[474]


[465]

AUC0-24/MPC AUC0-24/MPC ≥22

[455]

tMSW ≤30% tMSW

[448, 450, 454, 482]

Vancomycin AUC0-24/MIC AUC0-24/MIC: 86-460

[11]

AUC0-24/MIC: 400-600

[11, 483]

AUC0-24/MIC AUC0-24/MIC: 200

[448]

Linezolid AUC0-24/MIC AUC0-24/MIC: 50-80

[484]

AUC0-24/MIC ≥80

[485] - -

T>MIC ≥40% T>MIC

[484, 486]

≥85% T>MIC

[485] - -

Daptomycine AUC0-24/MIC AUC0-24/MIC: 388-537

[487] -

AUC0-24/MIC AUC0-24/MIC: 200

[448]

Cmax/MIC Cmax/MIC: 59-94

[487] - - -

Fosfomycin Unknown - - - -

Colistin AUC0-24/MIC AUC0-24/MIC: 50-65

[488, 489] - - -

Abbreviation: AUC0-24/MIC, ratio of area under the concentration-time curve during a 24-hour period to minimum inhibitory concentration; Cmax/MIC, ratio of maximum drug concentration to minimum inhibitory

concentration; T>MIC, duration of time that drug concentration remains above the minimum inhibitory concentration during a dosing interval; tMSW, percentage of time spent by an antibiotic within the mutant selection

window; AUC0-24/MPC, ratio of area under the concentration-time curve during a 24-hour period to the concentration that prevents mutation.

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Legend:

aAll values refer to the non-protein bound, free fraction except when indicated otherwise.

bData have been summarized from in vivo animal studies and may utilize different infection models employing different bacteria. Where the index is reported as a range, specific data for the contributing indices, which may

have been derived from different studies, can be found in the associated references. The data also reflect the 2-log kill and in some cases 1-log kill which may or may not coincide with maximum kill.

cData have been summarized from clinical studies and may recruit different patient population. Where the index is reported as a range, specific data for the contributing indices, which may represent PK/PD thresholds for

clinical or microbiological cure, can be found in the associated references.

dData have been summarized from pre-clinical studies, which may include in vitro and in vivo experimental infection models employing different bacteria. Specific data for the contributing indices can be found in the

associated references.

eValues reported here refer to total drug concentration.

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The AUC0-24/MPC index is also being investigated and the advantages over AUC0-24/MIC in the

prediction of resistance development have been documented in several in vitro studies [455, 458,

459]. To date, this remains a controversial argument as most authors found that both indices were

similar in their predictive potentials of resistance development [452, 490]. Nevertheless, higher

ratios of AUC0-24/MPC are associated with minimizing the emergence of resistance.

Recently, increasing interest and efforts have been focused on the application of MSW concept in

the evaluation of quinolones dosing regimens. Based on the current data, tMSW of ≤30% should

restrict mutant amplification and the index has been studied in several in vitro [450, 482] and in

vivo studies [452, 456]. Khachman et al., further extended this concept into clinical practice by

investigating the appropriateness of the currently recommended ciprofloxacin dosing in 102

critically ill patients [491]. Using Monte Carlo simulations, the PTA (i.e., ≤20% tMSW) for the

currently recommended ciprofloxacin dosing regimens (i.e., 800 mg or 1200 mg/daily) was less

than 50% and when higher doses such as 2400 mg/daily were used, only minor improvements were

observed i.e., PTA of 61%. More importantly, the risk of selecting resistant A. baumannii and P.

aeruginosa strains were extremely high with the recommended regimens thus challenging their

appropriateness in critically ill patients. As it stands, a quinolone-dosing regimen that maximizes

the AUC0-24/MIC ratio should be considered in critically ill patients and by citing ciprofloxacin as

an example; the objective may be achieved with a 400 mg 8-hourly or 600 mg 12-hourly regimen.

When treating pathogens with high MICs, dose escalation should be considered whilst being

observant of possible dose-related adverse effects occurrence.

7.2.5.2 Aminoglycosides

Aminoglycosides are hydrophilic in nature and they demonstrate concentration-dependent kill

characteristics [431, 492]. Although previous studies have mainly suggested that achieving a high

Cmax/MIC ratio predicts optimal outcome [229, 386, 474, 478, 493], Craig et al., argued that the

ratio of AUC0-24/MIC would be more appropriate in describing the antibiotic’s activity [11]. In the

1980s, Moore et al., [386] suggested that an aminoglycoside dose that provided a Cmax/MIC ratio of

8-10 was associated with a higher probability of clinical success against Gram-negative infections.

However, the investigators chose the index due to their sparse PK sampling times and consequently,

AUC0-24/MIC ratio was not considered in the study. Importantly, high collinearity existed between

Cmax and AUC. Several investigators have since suggested that the ratio of AUC0-24/MIC is more

likely to be a “better” PD descriptor for aminoglycosides activity [430, 476], in which an AUC0-

24/MIC ratio of 80-160 has been advocated for its efficacy [475, 476].

