Nurse-led clinic for patients with liver cirrhosis – effects on health-related quality of life NCT02957253 Date: 08/08/2018

1Hjorth M, et al. BMJ Open 2018;8:e023064. doi:10.1136/bmjopen-2018-023064

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Nurse-led clinic for patients with liver cirrhosis—effects on health-related quality of life: study protocol of a pragmatic multicentre randomised controlled trial

Maria Hjorth,1,2 Daniel Sjöberg,1 Anncarin Svanberg,2,3,4 Elenor Kaminsky,3 Sophie Langenskiöld,3 Fredrik Rorsman2

To cite: Hjorth M, Sjöberg D, Svanberg A, et al. Nurse-led clinic for patients with liver cirrhosis—effects on health-related quality of life: study protocol of a pragmatic multicentre randomised controlled trial. BMJ Open 2018;8:e023064. doi:10.1136/bmjopen-2018-023064

► Prepublication history for this paper is available online. To view these files, please visit the journal online (http:// dx. doi. org/ 10. 1136/ bmjopen- 2018- 023064).

Received 19 March 2018Revised 21 June 2018Accepted 8 August 2018

1Center of Clinical Reaerch in Dalarna, Falun, Sweden2Department of Medical Sciences, Uppsala Universitet Medicinska fakulteten, Uppsala, Sweden3Department of Public Health and Caring Sciences, Uppsala University, Falun, Sweden4Dalarna University, Falun, Sweden

Correspondence toMrs Maria Hjorth; maria. hjorth@ medsci. uu. se

Protocol

© Author(s) (or their employer(s)) 2018. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.

AbstrACtIntroduction Liver cirrhosis affects health-related quality of life (HRQoL) even in its early stages. Morbidity is especially high when the disease decompensates and self-care actions become essential. Nurse involvement in secondary prevention in other chronic diseases has contributed to better symptom control, less need of inpatient care and improved HRQoL. In order to evaluate the impact of nurse involvement in the follow-up of patients with liver cirrhosis, we decided to compare structured nurse-led clinics, inspired by Dorothea Orem’s nursing theory and motivational strategies, with a group of patients receiving standard care. The primary outcome is HRQoL and the secondary outcomes are quality of care, visits to outpatient clinics or hospitals, disease progress and health literacy.Methods and analysis This is a pragmatic, multicentre randomised controlled study conducted at six Swedish hepatology departments. Eligible patients are adults with diagnosed cirrhosis of the liver (n=500). Participants are randomised into either an intervention with nurse-led follow-up group or into a standard of care group. Recruitment started in November 2016 and is expected to proceed until 2020. Primary outcomes are physical and mental HRQoL measured by RAND-36 at enrolment, after 1 and 2 years.Ethics and dissemination The study is ethically approved by the Regional Ethical Review Board in Uppsala. The results shall be disseminated in international conferences and peer-reviewed articles. trial registration number NCT02957253; Pre-results.

IntroduCtIon The incidence of liver cirrhosis in Sweden is approximately 14 per 100 000 citizens each year.1 It is a disease with high mortality as well as high morbidity, affecting patient’s health-related quality of life (HRQoL). Fatigue and depression are already frequent during the early, compensated, phase of liver cirrhosis and are believed to impair HRQoL by affecting the patient’s social life.2 HRQoL

is further impaired in the decompensated patients, when symptoms of ascites, hepatic encephalopathy (HE) or variceal haemor-rhage occur.3 4

In the compensated stages, lifestyle changes are important to prevent or delay disease progression. While in the decompensated phase, customised lifestyle changes and self-care become essential in the management of the disease.5 Unstructured follow-up in outpa-tient settings causes frequent readmissions due to the reappearance of complications of cirrhosis. The reason may be drug-related side effects, for example, diuretics, non-ad-herence to self-care or medical treatment. One-third of these episodes are said to be preventable with closer follow-up in an outpa-tient setting.6 7

Motivating patients for self-care activities is essential in nursing care. For this, Orem’s theory of nursing,8 consisting of the three theories: self-care, self-care deficit and the nursing system may be applied. This theory

strengths and limitations of this study

► This pragmatic multicentre randomised controlled study design enables evaluation of a nurse-led clin-ic intervention in patients with liver cirrhosis in the real-life context.

► All nurses involved in the study are proficient in the field of liver diseases, having a holistic understand-ing of the situation of liver cirrhosis.

► The generic health-related quality of life instrument RAND-36 is used as a Swedish version of a liv-er-specific instrument is currently unavailable.

► There is a risk of unwittingly transferring the inter-vention to the control group. This is counteracted by the multicentre design and will shorten the time for recruitment of participants.

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guides nurses to identify and support patients to enter self-care for better symptom control and improved health.8–10 In liver cirrhosis, management of patients with liver cirrhosis is traditionally taken care of by physicians, while nurse-led clinics are still rare. However, previous studies on liver cirrhosis, nurse-led clinics have suggested that nurse-led clinics will contribute to better patient concor-dance with physician recommendations11–13 and medical treatment,11 12 with positive effects on patients HRQoL.12 Furthermore, there are indications that nurse-led clinics increase the quality of care by increasing the number of patients treated according to medical healthcare guidelines.12 Finally, the patients have reported a high degree of satisfaction by nursing care in such outpatient settings.12 14 Despite these reports, the significance of adjunctive nurse-led clinic to standard care by physician in liver cirrhosis is unclear. Conversely, in chronic heart failure, nurse-led care is established and proved equally effective as traditional care by the physician within outpatient settings.15 The holistic and person-centred approaches by the nurse, including motivational strat-egies, have been shown to be crucial in the secondary prevention of chronic heart disease, reducing the need for inpatient care and to increase HRQoL.16 17 Hence, the experience from nurse-led clinics in chronic heart disease is likely to provide guidance regarding content, methods and necessary skills in the set-up of nurse-led clinics within the field of liver cirrhosis.

The aim with the present study is to compare HRQoL in patients with liver cirrhosis receiving either adjunctive nursing care based on Orem’s nursing theory or standard care only in outpatient settings.

