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ORIGINAL PAPER
The place of DPP-4 inhibitors in the treatment algorithmof diabetes type 2: a systematic review of cost-effectiveness studies
Alexandre Baptista1• Ines Teixeira2
• Sonia Romano2• Antonio Vaz Carneiro3
•
Julian Perelman4
Received: 9 October 2015 / Accepted: 30 September 2016 / Published online: 17 October 2016
� Springer-Verlag Berlin Heidelberg 2016
Abstract
Objective To conduct a systematic review of cost-effec-
tiveness, cost-utility, and cost-benefit studies of DPP-4
inhibitors for diabetes treatment versus other antidiabetics.
Methods Three investigators searched the CRD York,
Tufts CEA Registry, and MEDLINE databases through
2015. We reviewed all potentially relevant titles and
abstracts, and screened full-text articles, according to
inclusion criteria. We established a quality score for each
study based on a 35-item list.
Results A total of 295 studies were identified, of which 20
were included. The average quality score was 0.720 on a
0–1 scale. All studies were performed in high- and middle-
income countries, using a 3rd-party payer perspective and
randomized clinical trials to measure effectiveness. Sita-
gliptin, saxagliptin and vildagliptin had an ICER below
25,000 €/QALY, as second-line and as add-ons to met-
formin, in comparison to sulfonylureas. When compared
with sitagliptin, liraglutide (GLP-1 receptor agonist) had an
ICER of up to 22,724 €/QALY for the 1.2-mg dosage, and
up to 32,869 €/QALY for the 1.8-mg dosage. Insulin
glargine was dominant when compared with sitagliptin.
Conclusions According to the WHO threshold applied to
the country and year of each study, DPP-4 inhibitors were
highly cost-effective as second-line, as add-ons to met-
formin, in comparison with sulfonylureas. More recent
therapies (GLP-1 receptor agonists and insulin glargine)
were highly cost-effective in comparison to DPP-4 inhi-
bitors. These results were obtained, however, on the basis
of a limited number of studies, relying on the same few
clinical trials, and financed by manufacturers. Further
independent research is needed to confirm these findings.
Keywords Diabetes � Cost-effectiveness studies � DPP-4inhibitors � Systematic review
JEL Classification I1
Introduction
Diabetes is one of the largest global health emergencies of the
twenty-first century. In addition to the 415 million adults
estimated to have diabetes in 2015, there are 318 million
adults with impaired glucose tolerance, which puts them at
high risk of developing the disease in the future [1]. Also,
according to the International Diabetes Federation (IDF), 5
million people died of diabetes in 2015.Uppermiddle-income
and high-income countries are those where the prevalence of
diabetes is highest amongst those 20–79 years old [1].
Regarding the economic burden, the majority of high-in-
come countries spend between 5 and 20 % of their total health
expenditure on diabetes [1]. In France total direct costs reached
12.9 € billion in 2010. In Germany the total direct cost burden
& Alexandre Baptista
alexcalaca@hotmail.com
1 Unit of Epidemiology of the Faculty of Medicine of Lisbon,
Edifıcio Egas Moniz, Faculdade de Medicina da
Universidade de Lisboa, Av. Professor Egas Moniz,
1649-028 Lisbon, Portugal
2 Centre for Health Evaluation and Research (CEFAR),
National Association of Pharmacies Group, R. Marechal
Saldanha, 1., 1249-069 Lisbon, Portugal
3 Center for Evidence-Based Medicine (CEMBE) of the
Faculty of Medicine at the University of Lisbon, Faculdade
de Medicina da Universidade de Lisboa, Av. Professor Egas
Moniz, 1649-028 Lisbon, Portugal
4 Escola Nacional de Saude Publica and Centro de
Investigacao em Saude Publica, Universidade Nova de
Lisboa, Avenida Padre Cruz, 1600-5605 Lisbon, Portugal
123
Eur J Health Econ (2017) 18:937–965
DOI 10.1007/s10198-016-0837-7
arising from treatment has been estimated at 43.2 € billion for2010. Total direct cost in the UK has been estimated at £13.8
billion (20.2 € billion using the base year rate of exchange) [2].In 2012 the total estimated cost of diagnosed diabetes in the
United States was $245 billion, including $176 billion in direct
medical costs and $68 billion in indirect costs [3]. These indi-
rect costs included increased absenteeism ($5 billion) and
reduced productivity while at work ($20.8 billion) for the
employed population, reduced productivity for those not in the
labour force ($2.7 billion), inability to work as a result of dis-
ease-related disability ($21.6 billion), and lost productive
capacity due to early mortality ($18.5 billion). On average,
medical expenditures among people with diabetes are approx-
imately 2.3 times higher than among thosewithout diabetes [3].
As a result, diabetes has been considered to be a research
priority, leading to a large increase in recent years in the
number of glucose lowering medicines for treating type 2
diabetes. Dipeptidyl peptidase-4 inhibitors (DPP-4 inhibi-
tors) are a relatively new oral hypoglycaemic drugs group.
Among these, sitagliptin, vildagliptin, saxagliptin, linaglip-
tin, and alogliptin are currently approved by theUS Food and
Drug Administration and the European Medicines Agency,
while others are awaiting approval or are in development. In
practice, the American Diabetes Association (ADA) and the
European Association for the Study of Diabetes (EASD)
clinical guideline for type 2 diabetes, suggested adding a
DPP-4 inhibitor, insulin, glucagon-like peptide 1 (GLP-1)
receptor agonists, sodium-glucose cotransporter 2 (SGLT2)
inhibitors, thiazolidinedione, or a sulfonylurea as second-
line treatment to first-line metformin [4].
Drug choice is based on patient preferences as well as
various patient, disease, and drug characteristics,with the goal
being to reduce glucose concentrationswhile minimizing side
effects, especially hypoglycemia [4]. However, the guideline
did not incorporate cost-effectiveness considerations regard-
ing the newest medicines, such as DPP-4 inhibitors or SGLT2
inhibitors, which are nevertheless essential as an instrument to
help resource allocation decisions. The importance is also
emphasized in the current context of economic recession and
pressure on tight public budgets, and considering the high
epidemiological and economic burden of the disease.
The objective of this study was to conduct a systematic
review of cost-effectiveness, cost-utility, and cost-benefit
studies of DPP-4 inhibitors versus other antidiabetics as
treatment of type 2 diabetesmellitus (T2DM), and understand
the implications for guidelines, policy, and further research.
Methods
This review followed the methodology recommended by
the Preferred Reporting Items for Systematic Reviews and
Meta-Analyses (PRISMA) statement [5], and by the Centre
for Reviews and Dissemination (CRD) of the University of
York for systematic reviews of economic evaluations [6].
The literature review was based on a search for journal
articles and abstracts in Medline and the CRD database
from 1996 to 2015, and NHS EED, the Health Economic
and Evaluations Database (HEED), and the Tufts CEA
Registry to 2015. Google scholar was also searched. In
addition, relevant grey literature, including models pre-
sented at recent professional meetings available solely as
abstracts in conference proceedings, were also explored.
Searches for economic outcomes were conducted using
a variety of terms from the medical literature to describe
the intervention, the comparator, the target patient popu-
lation, the outcomes, and the study design. A combination
of these search terms was also used for the survey. The
search terms were: sitagliptin, vildagliptin, saxagliptin,
linagliptin, alogliptin, DPP-4 inhibitors, cost-effectiveness,
cost-utility, and cost-benefit. The search strings used for
the PubMed searches are available in the Appendix.
Firstly, three investigators independently reviewed all
potentially relevant titles and abstracts (1st screening) and
subsequently screened full-text articles (2nd screening),
according to pre-established inclusion criteria. Inclusion
criteria followed the PICOS approach [7]. PICOS is the
acronym for population, intervention, comparator, out-
comes, and study design. We followed the PRISMA
flowchart in reporting study selection, as suggested by the
PRISMA statement [5].
Cost-effectiveness, cost-utility studies, and cost-benefit
studies should be available as a full-text publication and
published in English, French, Spanish, or Portuguese lan-
guages. We excluded the incomplete economic evalua-
tions, namely: cost consequence analyses (4 studies);
patient reported outcomes (PRO) studies (1 study); the
studies on sub-populations that cannot be generalized (2
studies); the health technology assessment agencies reports
that were not submitted to peer-review (36 studies); studies
out of scope (162), and only abstracts (66).
Secondly, the three investigators used a standardized
data abstraction template, as recommended by the CRD of
the University of York for systematic reviews of economic
evaluations [6], to independently extract data from each
study, with disagreements being resolved by discussion.
For each study, the information was extracted and recorded
in a specific template, provided in the Appendix.