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Although higher concentrations enhance aminoglycoside activity, prolonged exposure of such

concentrations may lead to drug toxicity as well as the development of bacterial resistance. This

type of resistance is known as adaptive resistance and is characterized by a slow but reversible,

concentration-independent killing [494-496]. Maximizing the Cmax/MIC ratio seems to reduce the

development of adaptive resistance and the objective is likely achieved with extended-daily dosing

(EDD) as opposed to the traditional dosing schemes (i.e., twice or thrice daily dosing) [496]. In a

PD model designed to predict aminoglycosides activity against A. baumannii and P. aeruginosa,

Tam et al., further quantified the required Cmax/MIC ratio to prevent the resistance development

[477]. In this study, a Cmax/MIC ratio of 20 for a once-daily amikacin dosing regimen and 30 for a

12-hourly gentamicin dosing regimen was required for suppressing A. baumannii and P. aeruginosa

regrowth, respectively. Based on these results, it could be then inferred that the Cmax/MIC ratio and

AUC0-24/MIC are the PD indices to consider in order to suppress A. baumannii and P. aeruginosa

resistant mutants, respectively.

Based on the available data, EDD rather than the traditional multiple daily dosing of

aminoglycosides is currently advocated in an attempt to maximize their therapeutic potential and

minimize resistance development. Furthermore, it has been shown in numerous clinical studies

[497, 498] and several meta-analyses [499, 500] that the dosing recommendation is indeed

appropriate and valid in reducing aminoglycosides toxicity and may increase the likelihood of

successful treatment outcomes. Clinical data on these dosing effects on development of resistance

remains sparse.

7.2.5.3 Beta-lactams

The beta-lactam antibiotics are made up of penicillins, cephalosporins and monobactams and

carbapenems but the latter will be considered separately in the section below because of their

different spectrum and PD properties. Beta-lactam antibiotics are generally hydrophilic in nature

and display time-dependent kill characteristics. The fT>MIC is regarded as the optimal PD index for

their activity and as such, maintaining effective drug exposure above the MIC should be the priority

when this antibiotic class is used [12]. It has been generally suggested that % fT>MIC required for

bactericidal effect is 50%, 60-70% and 40% for penicillins, cephalosporins and carbapenems,

respectively [22, 393, 501]. Additionally, relatively higher fT>MIC exposures are needed for maximal

activity against the Gram-negatives as opposed to the Gram-positive pathogens. However, clinical

data from critically ill patients have not consistently supported these targets. Some data suggest that

these in vitro exposures to be the minimum antibiotic exposures required, with patients potentially

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benefitting from higher and longer antibiotic exposures than those previously described in in vitro

and in vivo studies [20, 21, 25, 27, 28, 152]. It has also been demonstrated that maximal bactericidal

activity occurs when drug concentrations are maintained at 4-5 x MIC, with higher concentrations

providing little added benefit [23, 26, 152]. Therefore, it has been suggested that beta-lactam

concentrations should be maintained at least 4-5 x MIC for extended periods during each dosing

interval to ensure clinical success, particularly in severely ill patients [13].

It is still inconclusive whether the fT>MIC index predicts beta-lactams resistance although the

potential link has been described in several in vitro [405] and in vivo experimental studies [404,

457]. Fantin et al., utilized an in vivo animal model to suggest that the development of resistance

against ceftazidime might arise should the drug concentration fall below the MIC for more than half

of the dosing interval [404]. The risk of developing resistance against a cephalosporin has also been

linked to a low AUC0-24/MIC ratio [502]. This was further demonstrated by Stearne et al., who

found that an AUC0-24/MIC of 1000 was required with ceftizoxime to prevent the emergence of

resistant Enterobacter cloacae strains [437]. In another murine lung infection model, Goessens et

al., found that the growth of resistant E. cloacae strains was correlated with prolonged ceftazidime’s

tMSW [479].

Based on the limited data on resistance suppression, beta-lactams dosing that targets concentrations

greater than 4 x MIC for extended periods would be most appropriate [503]. Importantly, research

has shown that the objective can be obtained via frequent dosing or by utilizing EI or CI. However,

the altered dosing schemes may potentially drive the emergence of resistance with sub-optimal

dosing, at least in theory, as these approaches tend to increase beta-lactams tMSW. In a recent in

vitro hollow-fibre infection model (HFIM) of P. aeruginosa, Felton et al., suggested that EI of

piperacillin/tazobactam was equivalent to IB dosing in terms of the bactericidal effect and the

prevention of resistance [504]. However, the target concentration for the two approaches should be

different in which the ratio of Cmin/MIC of 10.4 and 3.4 was required by EI and IB to suppress

resistant mutants, respectively.

7.2.5.4 Carbapenems

Generally, carbapenems have similar PK/PD characteristics when compared to other beta-lactam

antibiotics. Some studies have suggested that unlike other beta-lactams, carbapenems possess a

PAE against Gram-negative bacilli, including P. aeruginosa strains [157] although this could not be

confirmed in another study [505]. This PAE property of carbapenems may explain a shorter %

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fT>MIC for optimal bactericidal activity. Li et al., further quantified the % fT>MIC as >54% in order to

achieve optimal microbiological outcome when meropenem is used in patients with lower

respiratory tract infections [23]. Additionally, only a ratio of Cmin/MIC of >5 was significantly

associated with clinical and microbiological cure in this cohort of patients. Further, Tam et al., used

an in vitro HFIM to demonstrate that a Cmin/MIC of >6.2 was required to suppress the development

of resistant P. aeruginosa mutants [405]. The finding was later corroborated by the same group of

investigators in a neutropenic mouse infection model and in this current analysis, % fT>MIC of >40%

was also associated with the selection of resistant mutants [480]. More recently in an in vitro

dynamic model simulating doripenem concentrations, Zinner et al., found that resistant P.

aeruginosa mutants were likely to be selected at drug concentrations that fell ≥45% within the

MSW (≥45% tMSW) [481].