MEthods And AnAlysIsThe protocol follows the statement of Standard Protocol Items: Recommendations for Interventional Trials 2013,18 for study protocol and Template for Intervention Dscrip-tion and Replication (TIDieR).19 .

study designThe study has a pragmatic, multicentre randomised controlled comparative design.

study armsPatients in the intervention group obtain structured visits to nurse-led clinics depending on the severity of the disease. The intervention is adjunctive, that is, the intervention is added to standard care. Patients in the control group get standard inpatient and outpatient care according to clinical routines.

study sitesThe study settings consist of six outpatient clinics at hepa-tology departments in Sweden, two county hospitals and four university hospitals. None of the clinics had struc-tured nursing care for patients with liver cirrhosis at the beginning of the study. The six outpatient clinics serve

a population of approximately 2 000 000 individuals, comprising about 20% of Sweden’s population.

Eligibility criteriaDiagnosis of liver cirrhosis is based on clinical investi-gation, laboratory findings, histology, MRI, computer tomography, ultrasound or elastography. Factors likely to strongly affect the primary variable due to other reasons than liver cirrhosis, that is, severe comorbidities and those unable to adhere to the study protocol, that is, persistent, overt HE, are excluded. Inclusion and exclusion criteria are presented in table 1.

screening and recruitment of participantsInvitation letters are sent by intervention nurses (INs), offering oral information. Patients are invited to a screening visit to IN for baseline measurements. Those who meet inclusion criteria are registered. Patients, who agree to participate, hereafter denoted as participants, are randomised after giving informed consent. Newly diagnosed patients are recruited consecutively (figure 1). INs are responsible facilitators and consecutively follow participants.

randomisationComputerised randomisation (Randomize.Net, Inter-rand, Ottawa, Canada) is performed at the screening visit with randomly mixed block sizes of 4, 6 and 8, stratified by study site and disease severity in terms of compen-sated or decompensated state (figure 1). Blinding of the randomisation sequence is applicable to all involved personnel; allocation will be 1:1. Baseline measurements are completed before randomisation. Further blinding is not possible in this study.

Table 1 Inclusion and exclusion criteria 

Inclusion criteria Exclusion criteria

Diagnosed liver cirrhosis within the past 24 months

Insufficient knowledge of the Swedish language

Follow-up at the hepatology department

Persistent hepatic encephalopathy grades 2–4

Age 18–85 years Comorbidity

Chronic obstructive pulmonary disease grades 3–4

Coronary heart disease New York Heart Association Functional Classification (NYHA) classes 3–4

Dementia

Actual advanced cancer

Stroke with sequelae

Severe psychiatric disease

Renal failure requiring dialysis

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description of the interventionParticipants in the intervention group offer scheduled individual visits to INs at the nurse-led clinic, in addi-tion to visits to a physician according to clinical prac-tice. Intervals between visits to the nurse-led clinic are varying from once yearly in compensated stable disease, up to two visit per month in decompensated disease

(figure 2). The tailored frequency and content of visits are individualised to promote person-centred care (table 2).

Participants in the control group will receive standard care by physicians within hepatology inpatient or outpa-tient clinics as required and a yearly follow-up for data collection by IN within the study (figure 2).

Figure 1 Recruitment and randomisation of participants. CC, compensated control group; CI, compensated intervention group; DC, decompensated control group; DI, decompensated intervention group; LC, liver cirrhosis.

Figure 2 Study measurements and intervention nurse visit interval. CRT, continuous reaction time; IN, intervention nurse; MELD, Model for End-Stage Liver Disease; NVS, Newest Vital Sign; PHES-test, psychometric HE score; QPP, quality of care from the patient’s perspective; RFH-NPT, Royal Free Hospital-Nutritional Prioritising Tool.

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Each visit to INs contains assessment of disease severity to enable early action against disease progression and malnutrition (table 2). The intervention includes treat-ment and nursing care inspired by Dorothea Orem’s nursing theory.10 Further, motivational interviewing (MI),20 communication strategies will be used. Both Orem’s theory and MI implies that individuals have an intrinsic motivation to make appropriate choices, to promote health and prevent disease or to perform actions to counteract disease.10 20 The task of the IN is to assess the participants’ self-care needs and their ability to perform essential self-care in order to discover self-care deficits. To evoke participants’ motivation, INs listen and reflect on preparatory and mobilising change talk. In addition, INs give information adherent to MI techniques to facil-itate participants understanding of actual self-care and medical treatment (figure 3). When applicable, INs offer next of kin instructions to help the participant achieve self-care.

The areas of the intervention are: (1) monitoring risk factors for deterioration of the liver disease, (2) informa-tion and motivation to perform self-care and adhere to medical treatment, (3) nutrition assessment and support, (4) motivation of lifestyle changes essential for preventing or delaying disease progress and (5) psychosocial care. A booklet written by MH is handed to all INs describing these five areas converted into terms of Orem’s nursing theory.

One objective of INs’ use of MI is to promote engage-ment and increased collaboration between IN and partic-ipant via the MI spirit concepts: partnership, evocation, compassion and acceptance. Another objective is that INs evoke participants’ own motivation and explore patients’ own thoughts about a target behaviour when there is need for behavioural change. When participants express mobilising ‘change talk’,20 they are ready for the plan-ning phase (figure 3). The intervention is individually tailored and INs’ activities depend on actual needs. An

Table 2 Description of the intervention

Disease severity Frequency of visits Content of visits

Compensated disease Once yearly Child Pugh scoreModel for End-Sage Liver Disease (MELD)-scoreThe Royal Free Hospital-Nutritional Prioritising ToolAssessment of: ascites, encephalopathyMotivation to lifestyle changesPsychosocial issues

Decompensated disease within 12 months or

1–2 visits/month Child Pugh scoreMELD scoreThe Royal Free Hospital-Nutritional Prioritising ToolAssessment of: ascites, encephalopathy, side effects of medical treatmentMotivation to self-care and/or lifestyle changesPsychosocial issues

Previously decompensated disease

Every third month

Figure 3 The four processes of motivational interviewing techniques. IN, intervention nurse; MI, motivational interviewing.

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information booklet about liver cirrhosis is available to participants as a complement to oral information.

Standard care includes flexible visits or telephone follow-up by physicians, gastroscopies, ascites drainage, registered nurse telephone counselling by a nurse not participating in the study and inpatient care.