Thirdly, a critical appraisal of the methodology and
reporting was performed focusing on key quality issues,
such as: methods of deriving the effectiveness data; mea-
surement and valuation of resource data; measurement and
valuation of health benefits (utilities); method of synthe-
sizing the costs and effects; analysis of uncertainty; and
external validity. To do so, we used the 35-item version of
the BMJ checklist [7]. A score in percentage was attributed
938 A. Baptista et al.
123
to each study, calculating the affirmative answers in the
checklist. Three investigators performed all quality
assessments independently, with disagreement resolved
through discussion.
Finally, we reported summary statistics and qualitative
(descriptive) syntheses of identified cost-effectiveness,
cost-utility, and cost-benefit studies in the form of sum-
mary tables. Categorical data were reported as percentages,
while continuous data were reported as means with confi-
dence intervals or standard deviations. A comparative
qualitative synthesis was performed to explore relation-
ships within and between studies.
Results
The literature search initially identified 295 citations
(Fig. 1). Of these, 24 cost-effectiveness studies were
accepted after the 1st screening, and 20 were accepted after
the 2nd screening.
Characteristics of the selected publications
Main details of the selected studies are presented in
Table 1. We organized these results according to the tim-
ing of the market introduction, that is: (1) sitagliptin versus
sulfonylurea; (2) saxagliptin versus sulfonylurea; (3) sax-
agliptin versus insulin; (4) saxagliptin versus pioglitazone;
(5) vildagliptin versus sulfonylurea; (6) liraglutide versus
sitagliptin; (7) insulin glargine versus sitagliptin; and (8)
GLP-1 receptor agonists versus DPP-4 inhibitors.
The studies were all performed in high-income and
middle-income countries (using the World Bank classifi-
cation) [8]. The high-income countries were Austria,
Canada, Finland, Germany, Greece, Poland, Portugal,
Spain, Sweden, United Kingdom (UK), and United States
(US). The middle-income countries were Argentina and
Brazil. These are very recent studies with retrieval of data:
one study from 2014, four studies from 2013, five studies
from 2012, two studies from 2011, one study from 2010,
four studies from 2009, two studies from 2008, and one
1st screening
2nd screening
Relevant titles and abstracts identified after duplicated removed n= 295
Full copies assessed and retrieved for eligibility n= 24
Excluded n = 271 Agencies reports = 36 Sub-populations= 2 PRO studies = 1 Cost consequence study =4 Out of scope= 162 Only abstracts =66
Excluded n= 4 Out of scope = 4
Studies included in the review n= 20
Relevant titles and abstracts identified n= 303
Flowchart of the literature search
Fig. 1 Flowchart of the literature search
The place of DPP-4 inhibitors in the treatment algorithm of diabetes type 2: a systematic… 939
123
Ta
ble
1Characteristicsoftheselected
publications
Reference/country/authors
(publicationyear)
Yearof
retrieval
ofdata
Population
Interventions,designandtime-horizon
Costs,benefits,discountrate
andperspective
Score
[12]/6Europeancountries
(Austria,
Finland,
Portugal,Spain,Scotland-
UK,Sweden)/Schwarz
etal.(2008)
2007
Meanage56.7–64.9
years
MeanHbA1c7.5–8.09%
Sitagliptin(?
Met)vsrosiglitazoneor
sulfonylurea(?
Met)
Cost-utility
analysis:
discreteevent
simulation(JADEmodel)
Tim
e-horizon:patientlifetime
Directcost:drugs,adverse
events,
(hypoglycaem
ia,weight),macro-and
microvascularcomplications
Benefits:QALY
Discountrate:Austria/Sweden
3%;Spain6%;
Finland/Portugal
5%;Scotland3.5
%(costs
andbenefits)
Perspective:
3rd
party
payer
0.714
[13]/Portugal
/Pereira
etal.
(2012)
2010
MeanHbA1c6.5–11%
Sitagliptin(?
Met)vssulfonylurea
(?Met)
Cost-utility
analysis:
discreteevent
simulation(JADEmodel)
Tim
e-horizon:50years
(patientlifetime)
Directcost:drugs,macro-andmicrovascular
complications,hypoglycaem
ia
Benefits:QALY
Discountrate:5%
costsandbenefits
(0–3%
SA)
Perspective:
societal
(butonly
withdirectcosts)
0.629
[14]/Argentina/Elgartet
al.
(2013)
2009
Meanage64years
Proportionofmen
53%
MeanHbA1c7.7
%
Meandurationofdiabetes
10.5
years
Saxagliptin(?
Met)vssulfonylurea
(?Met)
Cost-utility
analysis:
discreteevent
simulation(Cardiffdiabetes
model)
Tim
e-horizon:20years
Directcost:drugs,adverse
events,macro-and
microvascularcomplications
Benefits:QALY
andLYG
Discountrate:3.5
%costsandbenefits
Perspective:
3rd
party
payer
0.829
[15]/Germany
/Erhardtet
al.
(2012)
2009
Meanage57.55years
Proportionofmen
52%
MeanHbA1c7.65%
Meandurationofdiabetes
5.4
years
Saxagliptin(?
Met)vssulfonylurea
(?Met)
Cost-utility
analysis:
discreteevent
simulation(Cardiffdiabetes
model)
Tim
e-horizon:40years
(patientlifetime)
Directcost:medicines,hypoglycaem
ia
treatm
ent,diabetes
relatedcomplications
Benefits:QALY
andLYG
Discountrate:3%
costsandbenefits(0,5,7and
10%
SA)
Perspective:
3rd
party
payer
0.714
[16]/Sweden/Granstrom
etal.(2012)
2008
Meanage57.55years
Proportionofmen
52%
MeanHbA1c7.65%
Meandurationofdiabetes
5.4
years
Saxagliptin(?
Met)vssulfonylurea
(?Met)
Cost-utility
analysis:
discreteevent
simulationmodel
Tim
e-horizon:patientlifetime
Directcost:drugs,BGSM,macro-and
microvascularcomplications,hypoglycaem
ia
Benefits:QALY
andLYG
Discountrate:3%
costsandbenefits
Perspective:
3rd
party
payer
0.771
[17]/US/Bergenheim
etal.
(2012)
2009
Meanage60years
Proportionofmen
48%
MeanHbA1cNA
Meandurationofdiabetes
5.4
years
Saxagliptin(?
Met)vssulfonylurea
(?Met)
Cost-utility
analysis:
discreteevent
simulation(Cardiffdiabetes
model)
Tim
e-horizon:5–40years
(patient
lifetime)
Directcost:drugs,macro-andmicrovascular
complications
Benefits:QALY
Discountrate:3%
costsandbenefits
Perspective:
3rd
party
payer
0.600
940 A. Baptista et al.
123
Ta
ble
1continued
Reference/country/authors
(publicationyear)
Yearof
retrieval
ofdata
Population
Interventions,designandtime-horizon
Costs,benefits,discountrate
andperspective
Score
[18]/Portugal/Carvalho
etal.(2014)
2014
Meanage53years
Proportionofmen
64.4
%
MeanHbA1c7.0
%
Meandurationofdiabetes
0years
Saxagliptin(?
Met)vssulfonylurea
(?Met)
Cost-utility
analysis:
discreteevent
simulation(Cardiffdiabetes
model)
Tim
e-horizon:40-yeartime-horizon
(patientlifetime)
Directcost:medicines,hypoglycaem
ia
treatm
ent,diabetes
relatedcomplications
Benefits:QALY
andLYG
Discountrate:5%
costsandbenefits
Perspective:
societal
(productivityloss
included
for1styear)
0.829
[19]/Poland/Grzeszczak
etal.(2012)
2009
Meanage52years
Proportionofmen
48%
MeanHbA1c7.9
%
Meandurationofdiabetes
1.7
years
Saxagliptin(?
Met/sulfonylurea)
vsNPH
insulin(?
Met/sulfonylurea)
Cost-utility
analysis:
model
(long-term
Cardiffdiabetes
model)
Tim
e-horizon:40-year(patientlifetime)
Directcost:drugs,macro-andmicrovascular
complications,hypoglycaem
ia
Benefits:QALY
Discountrate:5%
costsand3.5
%benefits
Perspective:
3rd
party
payer
0.686
[20]/Brazil/Nitaet
al.
(2012)
2011
Meanage59.77years
Proportionofmen
42%
MeanHbA1c6.47%
Meandurationofdiabetes
7.27years
Saxagliptin(?
Met)vsrosiglitazoneor
pioglitazone(?
Met)
Cost-utility
analysis:
discreteevent
simulationmodel
(UKPDS)
Tim
e-horizon:patientlifetime
Directcost:hospitalizationandtreatm
entof
adverse
advents
Benefits:QALY
andLYG
Discountrate:5%
costs
Perspective:
privatehealthcare
system
0.571
[21]/Portugal/Viriato
etal.
(2014)
2013
Meanage63years
Proportionofmen
52%
MeanHbA1c7.2
%
Meandurationofdiabetes
9.13years
MeanBMI31.39kg/m
2
Vildagliptin(?