Similar to the other beta-lactam antibiotics, maintaining carbapenem concentrations at 4-6 x MIC

for extended periods is currently advocated to suppress resistant mutants selection. To achieve this

objective, prolonging the duration of infusion is generally recommended when the antibiotic is

used. However, EI as opposed to CI is the currently preferred dosing method when carbapenems are

used considering the group’s inherent drug instability in aqueous solutions. With increasing

information and emerging data, clear distinction, in the context of stability problems, needs to be

emphasized between the different members of the carbapenem group. Whilst imipenem is indeed

less stable, there are currently no practical reasons to oppose continuous meropenem infusion as it

has been successfully administered up to 8 hours (under hospital environment) in numerous clinical

studies without drug instability or degradation reports [86, 276, 506]. In an in vitro HFIM

examining cell-kill and resistance suppression for three P. aeruginosa strains, Louie et al.,

demonstrated that a doripenem dosing regimen of 1 g infused over 4 hours was the solitary regimen

that was able to completely suppress resistance for the full period of 10 days for wild-type isolates

[507]. Importantly, the investigators also reported that the dosing regimen produces concentrations

at >6.2 x MIC which were significantly associated with maximal resistance suppression in other

evaluations [405, 481]. In addition, Chastre et al., also observed lower occurrence of resistant P.

aeruginosa strains arising in patients treated with EI of doripenem when compared to patients who

received conventional imipenem dosing in a multicentre, RCT of critically ill patients with VAP

[336].

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7.2.5.5 Vancomycin

Vancomycin is a glycopeptide antibiotic and is a relatively hydrophilic drug. Some in vitro [508,

509] and in vivo animal studies [510] suggest that the bactericidal activity of the antibiotic is time-

dependent whereas some have shown the ratio of Cmax/MIC to be equally important [511]. More

recently, it has been generally accepted that achieving a high ratio of AUC0-24/MIC would be more

predictive of its clinical success. Studies by Moise-Broder et al., were the earliest to quantify that a

ratio of AUC0-24/MIC of ≥400 is needed for an optimal bacteriological and clinical outcome when

treating patients with S. aureus respiratory infections [432, 512]. The findings are consistent with

Zelenitsky et al., retrospective data evaluation and the investigators also described that higher

exposures are needed, specifically a ratio of AUC0-24/MIC of ≥578, when treating critically ill

patients with septic shock [483]. Due to common clinical practice of measuring trough

concentrations when vancomycin is used, a trough concentration ranging between 15-20 mg/L is

recommended for optimal outcome in hospital-acquired pneumonia and complicated infections

[513, 514].

Although scarce data exist, it could be assumed that the development of resistance is linked to sub-

optimal vancomycin exposure. Through their in vitro PD model, Tsuji et al., was able to conclude

that the development of vancomycin-intermediately susceptible S. aureus (VISA) strains was driven

by sub-optimal vancomycin exposure in the setting of dysfunctional agr locus in S. aureus [515].

Additionally, the investigators also found that the AUC0-24/MIC ratio needed to suppress resistance

for the strains was four-fold higher than that in the parent strains. Charles et al., observed that

patients with VISA infections were more likely to present with low vancomycin trough

concentrations (i.e., <10 mg/L) [516]. Based on similar findings to Charles et al., retrospective data

evaluation [517, 518], and considering the recommended trough concentrations for successful

clinical outcomes in severe infections, vancomycin trough concentrations should also be maintained

between ≥15-20 mg/L at all times to suppress resistance emergence [513]. Thus, loading doses of

25-30 mg/kg should be considered in critically ill patients to rapidly attain the target concentration

and certainly, higher vancomycin doses of up to 40 mg/kg may be important to minimize resistance

development. In addition, doses in excess of 5 g/daily were estimated to be necessary to achieve the

target AUC0-24/MIC ratio when treating VISA infections [107]. Increasing knowledge of the

relationship between higher vancomycin exposures and drug toxicities may limit the dosing of this

drug to limit the emergence of resistance.

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7.2.5.6 Linezolid

Linezolid belongs to a class of antibiotics known as oxazolidinones, which was developed for the

treatment of Gram-positive infections. In a murine infection model, Andes et al., demonstrated that

optimal linezolid activity correlates well with the ratio of AUC0-24/MIC, with a ratio of between 50

and 80 predicting the likelihood of successful treatment outcome [484]. However, higher clinical

success rates may occur at AUC0-24/MIC ratio of 80-120 for bacteraemia, lower respiratory tract

infections and skin structure infections as reported by Rayner et al., in their retrospective clinical

PD evaluation of 288 patients [485]. Importantly, the investigators also showed that the drug

exposure required for optimal treatment outcome was also dependent on the site and types of

infection. Additionally, the probability of treatment success appeared likely when linezolid

concentrations were maintained above the MIC for the entire dosing interval. The finding

corroborated two earlier rabbit endocarditis experimental models, which described linezolid as a

time-dependent antibiotic where an fT>MIC of 40% is needed for optimal antibiotic activity [484,