Intervention nursesAt each of the six clinics, 1–2 INs are involved in the intervention. All of these are registered nurses with a minimum of 2 years experience from hepatology inpa-tient or outpatient care. Implementation of the interven-tion and training of INs include a 6-hour seminar with a short description of MI and Orem theories followed by a 3-day training to perform MI. INs are also educated in pathophysiology of liver cirrhosis, nursing care according to presenting symptoms, study bias and study instruments. Scheduled tutorial group sessions to follow the interven-tion and MI practice will be due every 6 months for all INs during the study period.

study pilotingA pilot of the intervention and patient questionnaire was performed in Falun from 2014 to 2015 with 26 partici-pating patients. The aim was to define the actual size of the population available for the study and to assess the time and budget for the INs’ assignment.

baseline sociodemographic data collectionSociodemographic data collected at enrolment are presented in figure 2.

Primary outcomePhysical and mental HRQoL are the two main outcomes in the present study measured by RAND-36.21 RAND-36 consists of 36 category scale questions: the answer to each question ranges from 0 to 100, a higher value predicts better health. From the RAND-36 questionnaire, eight subscales are derived: (1) physical functioning, (2) role limitations caused by physical health problems, (3) pain, (4) energy/fatigue, (5) social functioning, (6) role limita-tions caused by emotional problems, (7) emotional well-being and (8) general health perception. Out of the eight subscales, two summary components are derived: Phys-ical Component Summary (PCS) and Mental Compo-nent Summary (MCS).21 22 HRQoL measurements by the RAND-36 has high validity and reliability to identify differences in HRQoL over time within and compared with patient populations with different chronic diseases.22

secondary outcomes ► Patient’s perspective of quality of care due to a change

in follow-up strategy: The questionnaire quality of care from the patient’s perspective (QPP)23 includes four dimensions: (1) medical-technical competence, (2) physical-technical conditions, (3) identity-orientated approach and (4) sociocultural atmosphere. Within each dimension, the participants first value their expe-rience of the specific care aspects they have received

((1) totally agree, (2) agree in large part, (3) partly agree or (4) do not agree) and second, the impor-tance of these aspects ((1) of greatest importance, (2) of great importance, (3) of some importance or (4) of little or no importance). The difference between the experienced care and the importance of each ques-tion is categorised as: excess of, balanced or lack of quality of care. A short form of QOP has been found valid and reliable.24 In the present study, partici-pants receive a modified QPP 38-item questionnaire adjusted for patients with liver cirrhosis in outpatient care. The modification has been approved by the instrument developer. The questionnaire includes a variation of yes/no questions, category scales from 1 to 4 and open-ended questions.

► Visits at outpatient clinics and admissions to hospital: Visits at outpatient clinics, number of admissions to hospitals and days of inpatient care at medical wards or intensive care units will be recorded as measures of healthcare consumption. In case of significant clinical outcomes, these data will later be used to perform a separate health economic analysis.

► Disease progress1. Child Pugh score25 includes five variables: serum

albumin, serum bilirubin, prothrombin time, ascites and encephalopathy. Each variable grading from 1 to 3 and the total range is 5–15. A higher value means a more advanced disease. Three risk classes are derived: A=score 5–6, B=score 7–9 and C=score 10–15.26

2. The Model for End-Stage Liver Disease (MELD)27 predicts the 3-month mortality of patients with chronic end-stage liver disease. Based on labora-tory findings, MELD is a valid and reliable instru-ment. The formula for MELD is constant for disease aetiology, the calculation score is: 9.57 x log e (creatinine mg/dL)+3.78 x log e (bilirubin mg/dL)+11.20 x log e (INR) +6.4. The score is contin-uous, ranging from 6 to 40, a high score predicts an increased risk of mortality within 3 months.28

3. The Royal Free Hospital-Nutritional Prioritising Tool (RFH-NPT)29 assesses the risk of malnutrition in liver cirrhosis as a predictor of disease deteriora-tion and transplant-free survival. RFH-NPT corre-lates with deterioration of the liver disease and divides participants into low (0 points), medium (1 point) or high (2–7 points) risk groups for malnutrition. Parameters taken into account are nutritional history (unplanned weight loss, dietary intake body mass index) and current complications of liver cirrhosis (acute alcoholic hepatitis, ascites, general fluid overload). The instrument used in the study is a translation into Swedish from the English version. Validation of the translation is made in a research seminar within the research group.

4. Appearance of decompensation episodes (eg, ascites, overt HE and variceal bleed) is assessed at screening, after 12 months and after 24 months

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through medical records. HE is common in liver cirrhosis with a cumulative risk of 30%–40%.30 According to the West-Haven criteria,31 HE ranges from 0 to 4. Grades 0–1 mean subclinical or minimal symptoms (covert HE) and grades 2–4 mean severe neuropsychiatric symptoms (overt HE).30 Even milder grades of HE affect HRQoL.30 31 In the majority of cases, HE is treatable. Two psycho-metric tests in combination are recommended to detect covert HE.30 In this study, the psychometric HE score (PHES) and continuous reaction time (CRT) are used:a. PHES consists of five-step paper and pencil

tests,32 and includes a line drawing test, a serial dotting test and a digit symbol test to examine motor speed and accuracy, visual perception, visuospatial orientation, visual construction, concentration and attention. The test ends up with a score ranging from +6 to −18; −4 or less is the cut-off for a pathological result.

b. CRT33 is a 10 min test with auditory stimuli in headphones in intervals of every 2–6 s. It tests the reaction time and endurance by pushing a trigger button after a signal. Using the software EKHO reaction-time analysis tool, an index <1, 9 with 150 repetitions separate HE from other brain dysfunctions with a specificity of 0.92 and sensitivity of 0.93.

► Health literacy (HL): involves a person’s ability to receive, process and understand basic medical information in making decisions and taking actions to promote health.34 The grade of HL may influ-ence the intervention as it impacts the participants’ ability to understand and translate information into practice. The instrument Newest Vital Sign,35 which consists of six standardised questions about nutrition label information, is used. The questions is asked by INs, the correct answer scores 1 point, a score of 4 or above indicates no limits of HL and scores below 4 indicate limited HL. The instrument is translated from English to Swedish within another study (Health literacy among Swedish lung transplant recipients 1–5 years after transplantation, A Lennerling, A Kisch and A Forsberg, personal communication, 2018). Valida-tion of the translation has been made in a research seminar within our research group and the risk of translation errors was judged to be low.