Met)vssulfonylurea
(?Met)
Cost-utility
analysis:
patientlevel
simulationmodel
(UKPDS)
Tim
e-horizon:40years
(patientlifetime)
Directcost:drugs,macro-andmicrovascular
complications,hypoglycaem
ia
Benefits:QALY
andLYG
Discountrate:5%
costsandbenefits
(0–8%
SA)
Perspective:
3rd
party
payer
0.771
[22]/US/Liet
al.(2014)
2010-2012
Meanage54years
(liraglutide),58years
(sitagliptin)
Proportionofmen
43.9
%
(liraglutide),61.8
%
(sitagliptin)
Liraglutidevssitagliptin
Retrospectiveobservational
study
Tim
e-horizon:3years
Directcost:medicines,diabetes
related
complications
Benefits:%
pointsin
reductionofHbA1c
(liraglutide-0.95%,sitagliptin-0.63%,
Difference
0.31%)
Discountrate:N/A
Perspective:
3rd
party
payer
0.485
[23]/Sweden/CarlssonK,
PerssonU.(2014)
2013
Meanage56years
MeanHbA1c8.4
%
Meandurationofdiabetes
6years
MeanBMI32.6
kg/m
2
Liragutide1.2
mg(?
Met)vssitagliptin
100mg(?
Met)
Costutility
analysis:Markovmodel
(IHE
cohortmodel
oftype2
diabetes)
Tim
e-horizon:40years
(patientlifetime)
Directcosts:
medicines,diabetes
related
complications,hypoglycaem
ia
Productionloss:dueto
hypoglycaem
iaand
diabetic
complications
Discountrate:3%
costsandbenefits
Perspective:
societal
0.800
The place of DPP-4 inhibitors in the treatment algorithm of diabetes type 2: a systematic… 941
123
Ta
ble
1continued
Reference/country/authors
(publicationyear)
Yearof
retrieval
ofdata
Population
Interventions,designandtime-horizon
Costs,benefits,discountrate
andperspective
Score
[24]/Greece/Tzanetakos
etal.(2014
)2013
Meanage64.5
years
Proportionofmen
51.5
%
MeanHbA1c8.2
%
Meandurationofdiabetes
10.4
years
MeanBMI30.4
kg/m
2
Liragutide1.2
mg(?
Met)vssitagliptin
100mg(?
Met)
Cost-utility
analysis:
Markov(CORE
diabetes
model)
Tim
e-horizon:patientlifetime
Directcost:medicines,diabetes
related
complications,hypoglycaem
ia
Benefits:QALY
Discountrate:3.5
%costsandbenefits
(0–6%
SA)
Perspective:
3rd
party
payer
0.828
[25]/US/Langer
etal.
(2013
)2012
Meanage55.3
years
Proportionofmen
52.9
%
MeanHbA1c8.4
%
Meandurationofdiabetes
6.0
years
MeanBMI32.8
kg/m
2
Liraglutide1.2
mgand1.8
mg(?
Met)vs
sitagliptin100mg(?
Met)
Cost
effectivenessanalysis
Tim
e-horizon:1year
Directcost:medicines
Benefits:%
patients
reachingthecomposite
endpoint(H
bA1c\7.0
%,nohypoglycaem
ia,
noweightgain)
Discountrate:0%
(1yeartime-horizon)
Perspective:
3rd
party
payer
0.657
[26]/Spain/Perez
etal.
(2015)
2012
Meanage55.3
years
MeanHbA1c8.4
%
Meandurationofdiabetes
6.0
years
MeanBMI32.8
kg/m
2
Liraglutide1.8
mg(?
Met)
vssitagliptin100mg(?
Met)
Cost-utility
analysis:
Markov(CORE
diabetes
model)
Tim
e-horizon:patientlifetime
Directcosts:medicines,self-monitoringof
bloodglucose,diabetes
relatedcomplications
Benefits:QALY
Discountrate:3%
costsandbenefits
(0–5%
SA)
Perspective:
3rd
party
payer
0.685
[27]/Spain/Rayaet
al.
(2013)
2012
Meanage55.3
years
Proportionofmen
52.9
%
MeanHbA1c8.4
%
Meandurationofdiabetes
6.0
years
MeanBMI32.8
kg/m
2
Liraglutide1.2
mg(?
Met)
vssitagliptin100mg(?
Met)
Cost-utility
analysis:
Markov(CORE
diabetes
model)
Tim
e-horizon:patientlifetime
Directcost:medicines,self-monitoringofblood
glucose,diabetes
relatedcomplications
Benefits:QALY
Discountrate:3%
costsandbenefits
(0–5%
SA)
Perspective:
3rd
party
payer
0.714
[28]/UK/Davieset
al.
(2012)
2008
Meanage55.3
years
Proportionofmen
52.9
%
MeanHbA1c8.4
%
Meandurationofdiabetes
6.0
years
MeanBMI32.8
kg/m
2
Liraglutide1.2
mgand1.8
mg(?
Met)vs
sitagliptin100mg(?
Met)
Cost-utility
analysis:
Markov(CORE
diabetes
model)
Tim
e-horizon:patientlifetime
Directcost:medicines,self-monitoringofblood
glucose,diabetes
relatedcomplications
Benefits:QALY
Discountrate:3.5
%costsandbenefits
(0–6%
SA)
Perspective:
3rd
party
payer
0.686
[29]/US/Lee
etal.(2012)
2011
Meanage55.3
years
Proportionofmen
52.9
%
MeanHbA1c8.4
%
Meandurationofdiabetes
6.0
years
MeanBMI32.8
kg/m
2
Liraglutide1.2
mgand1.8
mg(?
Met)
vssitagliptin100mg(?
Met)
Cost-utility
analysis:
Markov(CORE
diabetes
model)
Tim
e-horizon:35years
Directcost:medicines,macro-and
microvascularcomplications,hypoglycaem
ia
Benefits:QALY
andLYG
Discountrate:3%
costsandbenefits
(0–6%
SA)
Perspective:
3rd
party
payer
0.743
942 A. Baptista et al.
123
study from 2007. There were four studies with a societal
perspective and sixteen studies with a 3rd-party payer
perspective. The societal perspective is the broadest and
most complex perspective, in which ideally the estimated
costs reflect the true social opportunity costs, while the 3rd-
party payer perspective reflects only the costs borne by that
payer. Costs measurements should be fully transparent and
the perspective adopted defines the scope of the analysis,
with different countries having different guidelines for this
issue [9].
One single study used an observational study providing
real-world effectiveness data. The majority of the studies
were based on one randomized controlled trial. Sitagliptin
was assessed in eleven studies, saxagliptin in seven studies,
vildagliptin in one study, and the three DPP-4 inhibitors
(sitagliptin, saxagliptin, and vildagliptin) were also asses-
sed jointly versus two GLP-1 receptor agonists (liraglutide
and exenatide) in one study.
All but one study evaluated these drugs as add-on to
metformin monotherapy as second-line, that is, for those
patients who did not achieve glycaemic control with met-
formin as first-line. One study did not specify clearly
whether the drug was assessed as second-line. Finally, the
majority of studies included in this review were of high
quality (average score 0.720 on a 0–1 scale, with a range
between 0.485 and 0.885).
The World Health Organization (WHO) threshold for
cost-effectiveness was used as Ref. [10]. This criterion
defined a strategy as cost-effective when the cost per
DALY averted or QALY gained was less than 3 times the
gross domestic product (GDP) per capita, and as very cost-
effective if it was less than the GDP per capita [11]. The
threshold was calculated for each study on the basis of the
year and country where the study was performed.
Main results of the selected publications
These findings are reported in Table 2, according to the
timing of the market introduction mentioned in the Meth-
ods section. More complete details of the studies, including
the characteristics of the base population, are shown in
Table A.1, in the Appendix.
First, we compared sitagliptin with sulfonylureas
[12, 13]. The studies used the Januvia Diabetes Economic
model (JADE). The JADE model is a discrete event sim-
ulation model developed to project the long-term impacts
of different interventions on diabetes related outcomes
[32]. It is an extension of the more well-known United
Kingdom Prospective Diabetes Study (UKPDS) outcomes
model, to which it adds the possibility of modelling the
effect of different treatment regimes in terms of health
outcomes, costs, and quality of life. The UKPDS appears as
less complete than the IMS core model—the most well-Ta
ble
1continued
Reference/country/authors
(publicationyear)
Yearof
retrieval
ofdata
Population
Interventions,designandtime-horizon
Costs,benefits,discountrate
andperspective
Score
[30]/Canada/Brownet
al.
(2014)
2012
Meanage54years
Proportionofmen
51%
MeanHbA1c8.5
%
Meandurationofdiabetes
4.5
years
MeanBMI31.1
kg/m
2
Insulinglargine(?