486]. A 600 mg 12-hourly dose is currently suggested to achieve these PD indices and hence,

predicts successful treatment outcome. However, it is also imperative to emphasize that the

antibiotic’s PK is highly variable [429, 505, 519-521], particularly in patients with severe

infections, and the phenomenon has, in part, contributed to treatment failures as well as the

increased occurrence of adverse events in such patients [485, 522]. As such, TDM of linezolid is

beneficial in this respect and emerging data are suggesting that general TDM may optimize patient

outcomes when linezolid is used in critically ill patients. In the context of antibiotic resistance, low

dose linezolid (200 mg 12-hourly) has been associated with the development of E. faecium and E.

faecalis resistant strains [523]. In addition, prior exposure and prolonged linezolid administration

have been suggested to increase the likelihood of resistance development [524-526]. Nevertheless,

the development of resistance against the antibiotic has not been widely reported [527, 528].

7.2.5.7 Daptomycin

Daptomycin is the first approved member of the cyclic lipopeptides with a potent activity against

Gram-positive pathogens including methicillin-resistant S. aureus (MRSA) and vancomycin-

resistant enterococci (VRE). In vivo experimental studies describe daptomycin to be a

concentration-dependent antibiotic. The ratio of Cmax/MIC in concert with AUC0-24/MIC has been

correlated with its efficacy in several in vivo animal studies [487, 529, 530]. Safdar et al., used a

neutropenic murine thigh infection model to characterize the PD characteristics of the antibiotic

[487]. In the infection model, the Cmax/MIC and AUC0-24/MIC ratio required for bacteriostasis

ranged from 59-94 and 388-537 (total drug concentration), respectively. Similar ratios were

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required for bacteriostasis in two other clinical studies, which recruited healthy volunteers [531,

532]. Based on these suggested indices, optimal daptomycin exposure could be expected in most

patients with modest dosing (4-6 mg/kg per day). However, the emergence of daptomycin-resistant

strains has been reported with such dosing regimens [533, 534] and some experts recommend the

use of higher dosing to curb this issue (i.e., 8-12 mg/kg per day) [535], which was shown to be safe

in one retrospective data evaluation [536] and several case reports [537, 538]. A duration of therapy

exceeding 2 weeks has also been documented to increase the likelihood of daptomycin resistance

[534].

7.2.5.8 Fosfomycin

Fosfomycin, which was discovered more than 40 years ago but then forgotten, is a phosphonic acid

derivative that possesses promising in vitro activity against carbapenem-resistant K. pneumoniae

[539]. The introduction of fosfomycin into our current armamentarium of antibiotics was greeted

with some scepticism due to major setbacks in its initial in vitro evaluation and this has in part,

contributed to its limited acceptance for clinical use. Although there are suggestions that

fosfomycin’s bacterial killing appears to be driven by fT>MIC, the optimal PK/PD index relating to

its activity remains to be established and requires further investigations [540]. In addition, rapid

bacterial killing was observed in several static-time kill studies when drug concentrations were

maintained at 2-8 x MIC. Similar to the beta-lactams, the development of fosfomycin resistance is

driven by low drug exposures and prolonged duration of antibiotic course [541]. There has also

been some debate concerning the rapid development of fosfomycin resistance when it is used as a

monotherapy particularly in non-urinary tract infections. In a murine endocarditis model, Thauvin et

al., found that the combination of fosfomycin and pefloxacin was more effective in suppressing

resistant S. aureus strains emergence when compared to fosfomycin alone [542]. In several in vitro

and in vivo experimental studies, instances of synergism were also demonstrated against MRSA

when fosfomycin was combined with the beta-lactams [543, 544], linezolid [545], and moxifloxacin

[546]. Combining fosfomycin with beta-lactams is also strongly supported by in vitro data, which

describe synergism between the two antibiotics against P. aeruginosa infections [547-549].

However, whether the in vitro synergism would translate to increased clinical efficacy remains to be

demonstrated. In a recent prospective study, fosfomycin, in combination with colistin, gentamicin

or piperacillin/tazobactam, provided promising bacteriological and clinical outcome data in the

treatment of 11 critically ill patients with ICU-acquired infections caused by carbapenem-resistant

K. pneumoniae [550]. Based on limited clinical data in treating serious infections in the ICU and its

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high tendency for developing resistance, fosfomycin should not be used as a single agent and the

choice of adjunctive antibiotic should be appropriately evaluated in future studies.