Participant flow through the studyStudy time for each participant is 24 months (figure 2), after which participants in the intervention group may continue their follow-up at the nurse-led clinic if they want to. Participants in the control group may be offered follow-up at the nurse-led clinic after the end of study. Data collection and frequency of visits to INs are presented in figure 2. Reasons for withdrawal from the study are liver transplantation, move out of follow-up area or mortality. In case of two consecutive cancelled visits

to an IN, a reminder will be sent, asking participants to contact INs for further participation in the study.

data analysis and sample size calculationAnalysis includes the two primary variables in RAND-36: the PCS and the MCS. These components will be calcu-lated based on weights from the oblique method,36 to avoid potential problems in interpretation due to nega-tive weights. A repeated measurements model will be used for analysis of baseline, 12 and 24 months values of the component summary score. Treatment group, time (base-line, 12, 24 months) with interaction, and decompen-sated/compensated state will be fixed effects, while site will be a random effect in the model. The main contrast of interest to be estimated with this model is change from baseline to month 24 for both treatment groups. For the treatment group comparison, Bonferroni-Holm method using a corrected alpha=2.5% will be used to compensate for multiple testing of both PCS and MCS.

All tests will be two sided. For analyses of secondary vari-ables, p values<0.05 are considered significant. Multiple imputation will be used for missing values.

For the power calculation, a SD of 9 points was used based on back-calculated residual variances from CIs for MCS.37 A change of 3–5 points is estimated to be a mini-mally clinically important difference and corresponds to an effect size of 0.09–0.28.22 It is argued that even smaller changes are important,38 and a change of 2.5 points is therefore considered to be potentially relevant for the power calculation. To ensure a power of 0.80 for the effect size of 2.5 points and a Bonferroni-corrected alpha level of 2.5%, the recommended sample size is 250 partic-ipants per treatment group, that is, 500 in total.39 With a calculated 33% non-inclusion rate, enrolment time is esti-mated from November 2016 to December 2020 or until 500 participants are included.

Patient involvementFive patients contributed with comments on the question-naire that resulted in changes in tree of the 78 questions. No patients were involved in study design, research ques-tion or recruitment. The results will be disseminated to the study participants in a short summary after the publi-cation of the study.

strengths and limitationsThis randomised controlled trial in the field of nursing is a complex intervention with a pragmatic design and has a high risk of confounding factors. In a pragmatic design,40 the research aim is to reflect the clinical practice. Partici-pant heterogeneity and a minimum of exclusion criteria are therefore allowed to a larger extent. The researcher must be aware of factors that may bias study results. In this study, participants may have other chronic diseases that may affect HRQoL. Patients with severe comorbidity are not included in this trial as it would have required a larger sample than available. A prolonged study of 5 years raises the risk of unwitting transfer of the intervention on to

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the control group when other personnel than INs start to develop skills included in the study protocol.17 To reduce this risk and preserve the ability to identify changes in HRQoL, study time is set to 4 years. Furthermore, six study sites are included in the study that aims to shorten the time for the study as well as reduce time for contam-ination of the control group. Six study sites, however, imply a risk of performance differences regarding the intervention and control group. In a forthcoming study, the context and mechanisms that may affect the results will be assessed in a process evaluation as described by Moore et al.41 To reduce bias in inclusion, participants in the control group offer a nurse-led clinic when study participation ends.

Although RAND-36 has proved sensitivity to changes in liver cirrhosis, a disease-specific instrument may be more nuanced. However, available disease-specific HRQoL instruments for liver cirrhosis are unfortunately not translated into Swedish. The former comparable generic instrument SF-3622 has been shown to be sensible for differences in HRQoL in populations of liver cirrhosis,.4 42

The MI experience may affect INs’ ability to use MI skills in conversations with participants. However, all INs in the present study are proficient or experts in nursing in the field of liver cirrhosis, having a holistic understanding of the situation of the disease. During the study, the INs will attend tutorial sessions twice a year to develop their skills in MI.

The occurrence of overt HE limits the enrolment of participants. Overt HE may have an impact on the ability to answer questionnaires used in the study. At enrolment, patients with covert HE are accepted. Before measure-ments at 12 and 24 months, HE tests will be repeated before the participants answer the questionnaires. Partic-ipants with overt HE will not be asked to answer the ques-tionnaires, including RAND-36 and QPP, due to the risk of unreliable answers.

To our knowledge, this is the largest randomised controlled study evaluating nurse-led intervention in liver cirrhosis. The pragmatic design enables us to evaluate the effect of the intervention in the real-life context under which the study is performed. The results will hope-fully contribute with important knowledge about nurse involvement in the care of patients with liver cirrhosis that can be applied in the routine clinical setting.

disseminationThe study result will be published in peer-reviewed jour-nals and presented at international conferences. The result will be used for education and competence devel-opment within the field. Study results are reported on the group level.

Acknowledgements To Frank Miller for statistical support and to patient advisers for comments in development of the patient questionnaire.

Contributors MH has contributed to the design, implementation of the study and responsible for drafting the manuscript. DS has taken part in the design of the study and supervised MH in drafting the Manuscript, and has approved the final manuscript. AS has taken part in the design of the study and supervised MH in

drafting the manuscript, and has approved the final manuscript. EK has taken part in the design of the study and supervised MH in drafting the Manuscript, and has approved the final manuscript. SL has taken part in the design of the study and supervised MH in drafting the manuscript, and has approved the final manuscript. FR has taken part in the design of the study and supervised MH in drafting the manuscript, and has approved the final manuscript.

Funding This work was supported by Ester Åsberg Lindberg foundation and Centre for Clinical Research in Dalarna. The CRT equipment was funded by Norgine.

Competing interests None declared.

Patient consent Obtained.

Ethics approval The study has been approved by the Regional Ethical Review Board in Uppsala (Dnr: 2016/146) and is performed according to the Declaration of Helsinki and to the Swedish Ethical Review Act.

Provenance and peer review Not commissioned; externally peer reviewed.

open access This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See: http:// creativecommons. org/ licenses/ by- nc/ 4. 0/.