Met)vssitagliptin
(?Met)
Cost–utility
analysis:
Markov(CORE
diabetes
model)
Tim
e-horizon:patientlifetime
Directcost:medicines,diabetes
related
complications,hypoglycaem
ia
Benefits:QALY
Discountrate:5%
costsandbenefits
(0%
SA)
Perspective:
3rd
party
payer
0.800
[31]/Sweden/Kiadaliriet
al.
(2014)
2013
Meanage64.7
years
Proportionofmen
57.5
%
MeanHbA1c7.7
%
Meandurationofdiabetes
5.6
years
MeanBMI30.9
kg/m
2
GLP-1
agonists
(?Met)vsDPP-4
inhibitors
(?Met)vsNPH
insulin
(?Met)
Cost-utility
analysis:
Markovmodel
(IHECM-T2DM)
Tim
e-horizon:35years
(patientlifetime)
Directcosts:healthcare
costs
Productivitylosses,net
consumptionlosses
Benefits:QALY
Discountrate:3%
costsandbenefits
(0–5%
SA)
Perspective:
societal
0.885
N/A
notapplicable,Met
metform
in,SAsensitivityanalysis,JA
DEJanuvia
diabetes
economic
model,UKPDSUnited
Kingdom
prospectivediabetes
study,IH
ECM-T2DM
Institute
forHealth
Economicscohortmodel
forT2DM,BGSM
bloodglucose
self-m
onitoring
The place of DPP-4 inhibitors in the treatment algorithm of diabetes type 2: a systematic… 943
123
Ta
ble
2Resultsoftheselected
publications
Reference/country/authors
(publicationyear)
Interventionvscomparator
Costs(€)a
Clinical
outcomes/QALYs
Increm
entalcost-effectiveness
ratio(ICER)
[12]/6Europeancountries
(Austria,
Finland,Portugal,
Spain,UK,Sweden)/Schwarz
etal.(2008)
Sitagliptin(?
Met)vs
rosiglitazoneorsulfonylurea
(?Met)
Sitagliptinvssulfonylurea
Difference
331€to
1097€
across
countries
Difference
0.037–0.095
QALYsacross
countries
Austria:
20,350€/QALY
Finland:13,737€/QALY
Portugal:5949€/QALY
Spain:13,440€/QALY
UK:11,547€/QALY
Sweden:12,219€/QALY
5949€–20,350€/QALYacross
countries
[13]/Portugal/Pereira
etal.
(2012)
Sitagliptin(?
Met)vs
sulfonylurea(?
Met)
Sitagliptin44,821€
Sulfonylurea44,283€
Difference
538€
Sitagliptin8.222QALYs
Sulfonylurea8.173QALYs
Difference
0.048QALYs
11,198€/QALY
[14]/Argentina/Elgartet
al.
(2013)
Saxagliptin(?
Met)vs
sulfonylurea(?
Met)
Saxagliptin10,883€
[US$12,327.7]
Sulfonylurea9441€
[US$10,694.8]
Difference
1441€
[US$1632.9]
Saxagliptin9.54QALYs
Sulfonylurea9.32QALYs
Difference
0.22QALYs
6510€[U
S$7374]/QALY
[15]/Germany/Erhardtet
al.
(2012)
Saxagliptin(?
Met)vs
sulfonylurea(?
Met)
Saxagliptin38,163€
Sulfonylurea36,550€
Difference
1613€
Saxagliptin13.42QALYs
Sulfonylurea13.31QALYs
Difference
0.12QALYs
13,931€/QALY
[16]/Sweden/Granstrom
etal.
(2012)
Saxagliptin(?
Met)vs
sulfonylurea(?
Met)
Saxagliptin12,328€[116,221
SEK]
Sulfonylurea11,321€
[106,727SEK]
Difference
1006€[9,484SEK]
Saxagliptin12.56QALYs
Sulfonylurea12.46QALYs
Difference
0.10QALYs
9608€[91,260SEK]/QALY
[17]/US/Bergenheim
etal.
(2012)
Saxagliptin(?
Met)vs
sulfonylurea(?
Met)
Saxagliptin57,503€
[US$65,139]
Sulfonylurea55,056€
[US$62,367]
Difference
2447€[U
S$2772]
Saxagliptin11.02QALYs
Sulfonylurea8.37QALYs
Difference
2.65QALYs
924€[U
S$1047]/QALY
[18]/Portugal/Carvalhoet
al.
(2014)
Saxagliptin(?
Met)vs
sulfonylurea(?
Met)
Saxagliptin21,959€
Sulfonylurea21,198€
Difference
761€
Saxagliptin11.80QALYs
Sulfonylurea11.65QALYs
Difference
0.14QALYs
5307€/QALY
944 A. Baptista et al.
123
Ta
ble
2continued
Reference/country/authors
(publicationyear)
Interventionvscomparator
Costs(€)a
Clinical
outcomes/QALYs
Increm
entalcost-effectiveness
ratio(ICER)
[19]/Poland/Grzeszczaket
al.
(2012)
Saxagliptin(?
Met/SU)vs
NPH
insulin(?
Met/SU)
Saxagliptin(?
Met)7765€
[PLN
31,394]
Insulin(?
Met)6858€[PLN
27,730]
Difference
906€[PLN
3663]
Saxagliptin(?
SU)7963€
[PLN
32,198]
Insulin(?
SU)7090€[PLN
28,668]
Difference
873€[PLN
3,529]
Saxagliptin?
Met
13.33
QALYs
Insulin?
Met
13.20QALYs
Difference
0.13QALYs
Saxagliptin?
SU
13.32
QALYs
Insulin?
SU
13.18QALYs
Difference
0.14QALYs
(?Met)6790€[PLN
27,454]/
QALY
(?SU)6100€[PLN
24,663]/
QALY
[20]/Brazil/Nitaet
al.(2012)
Saxagliptin(?
Met)vs
rosiglitazoneorpioglitazone
(?Met)
Saxagliptin9679€[R$33,023]
Pioglitazone10,850€
[R$37,019]
Difference
-1171€[R$3996]
Saxagliptin10.55QALYs
Pioglitazone10.42QALYs
Difference
0.13QALYs
Dominant
[21]/Portugal/Viriato
etal.
(2014)
Vildagliptin(?
Met)vs
sulfonylurea(?
Met)
Vildagliptin14,409€
Sulfonylurea13,248€
Difference
1161€
Vildagliptin5.7681QALYs
Sulfonylurea5.6401QALYs
Difference
0.1279QALYs
9072€/QALY
[22]/US/Liet
al.(2014)
Liraglutidevssitagliptin
Liraglutide1403€[U
S$1589]
Sitagliptin1809€[U
S$2049]
Difference
-406€[U
S$-460]
Liraglutide-0.95%
Sitagliptin-0.63%
Difference
-0.31%
%points
inreductionof
HbA1c
NA
cost
per
patient
successfullytreatedto
the
target
composite
endpoint
[23]/Sweden/Carlssonand
Persson(2014)
Liraglutide1.2
mg(?
Met)vs
sitagliptin100mg(?
Met)
Liraglutide101,052€–
149,673€
[952,648–1411,014SEK]
Sitagliptin95,547€–
143,563€
[900,750–1353,411SEK]
Difference
5505€–
6110€
[51,898-57,603SEK]
Liraglutide8.55–10.53QALYs
Sitagliptin8.21–10.15QALYs
Difference
0.33–0.38QALYs
15,780€-17,060€[148,766-
160,827SEK]/QALY
[24]/Greece/Tzanetakoset
al.
(2014)
Liragutide1.2
mg(?
Met)vs
sitagliptin100mg(?
Met)
Liraglutide39,524€
Sitagliptin36,727€
Difference
2797€
Liraglutide9.24QALYs
Sitagliptin9.05QALYs
Difference
0.19QALYs
15,101€/QALY
The place of DPP-4 inhibitors in the treatment algorithm of diabetes type 2: a systematic… 945
123
Ta
ble
2continued
Reference/country/authors
(publicationyear)
Interventionvscomparator
Costs(€)a
Clinical
outcomes/QALYs
Increm
entalcost-effectiveness
ratio(ICER)
[25]/US/Langer
etal.(2013)
Liraglutide1.2
and1.8
mg
(?Met)vssitagliptin100mg
Liraglutide1.2
mg9123€
[US$10,335]
Liraglutide1.8
mg10,377€
[US$11,755]
Sitagliptin14,882€
[US$16,858]
Difference
1.2
mg5759€
Difference
1.8
mg4505€
Liraglutide1.2
mg38.9
%
Liraglutide1.8
mg49.9
%
Sitagliptin100mg18.6
%
%ofpatientsreachingendpoint
NA,cost
per
patient
successfullytreatedto
the
target
composite
endpoint
[26]/Spain/Perez
etal.(2015)
Liraglutide1.8
mg(?
Met)vs
sitagliptin100mg(?