7.2.5.9 Colistin

Colistin is a polymyxin antibiotic, which is administered parenterally as colistin methanesulfonate

(CMS). The antibiotic has concentration-dependent kill characteristics with a significant in vitro

PAE against Gram-negative pathogens [551]. In vivo murine studies suggested that the most

predictive PD index for its bacterial activity, particularly against A. baumannii and P. aeruginosa, is

AUC0-24/MIC [552, 553]. Based on observations in several lung infection models, the ratio of

AUC0-24/MIC between 50 and 65 has been suggested as the optimal PD target although higher

exposures were also described in thigh infection models [488]. The heteroresistance phenomenon,

the situation whereby resistant sub-populations are present within a strain considered susceptible

based on MIC, is an emerging problem for the antibiotic and has been observed in clinical isolates

of A. baumannii [489, 554], K. pneumoniae [555], and P. aeruginosa [556]. Further to this, rapid

resistant mutants formation was demonstrated following colistin exposure in two recent in vitro

PK/PD studies mimicking clinical dosing regimens in humans [557, 558]. This is particularly

worrying as Garonzik et al., suggested that the currently recommended CMS dosing regimen is sub-

optimal in a population PK analysis of 105 critically ill patients [559] and their findings were

corroborated by other investigators who recruited smaller number of patients [560, 561]. With

increasing PK knowledge on the drug, Garonzik et al., [559] and Plachouras et al., [561] further

described optimized CMS dosing regimens in patients with varying degrees of renal function. The

dosing proposed by Plachouras et al., [561] has now been validated in a critical care setting by

Dalfino et al., [562] in the treatment of MDR infections. Among the relevant recommendations

concerning CMS dosing is the need for an initial loading dose as the conversion of the prodrug

CMS to the active entity of colistin is very slow and adequate colistin exposure may be delayed for

a few days. Although theoretically plausible based on its PD characteristics, the adoption of EDD is

not suitable on the basis of the resultant prolonged periods of low colistin concentrations leading to

the formation of heteroresistance [552, 553, 557]. Based on current PK data of critically ill patients

[559-561, 563, 564] and in vivo PK/PD experimental studies [552, 553] colistin monotherapy would

not be beneficial in maximizing therapeutic success and preventing resistance, particularly in

patients with moderate-to-good renal function and for pathogens with MICs of ≥1. In addition, a

treatment course lasting more than 12 days has been found to be associated with the development of

colistin resistance in two recent clinical studies [565, 566].

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7.2.6 Modifying treatment approaches to prevent emergence of resistance

7.2.6.1 Combination antibiotic therapy

Although combining antibiotics is common during the treatment of infection, the relevance of the

practice has been the matter of debate with conflicting conclusions. Proponents of combination

therapy will strongly suggest that the approach will increase antibiotic exposure via extending

coverage across a wider range of potential pathogens and in some clinical evaluations, has been

found to improve survival in severely ill patients [567-570]. Further strong theoretical reasons to

seriously consider a combination antibiotic approach include; antibiotic synergism which enhances

killing potency; combined activity against biofilm-growing pathogens; increasing tissue

penetration; inhibition of pathogen’s toxin and enzyme production; and prevention of resistance

development. However, there is also clinical evidence indicating that combination therapy may not

be superior, even harmful in some instances [571-573], as opposed to monotherapy in the treatment

of Gram-negative bacilli infections [574-576]. Based on the current data, it could be deduced that

combination antibiotic therapy may not benefit all patients but rather a select patient population

with select infections. While monotherapy may be sufficient for most patients, critically ill patients

with severe infections may benefit the most from rationally optimized combination therapy.

Although some in vitro infection models [577, 578] and animal studies [579] clearly indicated

benefits behind the approach, unfortunately, the vast majority of combination schemes were chosen

randomly without considering the pre-clinical findings [580].

In the context of resistance suppression, rationally optimized combination therapy may restrict the

amplification of resistant mutants. Epstein et al., [581] suggests that the presence of more than two

antibiotics at the infection loci (with drug concentrations above the MIC), each with a different

killing mechanism, would “shut” the MSW and thereby suppressing mutant growth [582-584].

Apart from several pre-clinical studies [448, 577, 579, 585, 586], no RCTs to date have shown that

the approach reduces the emergence of resistance. Furthermore, the benefit is particularly difficult

to be demonstrated in clinical evaluations, which frequently recruit heterogeneous patient

population and are not conducted long enough to detect the emergence of resistance. In the face of

rapidly evolving resistance phenomenon, it is likely that we have to turn our attention to the concept

of rationally optimized combination antibiotic therapy, particularly in the treatment of severely ill

patients in the ICU. In addition, the approach is likely to be important early in the course of

infection when the inoculum of the infecting pathogens is the highest.

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7.2.6.2 Duration of therapy

It has been increasingly shown in pre-clinical studies that prolonged antibiotic administration may

play an important role in the formation of resistant mutants. Conversely, the longer antibiotic

therapy persists, the more challenging it is to curtail the emergence of resistant pathogens. It has

been suggested that an antibiotic regimen that lasts for only 4-5 days should be sufficient to produce

maximal bactericidal effect with an added benefit of resistance suppression. Extending antibiotic

exposure to more than 10 days is risky on the basis of resistance development whereby higher drug

exposures are needed to suppress resistant mutants in this situation and if this threshold is not

achieved, treatment failure ensues as the resistant population dominates. This phenomenon has been

described by Tam et al., in their in vitro model of S. aureus infection which investigated two

garenoxin dosing regimens with different intensity; one with an AUC0-24/MIC ratio of 280 and the

other with 100 [438]. The investigators demonstrated that once the duration of garenoxin exposure

increased beyond 5 days, the magnitude of dosing needed for suppressing resistant mutants also

increased. The higher dosing regimen was found to suppress resistance amplification for 10 days

whilst the less intense regimen was only able to demonstrate the ability for 4-5 days.