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32. Weissenborn K, Ennen JC, Schomerus H, et al. Neuropsychological characterization of hepatic encephalopathy. J Hepatol 2001;34:768–73.

33. Elsass P, Christensen SE, Mortensen EL, et al. Discrimination between organic and hepatic encephalopathy by means of continuous reaction times. Liver 1985;5:29–34.

34. Sheridan SL, Halpern DJ, Viera AJ, et al. Interventions for individuals with low health literacy: a systematic review. J Health Commun 2011;16 Suppl 3:30–54.

35. Weiss BD, Mays MZ, Martz W, et al. Quick assessment of literacy in primary care: the newest vital sign. Ann Fam Med 2005;3:514–22.

36. Laucis NC, Hays RD, Bhattacharyya T. Scoring the SF-36 in Orthopaedics: a brief guide. J Bone Joint Surg Am 2015;97:1628–34.

37. Team UR. UKATT Research Team. Effectiveness of treatment for alcohol problems: findings of the randomised UK alcohol treatment trial (UKATT). BMJ 2005;331:541.

38. Samsa G, Edelman D, Rothman ML, et al. Determining clinically important differences in health status measures. Pharmacoeconomics 1999;15:141–55.

39. Julious SA. Sample sizes for clinical trials. United States of America: Chapman & Hall/CRC, 2009:268.

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ownloaded from

Statistical Analysis Plan NCT02957253

TABLE OF CONTENTS

1 Abbreviations .................................................................................................................................. 1

2 Introduction and study aim ............................................................................................................. 1

3 Study endpoints ............................................................................................................................... 1

3.1 Primary outcome ..................................................................................................................... 1

3.2 Secondary outcomes ............................................................................................................... 2

3.2.1 Patient’s perspective of quality of care (QPP) ................................................................. 2

3.2.2 Visits at outpatient clinics and admissions to hospital .................................................... 2

3.2.3 Child Pugh score .............................................................................................................. 2

3.2.4 Model of end stage liver disease (MELD) ........................................................................ 3

3.2.5 Royal free hospital-nutritional prioritising tool (RFH-NPT) ............................................. 3

3.2.6 Appearance of decompensation episodes ...................................................................... 3

3.2.7 Hepatic encephalopathy (HE) .......................................................................................... 3

3.2.8 Health literacy (HL) .......................................................................................................... 3

4 Sample size determination .............................................................................................................. 3

4.1 Assumption for variability ....................................................................................................... 3

4.2 Assumption for effect .............................................................................................................. 4

4.3 Sample size calculation ............................................................................................................ 4

5 Analysis Populations ........................................................................................................................ 4

6 General analysis methods ............................................................................................................... 5

6.1 Multiplicity aspects .................................................................................................................. 5

6.2 Visit windows ........................................................................................................................... 5

6.3 Handling of missing data ......................................................................................................... 5

7 Primary and secondary analyses ..................................................................................................... 5

7.1 Primary analysis ....................................................................................................................... 5

7.2 Secondary analyses ................................................................................................................. 6

7.2.1 Patient’s perspective of quality of care (QPP) ................................................................. 6

7.2.2 Visits at outpatient clinics and admissions to hospital .................................................... 6

7.2.3 Child Pugh score .............................................................................................................. 7

7.2.4 Model of end stage liver disease (MELD) ........................................................................ 7

7.2.5 Royal free hospital-nutritional prioritising tool (RFH-NPT) ............................................. 7

7.2.6 Appearance of decompensation episodes ...................................................................... 7

7.2.7 Hepatic encephalopathy (HE) .......................................................................................... 7

7.2.8 Health literacy (HL) .......................................................................................................... 7

References ............................................................................................................................................... 7

1

1 ABBREVIATIONS

CI Confidence interval

CRT Continuous reaction time

HE Hepatic encephalopathy

HL Health literacy

HRQoL Health-related quality of life

ITT Intention-to-treat (population)

MELD Model of end stage liver disease

MCID Minimum clinically important difference

MCS Mental component summary (of RAND-36)

NVS Newest Vital Sign (questionnaire)

PCS Physical component summary (of RAND-36)

PHES Psychometric hepatic encephalopathy score

QPP Quality of care from the patient’s perspective (questionnaire)

RAND-36 Health survey by the RAND (Research and Development) group

RFH-NPT Royal free hospital-nutritional prioritising tool

2 INTRODUCTION AND STUDY AIM

The study protocol is described by Hjorth et al. (2018). The Clinical Trial registration number is:

NCT02957253.

The aim with the present study is to compare Health-related quality of life (HRQoL) in patients with

liver cirrhosis receiving either adjunctive nursing care based on Orem’s nursing theory (intervention

group) or standard care only (control group) in outpatient settings.

The study has a pragmatic, multicentre randomised controlled comparative design. Computerised

randomisation (allocation 1:1) is performed at the screening visit after completion of baseline

measurements. Randomly mixed block sizes of 4, 6 and 8 are used, stratified by study site and

disease severity in terms of compensated or decompensated state. It is not possible to blind

interventions in this study.

Study time for each participant is 24 months and main timepoints for data collection are: baseline,

Month 12, Month 24.

3 STUDY ENDPOINTS

3.1 PRIMARY OUTCOME Physical and mental HRQoL are the two main outcomes in the present study measured by RAND-36

(Hays et al., 1993). RAND-36 consists of 36 category scale questions: the answer to each question

ranges from 0-100, a higher value predicts better health. From the RAND-36 questionnaire, eight

subscales are derived: (I) physical functioning, (II) role limitations caused by physical health problems,

(III) pain, (IV) energy/fatigue, (V) social functioning, (VI) role limitations caused by emotional

problems, (VII) emotional wellbeing and (VIII) general health perception. Out of the eight subscales,

2

two summary components are derived: physical component summary (PCS) and mental component

summary (MCS), see Hays et al. (1993), Hays and Morales (2001). These components will be

calculated based on weights from the oblique method (Laucis et al., 2015) to avoid potential

problems in interpretation due to negative weights.