Met)
Liraglutide56,628€
Sitagliptin52,450€
Difference
4177€
Liraglutide9.24QALYs
Sitagliptin8.84QALYs
Difference
0.4
QALYs
10,436€/QALY
[27]/Spain/Rayaet
al.(2013)
Liraglutide1.2
mg(?
Met)vs
sitagliptin100mg(?
Met)
Liraglutide54,684€
Sitagliptin52,387€
Difference
2297€
Liraglutide9.04QALYs
Sitagliptin8.87QALYs
Difference
0.17QALYs
13,266€/QALY
[28]/UK/Davieset
al.(2012)
Liraglutide1.2
and1.8
mg
(?Met)vssitagliptin100mg
(?Met)
Liraglutide1.2
mg30,222€
[£21,793]
Liraglutide1.8
mg32,138€
[£23,175]
Sitagliptin27,667€[£19,951]
Difference
(1.2
mg)2554€
[£1842]
Difference
(1.8
mg)4471€
[£3224]
Liraglutide1.2
mg7.52
QALYs
Liraglutide1.8
mg7.64
QALYs
Sitagliptin100mg7.34
QALYs
Difference
(1.2
mg)0.19
QALYs
Difference
(1.8
mg)0.31
QALYs
(1.2
mg)13,661€[£9851]/
QALY
(1.8
mg)14,513€[£10,465]/
QALY
[29]/US/Lee
etal.(2012)
Liraglutide1.2
and1.8
mg
(?Met)vssitagliptin100mg
(?Met)
Liraglutide1.2
mg71,896€
[US$81,444]
Liraglutide1.8
mg78,127€
[US$88,502]
Sitagliptin66,438€[$76,262]
Difference
(1.2
mg)4575€
[US$5182]
Difference
(1.8
mg)11,689€
[US$13,241]
Liraglutide1.2
mg8.83
QALYs
Liraglutide1.8
mg8.98
QALYs
Sitagliptin100mg8.62
QALYs
Difference
(1.2
mg)0.20
QALYs
Difference
(1.8
mg)0.36
QALYs
(1.2
mg)22,724€
[US$25,742]/QALY
(1.8
mg)32,869€
[US$37,234]/QALY
946 A. Baptista et al.
123
Ta
ble
2continued
Reference/country/authors
(publicationyear)
Interventionvscomparator
Costs(€)a
Clinical
outcomes/QALYs
Increm
entalcost-effectiveness
ratio(ICER)
[30]/Canada/Brownet
al.
(2014)
Insulinglargine(?
Met)vs
sitagliptin(?
Met)
Insulinglargine33,409€
[$CAD
45,556]
Sitagliptin33,469€[$CAD
45,638]
Difference
-1052€[$CAD
-1434]
Insulinglargine8.815QALYs
Sitagliptin8.739QALYs
Difference
0.076QALYs
Dominant
–13,847€[$CAD
-
18,882]/QALY
[31]/Sweden/Kiadaliriet
al.
(2014)
GLP-1
agonists
(?Met)vs
DPP-4
inhibitors
(?Met)and
DPP-4
inhibitors
(?Met)vs
NPH
insulin(?
Met)
GLP-1
agonists
229,430€
[2162,907SEK]
DPP-4
inhibitors
225,732€
[2128,042SEK]
NPH
Insulin225,102€
[2122,105SEK]
Difference
(GLP-1
vsDPP-4
inhibitors)3698€[34,865
SEK]
Difference
(DPP-4
inhibitors
vsNPH
Insulin630€[5936
SEK]
GLP-1
agonists
4.75QALYs
DPP-4
inhibitors
4.65QALYs
NPH
Insulin4.50QALYs
Difference
(GLP-1
vsDPP-4)
0.10QALYs
Difference
(DPP-4
vsNPH
Insulin)0.15QALYs
GLP-1
vsDPP-4:37,463€
[353,172SEK]/QALY
DPP-4
vsNPH
insulin
3824€[36,050SEK]/QALY
Met
metform
in,SU
sulfonylurea,
NAnotavailable,PSAprobabilisticsensitivityanalysis,TZD
thiazolidinedione
aExchangerateswereassessed
on15May
2015usingtheconvertingtoolofthePortugueseNational
Bank(https://www.bportugal.pt/en-U
S/Estatisticas/Dominios%
20Estatisticos/Estatisti
casC
ambiais/Pages/Taxasdereferenciadiarias.aspx)
The place of DPP-4 inhibitors in the treatment algorithm of diabetes type 2: a systematic… 947
123
Ta
ble
3Detaileddescriptionsofstudyresults
References
Yearofretrieval
ofdata
Country/Authors
(pubyear)
Interventions
Perspective
Populationstudied
Sitagliptin(?
metform
in)vssulfonylurea(?
metform
in)
Schwarzet
al.
(2008)[12]
2007
6Europeancountries
(Austria,
Finland,
Portugal,Spain,Scotland-
UK,Sweden)
Schwarzet
al.(2008)
Sitagliptinvsrosiglitazoneor
sulfonylureaallas
add-onsto
metform
in
3rd
party
payer
in6European
countries
Meanagefrom
56.7
(Finnish
women)to
64.9
years
(Scottishmen
andwomen)
MeanHbA1cfrom
7.5
(Portugal
andFinland)to
8.09%
(Spanishmen)
BMIfrom
26.1
(Austrian
men)
to34.6
(Portuguesemen)
Pereira
etal.
(2012)[13]
2010
Portugal
Pereira
etal.(2012)
Sitagliptinvssulfonylureaall
asadd-onsto
metform
in
Societal
(butonly
withdirect
costs)
MeanHbA1c6.5–11%
Saxagliptin(?
metform
in)vssulfonylurea(?
metform
in)
Elgartet
al.
(2013)[14]
2009
Argentina
Elgartet
al.(2013)
Saxagliptinvssulfonylureaall
asadd-onsto
metform
in
(dose
notreferred)
3rd
party
payer
(Argentina
social
security
healthcare
system
)
Meanage64years
Proportionofmen
53%
MeanHbA1c7.7
%
Meandurationofdiabetes
10.5
years
Erhardtet
al.
(2012)[15]
2009
Germany
Erhardtet
al.(2012)
Saxagliptinvssulfonylureaall
asadd-onsto
metform
in
(dose
notreferred)
3rd
party
payer
(National
sick
funds)
Meanage57.55years
Proportionofmen
52%
MeanHbA1c7.65%
Meandurationofdiabetes
5.4
years
Granstrom
etal.(2012)
[16]
2008
Sweden
Granstrom
etal.(2012)
Saxagliptinvssulfonylureaall
asadd-onsto
metform
in
3rd
party
payer
inSweden
Meanage57.55years
Proportionofmen
52%
MeanHbA1c7.65%
Meandurationofdiabetes
5.4
years
Bergenheim
etal.(2012)
[17]
2009
US
Bergenheim
etal.(2012)
Saxagliptinvssulfonylureaall
asadd-onsto
metform
in
(dose
notreferred)
3rd
party
payer
intheUS
Meanage60years
Proportionofmen
48%
Meandurationofdiabetes
5.4
years
Carvalhoet
al.
(2014)[18]
2014
Portugal
Carvalhoet
al.(2014)
Saxagliptinvssulfonylureaall
asadd-onsto
metform
in
(dose
notreferred)
Societal
(Portuguese
perspective)
Meanage53years
Proportionofmen
64.4
%
MeanHbA1c7.0
%
Meandurationofdiabetes
0years
948 A. Baptista et al.
123
Ta
ble
3continued
References
Yearofretrieval
ofdata
Country/Authors
(pubyear)
Interventions
Perspective
Populationstudied
Saxagliptin(?
metform
in/sulfonylurea)
vsinsulin(?
metform
in/sulfonylurea)
Grzeszczak
etal.(2012)
[19]
2009
PolandGrzeszczaket
al.
(2012)
SaxagliptinvsNPH
insulin
when
usedin
combination
withmetform
inor
sulfonylurea
3rd
party
payer
(Polish
National
HealthFund)
Meanage52years
Proportionofmen
48%
MeanHbA1c7.9
%
Meandurationofdiabetes
1.7
years
Saxagliptin(?
metform
in)vspioglitazone(?
metform
in)
Nitaet
al.
(2011)[20]
2011
Brazil
Nitaet
al.(2012)
Saxagliptinvsrosiglitazoneor
pioglitazoneallas
add-onsto
metform
in(dose
notreferred)
Privatehealthcare
system
Meanage59.77years
Proportionofmen
42%
MeanHbA1c6.47%
Meandurationofdiabetes
7.27years
Vildagliptin(?
metform
in)vssulfonylurea(?
metform
in)
Viriato
etal.