At best, the common practice of administering an antibiotic for 10-14 days is currently based on

limited data and expert opinion rather than it being an evidence-based approach. However, for some

deep-seated infections such as osteomyelitis and endocarditis, prolonged antibiotic courses are

essential. Instances of potential benefits from shortening the duration of antibiotic therapy in

reducing the emergence of resistance while maintaining clinical efficacy have been increasingly

described [587-590]. Among these findings, Singh et al., demonstrated that patients who received

shortened antibiotic courses (i.e., ≤3 days) had reduced ICU stays, lower superinfection and

resistance rates as well as lower mortality rates compared to patients who received standard courses

[590]. Further investigations are warranted to elucidate the exact duration of therapy that maximizes

therapeutic outcome and suppresses resistance development. Until conclusive findings are made,

antibiotic therapy should “hit hard” in the early course of infection and “stop early” to assist in

resistance prevention.

7.2.6.3 Altered dosing approaches

Optimal and timely PK/PD target attainment has been associated with the likelihood of clinical

success and resistance suppression in critically ill patients [1]. However, organ function changes

that may result from either infectious or non-infectious pathologic processes may alter antibiotics

exposure. For example, the increase in Vd for hydrophilic antibiotics such as the aminoglycosides

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[591, 592], beta-lactams [56], glycopeptides [107], and linezolid [87], have been extensively

documented in critically ill patients. Importantly, this phenomenon leads to sub-optimal antibiotic

concentration and may impair the attainment of desired PK/PD targets for optimal activity,

particularly in the early phase of severe sepsis and septic shock. In this setting, higher initial loading

doses of hydrophilic antibiotics should be applied to compensate for the volume expansion. In the

context of resistance prevention, the approach may have the potential utility to rapidly reduce

bacterial burden in the early stage of infection. Tsuji et al., recently tested the impact of a front-

loaded linezolid-dosing regimen on bacterial killing and resistance suppression in a HFIM of

MRSA infection [593]. From a PD standpoint of bacterial eradication, their findings suggest

potential benefits of increasing doses of linezolid early in therapy although no differences were

observed in terms of resistance suppression. Further pre-clinical studies are necessary to investigate

this promising dosing strategy particularly in the context of resistance suppression, before it can be

fully applied in clinical practice.

For the beta-lactams, maintaining effective exposure for extended periods or increasing % fT>MIC

would be especially appropriate in the prevention of resistance particularly in critically ill patients.

Research has shown that the traditional bolus dosing produces sub-optimal antibiotic concentrations

for much of the dosing interval, which may consequently favour resistant bacterial strains

development [13]. Numerous pre-clinical and clinical PK/PD studies have demonstrated that

improved beta-lactams exposure could be achieved via EI or CI administration [14]. These altered

dosing approaches may be especially important in patients who develop severe pathophysiological

derangements and when less susceptible pathogens are present. However, more clinical studies are

urgently needed to evaluate the relative ability of EI and CI versus IB dosing of beta-lactam

antibiotics in reducing the emergence of resistance if a global practice change is to be expected.

7.2.7 Conclusion

For decades now, clinicians have overused antibiotics and apparently did so with the notion of our

continuous supply of new antibiotics would adequately address any emerging resistance concerns.

That thought didn’t materialize and on the contrary, as our current antibiotic pipeline is nearly dry,

infecting pathogens have tremendously outperform our existing armamentarium thus far and they

are becoming increasingly difficult to treat. The current situation that we are in is not surprising as

most of our treatment goals were previously focused on maximizing clinical and microbiological

cure and not minimization of the emergence of antibiotic resistance. With numerous pre-clinical

data indicating that the magnitude of the PK/PD indices for resistance suppression is generally

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higher than the thresholds required for clinical success, antibiotic dosing that only aims to optimize

clinical efficacy may potentially amplify resistance formation by selecting mutant bacterial strains

with reduced drug susceptibility. Furthermore, the relevance of commonly prescribed antibiotic

dosing is questionable in severely-ill patients as most dosing recommendations have been derived

from studies that do not consider the occurrence of pathophysiological changes in critical illness.

Therefore, with enhanced knowledge on antibiotic PK/PD over recent years, emerging data are

suggesting that the PD-based dosing approach should not only aim to maximize clinical outcomes

but to also include the suppression of resistance. In some antibiotics such as the fluoroquinolones,

the PD thresholds needed to prevent the emergence of resistance is readily described but

unfortunately, is often neglected and not implemented in clinical practice; whilst for most antibiotic

classes, specific research is urgently needed. To curb the development of resistance, it is likely that

we have to administer “the highest tolerated antibiotic dose” via alternative dosing strategies and

should also consider the combined use of multiple antibiotics (that are rationally optimized),

particularly early in the course of infection in severely ill patients.

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7.3 Conclusion

Previous studies of optimization of antibiotic dosing only focused on maximizing clinical and

microbiological cure and not minimization of the emergence of antibiotic resistance. The data

presented in this chapter showed that most of the information describing PK/PD and its association

with antibiotic resistance were derived from pre-clinical studies. The application of PK/PD

principles for dosing antibiotics have been shown to reduce the risk of antibiotic resistance and

increasing data are suggesting that the dosing approach should not only be explored to maximize

patient outcomes but to also include the suppression of resistance. To minimize the development of

antibiotic resistance in critically ill patients, it is likely that clinicians will have to administer “the

highest tolerated antibiotic dose” via alternative dosing strategies.