3.2 SECONDARY OUTCOMES

3.2.1 Patient’s perspective of quality of care (QPP)

Patients received at baseline, at Month 12, and at Month 24 a 38-item version of the questionnaire

Quality of care from the patient’s perspective (QPP). For Item 5 to 26, the participants both value

their experience of the specific care aspects they have received and their importance. These answers

were classified according to the QPP manual Wilde-Larsson et al. (2001) into “lacking quality”,

“balance” and “excess quality”. The items are grouped into 4 dimensions: (I) Medical-technical

competence, (II) physical-technical conditions, (III) identity-orientated approach and (IV) socio-

cultural atmosphere. The other items are items with multiple choice answers (usually, only one of

the provided answers can be given, except for Item 1 where multiple responses can be given) and

some open-ended questions.

3.2.2 Visits at outpatient clinics and admissions to hospital

The following variables will describe the number of visits at outpatient clinics:

Number of outpatient visits to physicians

number of outpatient visits to nurse-led clinics

number of visits to dietitian

number of visits to physiotherapist

number of visits to social counsellor

number of telephone contacts to physicians

number of telephone contacts to nurses

number of gastroscopies

number of paracentesis

The following variables will describe admissions to hospitals:

Number of admissions to hospitals,

days of inpatient care at medical wards,

days of inpatient care at intensive care units.

If a health economic analysis is conducted (see Section 7.2.2), the following measures will be

considered to calculate costs: TIPS, paracentesis, liver surgery, ablation, TACE, Sirtex and medical

treatment with Hepa-Mertz and Glypressin.

The above variables will be recorded for the interval between baseline and Month 12 and for the

interval between Month 12 and Month 24.

3.2.3 Child Pugh score

The Child Pugh score include five variables: serum albumin, serum bilirubin, prothrombin time,

ascites and encephalopathy. Each variable grading from 1-3 and the total range is 5-15. A higher

value means a more advanced disease. Three risk classes are derived: A= score 5-6, B= score 7-9 and

C= score 10-15.

3

3.2.4 Model of end stage liver disease (MELD)

The model of end stage liver disease (MELD) predicts the three-month mortality of patients with

chronic end-stage liver disease. The score used (defined in Hjorth et al., 2018) is continuous, ranging

from 6 to 40 with higher values for a worse disease state.

3.2.5 Royal free hospital-nutritional prioritising tool (RFH-NPT)

The Royal free hospital-nutritional prioritising tool (RFH-NPT) correlates with deterioration of the

liver disease and divides participants into low (0 points), medium (1 point) or high (2 to 7 points) risk

groups for malnutrition.

3.2.6 Appearance of decompensation episodes

Appearance of decompensation episodes (e.g., ascites, overt HE and variceal bleed) is assessed at

baseline, at Month 12, and at Month 24 through medical records. The event is recorded as yes or no.

3.2.7 Hepatic encephalopathy (HE)

Two psychometric tests for HE are used in this study: the psychometric HE score (PHES) and

continuous reaction time (CRT).

The PHES test ends up with a score ranging from +6 to -18; -4 or less is the cut-off for a pathological

result (Weissborn et al., 2001).

The CRT results will be analysed using the software EKHO reaction-time analysis tool. An index is

computed and the cut-off value of 1.9 separates a normal and pathological test result (Elsass et al.,

1985).

Minimal or Grade 1 HE is diagnosed if and only if both tests show a pathological result (according to

clinical guidelines).

3.2.8 Health literacy (HL)

Health literacy (HL) is measured with the instrument Newest Vital Sign (NVS) which consists of six

standardised questions about nutrition label information; a correct answer scores 1 point. A score of

4 or above indicates adequate literacy, 2 or 3 indicate possible limited literacy, 0 or 1 indicate likely

limited literacy (Shah et al., 2010). In the case that less than expected data is obtained, it might be

considered to pool the two classes for scores 0-3.

4 SAMPLE SIZE DETERMINATION

4.1 ASSUMPTION FOR VARIABILITY Change from baseline in summary components were analysed in UKATT (2005). Based on the

reported confidence intervals in their Table 3, the residual standard deviation for change from

baseline was back-calculated to be 5.5 for PCS and 9 for MCS. Note that in this study, PCS values at

baseline were not far from healthy population while MCS values were worse than healthy

population; therefore, it could not be expected that PCS change much during treatment and

variability for change from baseline might be lower than in situations where the potential for change

is larger. Hence, a standard deviation of 9 is judged as reasonable even for PCS in a population which

is worse than healthy population. We note that this is also roughly in line with the sd for change from

baseline in Ward et al. (2014) (PCS-sd=9.0, MCS-sd=11.2), however there a Rheumatoid Arthritis

population is studied and follow up is some months after baseline.

4

4.2 ASSUMPTION FOR EFFECT Samsa et al. (1999) mention a recommendation of a Minimum Clinically Important Difference (MCID)

= 3-5 points for the 8 subscales. Since these are non-standardized, this corresponds roughly to 1.5-

2.5 points for standardized subscales. Ward et al. (2014) justify a MCID of 7.2 for the standardized

PCS but this in patients with rheumatoid arthritis; Strand et al. (2012) have in the same population

argued for a MCID of 2.5. In general, it is argued that even small changes are judged important (e.g.

by Samsa et al., 1999) and a change of 2.5 points is therefore considered to be potentially relevant.

We judge now which effect can be expected from the proposed treatment. Younossi et al. (2001)

identified that the average PCS in patients with chronic liver diseases was 41, 39, and 31 for viral,

cholestatic, and hepatocellular disease, respectively, compared with 50 in the healthy population, i.e.

9, 11, and 19 points difference to normal population, respectively. This suggests a larger potential for

improvement. However, the results of Murchie et al. (2004) who investigated similar treatment

suggest that the potential might be limited. They have not analysed summary components but

averaging their results for the subscales roughly according to oblique-weights from Farivar et al.

(2007), we obtain around 4.5 points improvement for PCS and around 2.5 for MCS. These numbers

are based on non-standardized scores. The improvement in standardized scores would roughly be 2-

2.5 for PCS after one year. We recommend therefore to target an effect of 2.5 points for the

standardized summary components.

4.3 SAMPLE SIZE CALCULATION Assuming a residual standard deviation of 9 for change from baseline in PCS and MCS based on

calculations from reported confidence intervals in UKATT (2005) and requiring 80% power for a two-

sided test with significance level 5% between the treatment groups, the required sample size is in the

following table depending on the assumed treatment difference.