(2014)[21]
2013
Portugal
Viriato
etal.(2014)
Vildagliptinvssulfonylureaall
asadd-onsto
metform
in
3rd
party
payer
(Portuguese
healthcare
system
perspective)
Meanage63years
Proportionofmen
52%
MeanHbA1c7.2
%
Meandurationofdiabetes
9.13years
MeanBMI31.39kg/m
2
Liraglutidevssitagliptin
Liet
al.(2014)
[22]
2010–2012
US
Liet
al.(2014)
Liraglutidevssitagliptin
3rd
party
payer
Meanage54years
(liraglutide),58years
(sitagliptin)
Proportionofmen
43.9
%
(liraglutide),61.8
%
(sitagliptin)
Liraglutide(?
metform
in)vssitagliptin(?
metform
in)
Carlssonand
Persson
(2014)[23]
2013
Sweden
CarlssonK,PerssonU.
(2014)
Liraglutide1.2
mgvs
sitagliptin100mgallas
add-
onsto
metform
in
Societal
Meanage56years
MeanHbA1c8.4
%
Meandurationofdiabetes
6years
MeanBMI32.6
kg/m
2
The place of DPP-4 inhibitors in the treatment algorithm of diabetes type 2: a systematic… 949
123
Ta
ble
3continued
References
Yearofretrieval
ofdata
Country/Authors
(pubyear)
Interventions
Perspective
Populationstudied
Tzanetakos
etal.(2014)
[24]
2013
Greece
Tzanetakoset
al.(2014)
Liraglutide1.2
mgvs
sitagliptin100mg
allas
add-onsto
metform
in
3rd
party
payer
Meanage64.5
years
Proportionofmen
51.5
%
MeanHbA1c8.2
%
Meandurationofdiabetes
10.4
years
MeanBMI
30.4
kg/m
2
Langer
etal.
(2013)[25]
2012
US
Langer
etal.(2013)
Liraglutide1.2
and1.8
mgvs
sitagliptin100mgallas
add-
onsto
metform
in
3rd
party
payer
Meanage55.3
years
Proportionofmen
52.9
%
MeanHbA1c8.4
%
Meandurationofdiabetes
6.0
yearsMeanBMI32.8
kg/
m2
Perez
etal.
(2015)[26]
2012
Spain
Perez
etal.(2015)
Liraglutide1.8
mgvs
sitagliptin100mgallas
add-
onsto
metform
in
3rd
party
payer
(Spanish
Healthcare
payer
perspective)
Meanage55.3
years
MeanHbA1c8.4
%
Meandurationofdiabetes
6.0
yearsMeanBMI32.8
kg/
m2
Rayaet
al.
(2013)[27]
2012
Spain
Rayaet
al.(2013)
Liraglutide1.2
mgvs
sitagliptin100mgallas
add-
onsto
metform
in
3rd
party
payer
(Spanish
Healthcare
payer
perspective)
Meanage55.3
years
Proportionofmen
52.9
%
MeanHbA1c8.4
%
Meandurationofdiabetes
6.0
years
MeanBMI32.8
kg/m
2
Davieset
al.
(2012)[28]
2008
UK
Davieset
al.(2012)
Liraglutide1.2
and1.8
mgvs
sitagliptin100mgallas
add-
onsto
metform
in
3rd
party
payer
(NHS
perspective)
Meanage55.3
years
Proportionofmen
52.9
%
MeanHbA1c8.4
%
Meandurationofdiabetes
6.0
years
MeanBMI32.8
kg/m
2
Lee
etal.
(2012)[29]
2011
US
Lee
etal.(2012)
Liraglutide1.2
and1.8
mgvs
sitagliptin100mgallas
add-
onsto
metform
in
3rd
party
payer
inUS
Meanage55.3
years
Proportionofmen
52.9
%
MeanHbA1c8.4
%
Meandurationofdiabetes
6.0
years
MeanBMI32.8
kg/m
2
950 A. Baptista et al.
123
Ta
ble
3continued
References
Yearofretrieval
ofdata
Country/Authors
(pubyear)
Interventions
Perspective
Populationstudied
Insulinglargineandsitagliptin
Brownet
al.(2014)
[30]
2012
Canada
Brownet
al.
(2014)
Insulinglarginevssitagliptin
allas
add-onsto
metform
in
3rd
party
payer
Meanage54years
Proportionofmen
51%
MeanHbA1c8.5
%
Meandurationofdiabetes
4.5
years
MeanBMI31.1
kg/m
2
GLP-1
agonists
(?metform
in)vsDPP-4
inhibitors
(?metform
in)vsNPH
insulin(?
metform
in)
Kiadalirietyal.(2014)
[31]
2013
Sweden
Kiadaliriet
al.
(2014)
GLP-1
agonists
vsDPP-4
inhibitors
vs
NPHinsulinallas
add-onsto
metform
in
Societal
Meanage64.7
years
Proportionofmen
57.5
%
MeanHbA1c7.7
%
Meandurationofdiabetes
5.6
years
MeanBMI30.9
kg/m
2
References
Datasourceto
Effectiveness
measurement
Outcomes/consequences
measurement/utilities
source/Baseutilities
reference
Totalandincrem
entalanalysis
Sensitivityanalysis
Classification
Sitagliptin(?
metform
in)vssulfonylurea(?
metform
in)
Schwarzet
al.
(2008)[12]
Nauck
etal.
(2007)
QALY
UKPDS
0.78UKPDS
MeanQALYs:
Sitagliptinvssulfonylurea
Difference
0.037–0.095QALYsacross
countries
Meandirectcosts:sitagliptinvssulfonylurea
Difference
331–1097€across
countries
ICER(sitagliptinvssulfonylurea)
5949–20,350€/QALY
across
countries
Irrespectiveof20%
variationsin
thecost
andutility
weights
associated
withdiabetes-related
complications,discountedICER
values
remained
within
anarrow
range(4060–5473€),as
did
values
associated
with50%
variationsin
costsandutility
weights
associated
with
hypoglycemia
(5040–5256€)
0.714
Pereira
etal.
(2012)[13]
Nauck
etal.
(2006),
Goldsteinet
al.
(2007),
Charbonnel
etal.(2006)
QALY
UKPDS
0.785UKPDS
MeanQALYs:
Sitagliptin8.222QALYs
Sulfonylurea8.173QALYs
Difference
0.048QALYs
Meandirectcosts:
Sitagliptin€4
4,821
Sulfonylurea€44,283
Difference
€538
ICER(sitagliptinvssulfonylurea)
11,198€/QALY
Globally
inoneway
sensitivity
analysisandmulti-way
sensitivityanalysistheICERs
arerobust
relativeto
the
differencesin
utilities
orin
the
costsofthedifferentparam
eters
aswellas
insomeparam
etersof
efficacy
0.629
The place of DPP-4 inhibitors in the treatment algorithm of diabetes type 2: a systematic… 951
123
Ta
ble
3continued
References
Datasourceto
Effectiveness
measurement
Outcomes/consequences
measurement/utilities
source/Baseutilities
reference
Totalandincrem
entalanalysis
Sensitivityanalysis
Classification
Saxagliptin(?
metform
in)vssulfonylurea(?
metform
in)
Elgartet
al.
(2013)[14]
RCT
D1680C00001-
52-w
eektrial
Gokeet
al.
(2010)
QALY
andLYG
Meandiscountedlife
expectancy:
Saxagliptin20.84years
Sulfonylurea20.76years
Difference
years
0.08years
MeandiscountedQALYs:Saxagliptin
9.54QALYs
Sulfonylurea9.32QALYs
Difference
0.22QALYs
Meandiscounteddirectcosts:
Saxagliptin10,883€[$12,327]
Sulfonylurea9441€[$10,694]
Difference
1441€[$1632.9]
ICER(saxagliptinvssulfonylurea)
6510€[$7374]/QALY
Cost-effectivenessacceptabilitycurve
illustratesaprobabilityofless
than
58%
that
saxagliptin?
metform
inis
cost-effectivecompared
with
sulfonylurea?
metform
in,considering
awillingnessto
pay
of6732€[$7626]/
(GDPper
capitaforArgentina)/QALY
0.829
Erhardtet
al.
(2012)[15]
RCT
D1680C00001
–52-w
eektrial
Gokeet
al.
(2010)
QALY
andLYG
UKPDS
Meanlife
expectancy:Saxagliptin
15.63years
Sulfonylurea15.62years
Difference
years
0.01years
MeanQALYs:
Saxagliptin13.42
QALYs
Sulfonylurea13.31QALYs
Difference
0.12QALYs
Meandirectcosts:
Saxagliptin
38,163€
Sulfonylurea36,550€
Difference
1613€
ICER(saxagliptinvssulfonylurea)
13,931€/QALY
Univariatedsensitivityanalysesshowthat
akey
driver
oftheresultswas
the
assumptionthat
patients
received
combinationtherapyandnotmetform
in
alonefrom
model
entry.ICER
of
saxagliptinvssulfonylureafellto
2372€/QALY
(an83.2
%reduction
from
basecase).In
ascenario
where
patients
enteredthemodel
atage
71.94years
[anincrease
of25%
over
thebasecase
(57.55years)],theICER
rose
by63.8
%to
23,175€/QALY.