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Chapter 8: Summary of findings, general discussion, conclusion and

future directions

8.1 Summary of findings and general discussion

Critically ill patients are markedly different from those in general ward settings as they are

associated with higher morbidity and mortality rates. These patients commonly demonstrate a high

level of illness severity which causes profound physiological changes that can alter the PK of

antibiotics. Antibiotic dosing that does not account for these changes may lead to therapeutic failure

and the emergence of antibiotic resistance.

The issue of critical illness-related alterations affecting beta-lactam dosing requirements was

described in Chapter 2. Chapter 2 aimed to describe the population PK of doripenem in critically ill

patients with sepsis and use Monte Carlo dosing simulations to provide clinically relevant dosing

guidelines for these patients. The typical Vd of doripenem in this cohort was 0.47 L/kg, which was

two-fold greater than that previously described in healthy volunteers and non-critically ill patients.

The finding is expected and it is in agreement with other currently available data investigating the

PK of doripenem in critically ill patients with sepsis. Extreme fluid extravasation related to critical

illness and aggressive medical interventions have been suggested to cause these increases in Vd.

The typical CL in this cohort was 0.14 L/kg/hr and this estimate was significantly influenced by

CLCR such that a 30 mL/min increase in estimated CLCR would increase doripenem CL by 52%.The

importance of BOV on CL in the PK model, which is also described in Chapter 2, suggests a certain

degree of variability in CL exists between treatment days. This means that dosing requirements in

this population may be dynamic and highlights that regular dosing review and potentially, use of

TDM to maximize therapeutic outcomes. It is likely that conventional dosing of doripenem does not

consider these pathophysiological perturbations and as such, the licensed “one-dose-fits-all” dosing

strategy is likely to be flawed in critically ill patients. Data presented in Chapter 2 showed that for

pathogens with a MIC of 8 mg/L, a dose of 1000 mg 8-hourly as a 4-hour infusion is optimal for

patients with CLCR of 30-100 mL/min whilst a dose of 2000 mg 8-hourly as a 4-hour infusion is

required for patients manifesting a CLCR >100 mL/min. This, in a way, highlights that an alternative

dosing approach such as the empirical use of EI of doripenem should be strongly considered in this

patient population, particularly when pathogens with higher MICs are involved.

The primary aims of the Thesis was to investigate the potential benefits of PI dosing (i.e., CI and

EI) as an alternative dosing method to conventional IB administration in critically ill patients. Based

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on the structured review of published literature presented in Chapter 3 and 5, current evidence

suggest that CI of beta-lactam antibiotics may not be advantageous for all critically ill patients but

may only be meritorious to a specific cohort of patients with severe infections. The niche benefits of

PI dosing was further explored in Chapter 4, which presented the findings of a post hoc analysis on

the database of the DALI study. The primary aims of the analysis was to compare the PK/PD target

attainment and clinical outcomes between PI (i.e., CI and EI) and IB dosing of two commonly used

beta-lactams (i.e., piperacillin/tazobactam and meropenem) in a large cohort of critically ill patients

who were not receiving RRT. In this analysis, the use of PI dosing significantly increased the target

attainment for most PK/PD end-points. The data presented in Chapter 4 further specified the sub-

group of patients who are more likely to benefit from PI dosing. In the sub-group of patients who

had respiratory infection, those who received beta-lactams via PI dosing demonstrated significantly

better 30-day survival as opposed to IB patients (86.2% versus 56.7%; p = 0.012). Additionally, in

patients with a SOFA score of ≥9, administration by PI as compared to IB dosing was significantly

associated with better clinical cure (73.3% versus 35.0%; p = 0.035) and higher survival rates

(73.3% versus 25.0%; p = 0.025). These findings further corroborate similar claims of previous

studies which suggested potential benefits of PI dosing of beta-lactam antibiotics in critically ill

patients with severe pneumonia. Accordingly, future clinical studies should seek to test the potential

clinical superiority of altered beta-lactam dosing strategies in a specific cohort of critically ill

patients with severe infections, particularly in those with respiratory infection and not receiving

RRT.

Although numerous pre-clinical and PK/PD data support CI of beta-lactam antibiotics in critically

ill patients, the current evidence, presented in Chapter 3 and 5, suggest neither superiority nor

inferiority of IB dosing with regards to patient outcomes. The lack of clinical outcome data to

support the pre-clinical data may be because the existing studies are underpowered to detect

differences in patient-centred outcomes (e.g., mortality) between the two dosing approaches.

Chapter 5 aimed to scrutinize the published clinical studies for their methodological shortcomings

in the comparison of CI and IB of beta-lactam antibiotics in hospitalized patients. As described in

that chapter, most of the published clinical studies used inconsistent study designs and treatment

arms, and mostly recruited heterogeneous patient populations which mainly consist non-critically ill

patients. Furthermore, most studies were found to recruit patients with highly susceptible pathogens

and this patient selection may mask the potential advantages of CI administration. If many patients

with highly susceptible pathogens are included in a study, the sample size required to show a

clinical difference between CI and IB dosing will rise dramatically. The findings in Chapter 5 also

suggest that these patients should be the focus of future clinical studies: (a) critically ill patients; (b)

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patients with higher level of illness severity (e.g., APACHE II ≥15); (c) patients infected with less

susceptible microorganism; (d) patients infected with Gram-negative infections and; (e) patients

who are not receiving RRT.