Treatment difference 2 2.5 3 3.5 4 4.5

Sample size per group (both PCS and MCS primary variables; Bonferroni correction)

390 250 175 125 100 80

The effects seen in the study by Murchie et al. (2004) correspond approximately to 2.5 points on PCS.

This change has been considered relevant in other diseases (see e.g. Strand et al., 2012). To ensure

the 80% power when the treatment difference is 2.5 points and when both PCS and MCS are primary

variables with Bonferroni-corrected tests, the sample size of 250 patients per treatment-group, i.e.

500 in total, was chosen (Julious, 2009). With a calculated 33% non-inclusion rate, enrolment time is

estimated from November 2016 to December 2020 or until 500 participants are included.

5 ANALYSIS POPULATIONS

The analyses will be based on the intention-to-treat (ITT) principle. All randomized patients will be

included in the analysis as belonging to the randomized treatment group, irrespectively of their

actual treatment.

Some of the secondary analyses will be based on complete cases which means that patients who

drop out prior to the analysis timepoint (Month 12 or Month 24) are excluded from the analysis. The

analysis populations for these analyses are therefore restricted to patients following the study

procedures (protocol) until a certain timepoint.

5

6 GENERAL ANALYSIS METHODS

6.1 MULTIPLICITY ASPECTS All tests will be two-sided. Generally, a significance level of 5% will be used. The analyses for the two

primary variables will be multiplicity adjusted. For analyses of secondary variables, no formal

adjustment for multiplicity will be done. Single significances must therefore not be overinterpreted.

Only if several analyses show results which together give a clear picture, a discussion of a potential

effect of the intervention is justified.

6.2 VISIT WINDOWS Most of the analysis variables are recorded at baseline, Month 12, and Month 24. The actual date of

collection might deviate from the ideal time point 12 or 24 months after the randomization date. The

measurement is considered valid if it is collected between 10 months and 14 months after

randomisation, or between 22 months and 26 months after randomisation, respectively. Otherwise

the measurement is not considered in the analysis. If two or more measurements fall in one of the

above windows, the measurement closest to the ideal time point (12 or 24 months after

randomisation date) will be used and the other measurements is not considered.

6.3 HANDLING OF MISSING DATA Missing values are expected in this study in most analysis variables. We assume however that the

variables “disease severity in terms of compensated or decompensated state” and “study site” used

as independent variables do not suffer from missingness; the former is required for randomisation.

The primary analysis uses a model-based method to deal with missing values: the repeated

measurements model analyses data of every patient even if one or two observations of baseline,

Month 12, and Month 24 are missing.

Secondary analyses will be performed first as complete case analysis. A sensitivity analysis using

multiple imputation (see e.g. Van Buuren, 2018) will be used to handle impact of missing values. If

the analysis model for a specific analysis is a linear or logistic regression model, then the imputation

model will be based on this model adding the independent variables age and gender. If the Mann-

Whitney U test is used for treatment comparison, then an imputation model which is appropriate for

the distribution of the variable will be searched using following independent variables: group

(intervention or control), baseline value (if relevant for this variable), disease severity in terms of

compensated or decompensated state, study site, age, and gender.

Reasons for dropout (patients prematurely terminating the study) will be compared between groups

(intervention or control) by reporting percentage dropout by reason and group. Implications of

differences between groups will be discussed.

7 PRIMARY AND SECONDARY ANALYSES

7.1 PRIMARY ANALYSIS The two primary variables are the physical component summary (PCS) and the mental component

summary (MCS) from RAND-36. A repeated measurements model will be used for analysis of

baseline, Month 12, and Month 24 values of the component summary score. Treatment group

6

(intervention or control), time (baseline, Month 12, Month 24) with interaction, and

decompensated/compensated state will be fixed effects, while site will be a random effect in the

model. The dependence of the observations over time will be modelled using an unstructured

covariance matrix. The main contrast of interest to be estimated with this model is change from

baseline to Month 24 for both treatment groups.

For the treatment group comparison, Bonferroni-Holm-method using a corrected alpha=2.5% will be

used to compensate for multiple testing of both PCS and MCS.

The contrast “change from baseline to Month 12” for both treatment groups will also be estimated

with this model for both PCS and MCS. The treatments will be compared but the p-values for this

Month 12 analysis will not be multiplicity adjusted.

7.2 SECONDARY ANALYSES

7.2.1 Patient’s perspective of quality of care (QPP)

The probability of having “lacking quality” in each of the Items 5-26 will be analysed with a logistic

regression model; in accordance with the QPP manual (Wilde-Larsson et al., 2001, page 37) we focus

on this category since it reflects the least favourable and most demanding situation. We distinguish

not between the categories “balance” and “excess quality” in this model.

Independent variables in the logistic model will be group (intervention or control), if the patient had

“lacking quality” at baseline, disease severity in terms of compensated or decompensated state, and

study site. The effect of group will be summarized using odds ratio with 95% CI, and a p-value for the

null hypothesis of no group effect. The analysis will be done separately for Month 12 and Month 24

data.

Based on the recommendation in the QPP manual (Wilde-Larsson et al., 2001, page 37), items are

analysed separately. Single significances must not be overinterpreted since no adjustment for these

multiple analyses is done. Only if several items within a dimension show similar differences this

points to a potential effect of the intervention.

Items with multiple choice answers are summarized descriptively showing percentage patients by

group (intervention, control) and by time (baseline, Month 12, Month 24). Answers to open-ended

items are summarized if deemed to be relevant.

7.2.2 Visits at outpatient clinics and admissions to hospital

Mean values for number of visits/days in each analysis variable will be summarized by group

(intervention, control) and by time interval (baseline-to-Month-12, Month-12-to-Month-24). Further,

the ratio of number of visits/days for the intervention group relative to the control group will be

reported.

The number of visits/days in each analysis variable will be compared between groups with the Mann-

Whitney U test; the analysis will be done for the baseline-to-Month-12 and Month-12-to-Month-24

interval separately.

These summaries and analyses will be done separately for the patients in compensated and

decompensated state.

If significant clinical outcomes are identified in the study, a health economic analysis will be

conducted.