Mean(H
bA1c)
level
atbaselinewas
also
akey
model
driver;values
both
higher
andlower
than
thebasecase
resulted
inhigher
ICERs:
HbA1c,
7.65%–ICER
14,147€/QALY
HbA1c,
7.15%–ICER17,840€/QALY
HbA1c,
8.15%–ICER15,155€/QALY
ICER10,329€in
thePSA
0.714
952 A. Baptista et al.
123
Ta
ble
3continued
References
Datasourceto
Effectiveness
measurement
Outcomes/consequences
measurement/utilities
source/Baseutilities
reference
Totalandincrem
entalanalysis
Sensitivityanalysis
Classification
Granstrom
etal.(2012)
[16]
RCT
D1680C00001-
52-w
eektrial
Gokeet
al.
(2010)
QALY
andLYG
UKPDS
Meandiscountedlife
expectancy:Saxagliptin
14.72years
Sulfonylurea14.72years
Difference
years
0.0
years
MeandiscountedQALYs:
Saxagliptin12.56
QALYs
Sulfonylurea12.46QALYs
Difference
0.10QALYs
Meandiscounteddirectcosts:Saxagliptin12,328€
[116,211SEK]
Sulfonylurea11,321€[106,727SEK]
Difference
1006€[9484SEK]
ICER
(saxagliptinvssulfonylurea)
9608€[91,260SEK]/QALY
Weight,anditsassociated
HRQoLdecrement
andim
pactondiabetes-related
events,was
anim
portantparam
eter
inthemodel.The
highestcost
per
QALY
29,320€[276,408
SEK]isobtained
under
theextrem
e
assumptionthat
theHRQoLdecrement(for
thefirstandsubsequentyears)per
unitBMI
gainis
reducedby75%
(0.0035).As
expected,when
thisHRQoLdecrementis
reducedbyhalf,theresultingcost
per
QALY
islower,17,652€[166,408SEK].
RaisingtheHbA1cthreshold
when
insulinis
initiatedto
8.0
%,increasesthecost
per
QALY
to18,156€[171,162SEK].The
overallcost
per
QALY
inthePSA
was:
11,578€[109,152SEK]
0.771
Bergenheim
etal.(2012)
[17]
RCT
D1680C00001-
52-w
eektrial
Gokeet
al.
(2010)
QALY
UKPDS
MeanQALYs:
Saxagliptin11.02QALYs
Sulfonylurea8.37QALYs
Difference
2.65QALYs
Meandirectcosts:Saxagliptin57,503€[$65,139]
Sulfonylurea55,056€[$62,367]
Difference
2447€[$2772]
ICER
(saxagliptinvssulfonylurea)
924€[$
1047]/QALY
When
evaluatingsensitivityaroundthe
subgroupofhypoglycaem
icevents
accruingcost,attributingacost
value
only
toevents
requiringmedical
assistance
did
notsignificantlychangetheoutcome.
PSAresultsshowed
ameanincrem
entalcost-
effectivenessratio(ICER)of(-€1748)
[-$1980]withsaxagliptinplusmetform
in
appearingto
bedominant.
0.600
Carvalhoet
al.
(2014)[18]
RCT
D1680C00001-
52-w
eektrial
Gokeet
al.
(2010)
QALY
andLYG
0884HealthSurvey
for
England2003
Meanlife
expectancy:Saxagliptin13.58years
Sulfonylurea13.57years
Difference
years
0.01years
MeanQALYs:
Saxagliptin11.80QALYs
Sulfonylurea11.65QALYs
Difference
0.14QALYs
Meancosts:Saxagliptin21,959€
Sulfonylurea21,198€
Difference
761€
ICER
(saxagliptinvssulfonylurea)
5307€/QALY
Inone-way
sensitivityanalysisthevalueof
HbA1cis
avariable
withaconsiderable
impactin
theresultsofthestudy.
InPSAtheprobabilityofbeingcost-effective
is84.5
%to
aWTPof20,000€per
QALY
and87%
forathreshold
of30,000€per
QALY
0.829
The place of DPP-4 inhibitors in the treatment algorithm of diabetes type 2: a systematic… 953
123
Ta
ble
3continued
References
Datasourceto
Effectiveness
measurement
Outcomes/consequences
measurement/utilities
source/Baseutilities
reference
Totalandincrem
entalanalysis
Sensitivityanalysis
Classification
Saxagliptin(?
metform
in/sulfonylurea)
vsinsulin(?
metform
in/sulfonylurea)
Grzeszczak
etal.(2012)
[19]
RCTJadzinsky
etal.(2009)
andRCT
Nauck
etal.
(2007)
QALY
UKPDS
Scenario
1(m
etform
in?
insulinvs
metform
in?
saxagliptin)
Meanlife
expectancy:
Saxagliptin?
metform
in22.58years
Insulin?
metform
in22.58years
Difference
years
0.00years
MeanQALYs:
Saxagliptin?
metform
in
13.33QALYs
Insulin?
metform
in13.20QALYs
Difference
0.13QALYs
Meandirectcosts:
Saxagliptin?
metform
in
7765€[PLN
31,394]
Insulin?
metform
in6858€[PLN
27,730]
Difference
906€[PLN
3663]
ICERsaxagliptinvsinsulin(?
metform
in)
6790€[PLN
27,454]/QALY
Scenario
2(SU
?saxagliptinvs
SU
?insulin)
Meanlife
expectancy:Saxagliptin?
SU
22.53years
Insulin?
SU
22.53years
Difference
years
0.00years
MeanQALYs:
Saxagliptin?
SU
13.32
QALYs
Insulin?
SU
13.18QALYs
Difference
0.14QALYs
Meandirectcosts:
Saxagliptin?
SU
7963€[PLN
32,198]
Insulin?
SU
7090€[PLN
28,668]
Difference
873€[PLN
3529]
ICERsaxagliptinvsinsulin(?
SU)6100€
[PLN
24,663]/QALY
Theresultswerefoundto
be
sensitiveto
someofthebasic
model
assumptions,althoughthe
ICERremained
below
12,366€
[PLN
50,000]per
QALY
gained
inallcases
0.686
954 A. Baptista et al.
123
Ta
ble
3continued
References
Datasourceto
Effectiveness
measurement
Outcomes/consequences
measurement/utilities
source/Baseutilities
reference
Totalandincrem
entalanalysis
Sensitivityanalysis
Classification
Saxagliptin(?
metform
in)vspioglitazone(?
metform
in)
Nitaet
al.
(2011)[20]
DIA
PS79StudyGroup
(2010)
QALY
andLYG
UKPDS
0885UKPDS
Meanlife
expectancy:Saxagliptin
12.17years
Pioglitazone12.16years
Difference
years
0.01
MeanQALYs:
Saxagliptin10.55
QALYs
Pioglitazone10.42QALYs
Difference
0.13QALYs
Meandirectcosts:Saxagliptin
9679€[R$33,023]
Pioglitazone10,850€[R$37,019]
Difference
-1171€[R$-3996]
ICER
(saxagliptinvs
pioglitazone)—
Dominant
Intheunivariate
sensitivity
analysis,saxagliptinremained
dominantcompared
withTZDs
afteravariationof±15%
onall
selected
param
eters.
InPSA,addingsaxagliptinto
the
metform
intherapywas
dominant
in62.1
%ofallscenariosversus
theadditionofpioglitazone.
Only
in2.2
%ofthesimulations
did
saxagliptinshow
less
effectivenessandhigher
costs
0.571
Vildagliptin(?
metform
in)vssulfonylurea(?
metform
in)
Viriato
etal.
(2014)[21]
Ferranniniet
al.(2009)
RCT
QALY
andLYG
UKPDS
0.78Clarkeet
al.(2002)
Meanlife
expectancy:Vildagliptin
7.7486years
Sulfonylurea7.6591years
Difference
years
0.0896years
MeanQALYs:Vildagliptin5.7681
QALYs
Sulfonylurea5.6401QALYs
Difference
0.1279QALYs
Meandirectcosts:Vildagliptin
14,409€
Sulfonylurea13,248€
Difference
1161€
ICER
(vildagliptinvs
sulfonylurea)
9072€/QALY
Univariate
analysesshowed
that
ICERvalues
wererobustand
ranged
from
4195€to
16,052€
per
QALY
when
different
param
eterswerevaried.