The BLISS study, which was presented in Chapter 6, was designed to address most of the

limitations of previous studies. The BLISS study is a prospective, two-centre, RCT of CI versus IB

dosing of beta-lactam antibiotics which was conducted in two Malaysian ICUs. This study recruited

140 critically ill patients with severe sepsis who were not on RRT prior to study inclusion. The

primary outcome evaluated in the study was clinical cure at 14 days after antibiotic cessation and

secondary outcomes included PK/PD target attainment, ICU-free days and ventilator-free days at

Day 28 post-randomization, 14- and 30-day survival, and time to WCC normalization. In this study,

CI of beta-lactam antibiotics demonstrated higher clinical cure rates (56% versus 34%; p = 0.011)

and better PK/PD target attainment compared to IB dosing. CI participants were ten-times more

likely to achieve 100% fT>MIC on Day 1 (p <0.001) and nine-times more likely to achieve 100%

fT>MIC on Day 3 (p <0.001) post-randomization. Furthermore, CI participants also demonstrated

increased ventilator-free days (22 versus 14; p = 0.043) and a reduced time to WCC normalization

(3 days versus 8 days; p <0.001) as compared to IB participants. Essentially, the findings presented

in Chapter 6 highlight that CI of beta-lactam antibiotics may be highly advantageous in those with a

high level of illness severity and not receiving RRT. The findings of the BLISS study also suggest

that CI dosing may be highly important in the management of patients who are infected with

pathogens with higher MICs considering that this study was conducted in a geographical region

which is mostly implicated with less susceptible pathogens. Although actual MIC values were not

available, 41% of the causative pathogens isolated from the BLISS study were either A. baumannii

or P. aeruginosa which mostly have higher MICs to the study antibiotics, thereby reducing the

likelihood of achieving therapeutic concentrations with IB dosing. Importantly, CI participants in

this study were three-times more likely to achieve clinical cure even after controlling for

confounding variables (OR 3.21, 95% confidence interval 1.48-6.94; p = 0.003).

A final area of study which presented in this Thesis was a structured review of published literature

describing the relevance of PK/PD characteristics of different antibiotic classes on the development

of resistance. Findings presented in Chapter 7 showed that the risk of antibiotic resistance

dramatically increases with sub-optimal dosing and this phenomenon is frequently described with

the fluoroquinolones. Traditionally, most of our treatment goals were focused on maximizing

clinical outcomes and have not included minimization of the emergence of resistance and this

strategy has indirectly contributed to rapid development of bacterial resistance. The data in Chapter

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7 also suggest that PK/PD principles should be highly considered when dosing antibiotics in

critically ill patients as the strategy has been shown to minimize the risk of antibiotic resistance. To

prevent the emergence of resistance, it is likely that clinicians need to administer “the highest

tolerated antibiotic dose” via alternative dosing strategies particularly early in the course of

infection in critically ill patients.

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8.2 Future directions for research

Based on the findings presented in this Thesis, there are several areas for further research to address

the following gaps in knowledge:

The theoretical basis for CI administration of beta-lactam antibiotics in critically ill patients

are currently well established. However, numerous studies lacked a design that was

sufficient to explore the effect of CI and IB dosing and this may have prevented them from

obtaining a definitive answer as to which beta-lactam dosing method should be preferred in

critically ill patients. Therefore, a large-scale, prospective, multinational RCT (n = 700) is

now required to ascertain whether the potential benefits of CI dosing of beta-lactam

antibiotics do indeed translate into survival benefit in critically ill patients. The proposed

RCT should also focus on these patients: (a) critically ill patients with severe sepsis; (b)

patients who are not receiving RRT; (c) patients with severe pneumonia and; (e) patients

who are likely to be infected with less susceptible Gram-negative pathogens.

Although numerous studies have been performed to determine the optimal beta-lactam

PK/PD targets for clinical success, very little data exist describing their roles in the

prevention of bacterial resistance. Therefore, appropriate PK/PD targets are urgently

required for this antibiotic class before a dosing regimen that minimizes the emergence of

resistance can be suggested. It follows that, once these PK/PD targets are defined, they can

be employed as one of the main end-points in future RCTs in order evaluate the relative

ability of CI versus IB dosing in reducing the emergence of resistance associated with the

use of beta-lactam antibiotics.

Most antibiotic dosage suggestion in Malaysia does not appear to be based on any published

studies in Malaysian patients but rather PK/PD analyses of healthy Caucasian volunteers and

therefore, its “suitability” and “appropriateness” for the local critically ill population is yet

to be confirmed. Accordingly, there comes the need to evaluate the effectiveness of the

current antibiotic dosing regimen in the Malaysian critically ill population via PK/PD

analysis.

193

8.3 Conclusion

Profound pathophysiological changes in critically ill patients may significantly alter the PK of beta-

lactam antibiotics and consequently reduce PK/PD target attainment. Conventional beta-lactam

dosing does not address these alterations and as such, increases the likelihood of therapeutic failure

and the emergence of resistance in critically ill patients. Altered dosing approaches (i.e., CI and EI)

may be needed to ensure optimal beta-lactam exposure and may produce better therapeutic

outcomes than IB administration, particularly in critically ill patients with severe sepsis.

194

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