7

7.2.3 Child Pugh score

The risk classes (A, B, C) will be summarized descriptively showing percentage patients in each class

by group (intervention, control) and by time (baseline, Month 12, Month 24).

The change from baseline in Child Pugh score (5-15) will be compared between groups with the

Mann-Whitney U test; the analysis will be done for Month 12 and Month 24 separately.

7.2.4 Model of end stage liver disease (MELD)

The change from baseline in MELD score will be compared between groups using a linear regression

model with MELD-change as dependent variable. Independent variables will be group (intervention

or control), baseline MELD score, disease severity in terms of compensated or decompensated state,

and study site. The effect of group will be summarized using estimated group difference with 95% CI,

and a p-value from the t-test. The analysis will be done separately for Month 12 and Month 24 data.

7.2.5 Royal free hospital-nutritional prioritising tool (RFH-NPT)

The risk classes (low, medium, high) will be summarized descriptively showing percentage patients in

each class by group (intervention, control) and by time (baseline, Month 12, Month 24).

The change from baseline in RFH-NPT score (0-7) will be compared between groups with the Mann-

Whitney U test; the analysis will be done for Month 12 and Month 24 separately.

7.2.6 Appearance of decompensation episodes

The probability of appearance will be analysed with a logistic regression model. Independent

variables in the logistic model will be group (intervention or control), if the patient had these

episodes at baseline, disease severity in terms of compensated or decompensated state, and study

site. The effect of group will be summarized using odds ratio with 95% CI, and a p-value for the null

hypothesis of no group effect. The analysis will be done separately for Month 12 and Month 24 data.

7.2.7 Hepatic encephalopathy (HE)

The probability of having a Grade 1 HE diagnosis (pathological result in both PHES and CRT, i.e PHES-

score -4 or lower and CRT-index < 1.9) will be analysed with a logistic regression model. Independent

variables in the logistic model will be group (intervention or control), if the patient had a Grade 1 HE

diagnosis at baseline, disease severity in terms of compensated or decompensated state, and study

site. The effect of group will be summarized using odds ratio with 95% CI, and a p-value for the null

hypothesis of no group effect. The analysis will be done separately for Month 12 and Month 24 data.

7.2.8 Health literacy (HL)

The classes (likely limited literacy, possible limited literacy, adequate literacy) will be summarized

descriptively showing percentage patients in each class by group (intervention, control) and by time

(baseline, Month 12, Month 24).

The change from baseline in NVS score (0-6) will be compared between groups with the Mann-

Whitney U test; the analysis will be done for Month 12 and Month 24 separately.

REFERENCES

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for the SF-36 and SF-12 Health Survey, V.1. Health and Quality of Life Outcomes, 5, 54.

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Hays RD, Sherbourne CD, Mazel RM (1993). The RAND 36-Item Health Survey 1.0. Healthecon, 2, 217-27. Hays RD, Morales LS (2001). The RAND-36 measure of health-related quality of life. Ann Med, 33, 350-7. Hjorth, M, Sjöberg, D, Svanberg, A, Kaminsky, E, Langenskiöld, S, Rorsman F (2018). Nurse-led Clinic for Liver Cirrhotic Patients – Effects on Health-Related Quality of Life: Study Protocol of a Pragmatic Multicentre Randomised Controlled Trial. Submitted manuscript. Jenkinson C (1999). Comparison of UK and US methods for weighting and scoring the SF-36 summary measures. Journal of Public Health Medicine, 21, 372-376. Julious SA (2009). Sample Sizes for Clinical Trials. Chapman & Hall/CRC.

Laucis NC, Hays RD, Bhattacharyya T (2015). Scoring the SF-36 in Orthopaedics: A Brief Guide. J Bone

Joint Surg Am., 97, 1628-1634.

Rannou F et al. (2007). Should aggregate scores of the Medical Outcomes Study 36-item Short Form

Health Survey be used to assess quality of life in knee and hip osteoarthritis? A national survey in

primary care. OsteoArthritis and Cartilage, 15, 1013-1018.

Shah LC, West P, Bremmeyr K, Savoy-Moore RT (2010). Health Literacy Instrument in Family

Medicine: The “Newest Vital Sign” Ease of Use and Correlates. J Am Board Fam Med, 23, 195-203.

Strand V, Burmester GR, Ogale S, Devenport J, John A, Emery P (2012). Improvements in health-

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UKATT Research Team (2005). Effectiveness of treatment for alcohol problems: findings of the

randomised UK alcohol treatment trial (UKATT). BMJ, 331, 541-545.

Van Buuren S (2018). Flexible Imputation of Missing Data. Second Edition. Boca Raton, FL.: Chapman

& Hall/CRC Press.

Ward MM, Guthrie LC, Alba MI (2014). Clinically Important Changes in Short Form 36 Health Survey

Scales for Use in Rheumatoid Arthritis Clinical Trials: The Impact of Low Responsiveness. Arthritis

Care & Research, 66, 1783-1789.

Weissenborn K, Ennen JC, Schomerus H, et al (2001). Neuropsychological characterization of hepatic

encephalopathy. J Hepatol, 34, 768-73.

Wilde-Larsson B, Larsson G, Larsson M, Starrin B (2001). KUPP-boken. Vägledning till frågeformuläret

KUPP, Kvalitet ur patientens perspektiv (in Swedish). Vårdförbundet, Stockholm.

Nurse-led clinic for patients with liver cirrhosis – effects on health-related quality of life Date 17-11-2016

Consent Form

Patient ID:____________________

I hereby confirm that I have read and understood the written information concerning

participation in the research project: Liver Nurse-led Clinic I have been given verbal

information and my questions have been answered. I have had sufficient time in which to

consider my participation.

I consent to:

Participate and that my participation is wholly voluntarily.

I can at any time and without needing to state the reason why, terminate my

participation without it affecting my present and future care and healthcare needs.

My personal data is handled and processed in compliance with the stipulations under

the header Handling of data and confidentiality, in the written information about the

research project.

Patient: Signature of the patient

Date (dated by the patient)

Name, block letters

Nurse Practitioner: I have provided the patient with complete information concerning every aspect of this study.

Signature of nurse providing information

Date (dated by the nurse providing information)

Name, block letters

One copy of the patient information and the signed consent form is given to the patient.