ThePSA
of100simulated
interactionssuggestedthat
fora
WTPof30,000€per
QALY
treatm
entwithmetform
inplus
vildagliptinhad
a79%
probabilityofbeingcost-
effectivecompared
with
metform
inplussulfonylurea
0.771
The place of DPP-4 inhibitors in the treatment algorithm of diabetes type 2: a systematic… 955
123
Ta
ble
3continued
References
Datasourceto
Effectiveness
measurement
Outcomes/consequences
measurement/utilities
source/Baseutilities
reference
Totalandincrem
entalanalysis
Sensitivityanalysis
Classification
Liraglutidevssitagliptin
Liet
al.(2014)
[22]
Observational
longitudinal
retrospectivestudy
HbA1cchange
%points
Meanlife
expectancy:N/A
(6monthsfollow-up,without
extrapolation)
%pointsin
reductionofHbA1c
Liraglutide-0.95%
Sitagliptin-0.63%
Difference
0.31%
Liraglutide1403€[$1589]
Sitagliptin1809€[$2049]
Difference
-406€[$-460]
Liraglutideprovides
greater
benefits
atlower
cost,when
compared
withsitagliptin
(dominance)
Notapplicable
0.485
Liraglutide(?
metform
in)vssitagliptin(?
metform
in)
Carlssonand
Persson
(2014)[23]
RCTPratley
etal.(2010)
(ClinicalTrials.gov
Identifier:NCT00700817)
HbA1cchange
%points
UKPDS
Men,nonsm
oker
MeanQALYs:
Liraglutide
8.55–10.53QALYs
Sitagliptin8.21–10.15QALYs
Difference
0.33–0.38QALYs
Meandirectcosts:Liraglutide
101,052–149,673€
[952,648–1411,014SEK]
Sitagliptin95,547–143,563€
[900,750–1353,411SEK]
Difference
5505-6110€
[51,898–57,603SEK]
ICER
(liraglutidevssitagliptin)
15,780–17,060€
[148,766–160,827SEK]/QALY
Ninetyper
centofthepredicted
cost
increm
ents
andQALY
increm
entsforthecomparisonof
liraglutide1.2
mgvsSU
were
within
theintervals2408€
22,701.SEK–14,175€133,633
SEK
and0.15–1.27QALYs,
respectively.Theprobabilitythat
liraglutidewould
beconsidered
cost-effectivecompared
with
sitagliptinwas
89%
ataWTP
per
QALY
of53,037€500,000
SEK
0.800
956 A. Baptista et al.
123
Ta
ble
3continued
References
Datasourceto
Effectivenessmeasurement
Outcomes/consequences
measurement/utilities
source/Baseutilities
reference
Totalandincrem
entalanalysis
Sensitivityanalysis
Classification
Tzanetakos
etal.(2014)
[24]
QALY
UKPDS
Meanlife
expectancy:Liraglutide
14.22years
Sitagliptin14.09years
Difference
0.13years
MeanQALYs:
Liraglutide9.24
QALYs
Sitagliptin9.05QALYs
Difference
0.19QALYs
Meandirectcosts:Liraglutide
39,524€
Sitagliptin36,727€
Difference
2797€
ICER
(liraglutidevssitagliptin)
15,101€/QALY
Sim
ulationresultswerequite
sensitiveto
thegradual
shorteningofmodel
time-
horizonresultingin
anincrease
ofbasecase
ICERforliraglutide
bymore
than
600%
at5years
simulation.Sim
ulationresults
werequitesensitiveto
patients’
HbA1cvalues,underlining,as
such,theim
portance
ofthis
biochem
ical
param
eter
tohealth
andcost
outcomes
ofmodel
analysis
0.828
Langer
etal.
(2013)[25]
RCTPratley
etal.(2010)
(ClinicalTrials.gov
Identifier:NCT00700817)
HbA1c
%ofpatientsreachingendpoint
Liraglutide1.2
mg38.9%
Liraglutide1.8
mg49.9%
Sitagliptin100mg18.6%
Difference
(liraglutide1.2
mg)
(20.3%)
Difference
(liraglutide1.8
mg)
(31.3%)
Meandirectcosts(SD):
Liraglutide1.2
mg9123€
[US$10,335]
Liraglutide1.8
mg10,377€
[US$11,755]
Sitagliptin14,882€[U
S$16,858]
Variationin
cost
assumptionsby
±20%
andvariationin
clinical
inputsparam
eterswithin
the
rangeofthe95%
CIdid
not
changethefindingsthat
thecost
ofreachingthecomposite
endpoint(cost
ofcontrol)with
liraglutide1.2
mgand1.8
mg
was
lower
than
thecost
with
sitagliptinafter52weeksof
treatm
ent
0.657
The place of DPP-4 inhibitors in the treatment algorithm of diabetes type 2: a systematic… 957
123
Ta
ble
3continued
References
Datasourceto
Effectivenessmeasurement
Outcomes/consequences
measurement/utilities
source/Baseutilities
reference
Totalandincrem
entalanalysis
Sensitivityanalysis
Classification
Perez
etal.
(2015)[26]
RCTPratley
etal.(2010)
(ClinicalTrials.gov
Identifier:NCT00700817)
QALYs
Meanundiscountedlife
expectancy
(SD):Liraglutide
14.241years
(0.183)
Sitagliptin13.873years
(0.185)
Difference
0.368years
MeanQALY
(SD):
Liraglutide9.24QALYs(0.121)
Sitagliptin8.84QALYs(0.121)
Difference
0.40QALYs
Meandiscounteddirectcosts(SD):
Liraglutide56,628€(1323)
Sitagliptin52,450€(1394)
Difference
4177€
ICER
of10,436€/QALY
Cost
effectivenessoutcomes
were
most
sensitiveto
changes
in
time-horizonofthemodelling
analysis,withliraglutideless
cost-effectiveover
shorter
time-
horizons.Thiswas
primarilydue
totheim
provem
ents
in
physiological
param
eters
associated
withliraglutide
resultingin
reducedrisk
oflong-
term
complications,withthe
benefitsofthisnotfullyrealized
over
shorter
time-horizons
0.685
Rayaet
al.
(2013)[27]
RCTPratley
etal.(2010)
(ClinicalTrials.gov
Identifier:NCT00700817)
QALY
Meanundiscountedlife
expectancy
(SD):Liraglutide
20.00years
(0.33)
Sitagliptin19.72years
(0.30)
Difference
0.28years
MeanQALY
(SD):
Liraglutide9.04QALYs(0.13)
Sitagliptin8.87QALYs(0.11)
Difference
0.17QALYs
Meandiscounteddirectcosts(SD):
Liraglutide54,684€(1250)
Sitagliptin52,387€(1346)
Difference
2297€
ICER
of13,266€/QALY
Cost
effectivenessoutcomes
were
most
sensitiveto
changes
in
shorteningthetime-horizon
(5–10years)andin
changes
of
HbA1cbenefitassociated
with
liraglutide.
When
thetime-
horizonwas
changed
to10years,
theICER
increasedto
58,433€/
QALY
andwhen
changed
to
5years
theICER
increasedto
102,605€/QALY.Withthe
abolishmentoftheHbA1c
benefittheICERincreasedto
199,114€/QALY
0.714
958 A. Baptista et al.
123
Ta
ble
3continued
References
Datasourceto
Effectivenessmeasurement
Outcomes/consequences
measurement/utilities
source/Baseutilities
reference
Totalandincrem
entalanalysis
Sensitivityanalysis
Classification
Davieset
al.
(2012)[28]
RCTPratley
etal.(2010)
(ClinicalTrials.gov
Identifier:NCT00700817)
QALY
MeanQALYs(SD):Liraglutide1.2
mg7.52
QALYs(0.11)
Liraglutide1.8
mg7.64QALYs(0.11)
Sitagliptin100mg7.34QALYs(0.11)
Difference
(1.2
mg)0.19QALYs(0.15)
Difference
(1.8
mg)0.31QALYs(0.15)
Meandirectcosts:
Liraglutide1.2
mg
30,222€[£21,793]
Liraglutide1.8
mg32,138€[£23,175]
Sitagliptin27,667€[£19,951]
Difference
(1.2
mg)2554€£1842]
Difference
(1.8
mg)4471€[£3224]
ICER
(liraglutidevssitagliptin)
1.2
mg13,661€[£9851]/QALY
1.8
mg14,513€[£10,465]/QALY
Variationsin
key
param
etersare
allcost-effectiveat
athreshold
of£20000.Thegainin
QALYswithliraglutide1.2
mg
over
sitagliptinarises
mainly
from
improvem
ents
inHbA1c
(54%)andweight(44%)
0.686
Lee
etal.
(2012)[29]
RCTPratley
etal.(2010)
(ClinicalTrials.gov
Identifier:NCT00700817)
QALY
andLYG
Meanlife
expectancy:Liraglutide1.2
mg
13.003years
Liraglutide1.8
mg13.189years
Sitagliptin12.84years
Difference
(1.2
mg)0.163years
Difference
(1.8
mg)0.348years
MeanQALYs:
Liraglutide1.2
mg8.825QALYs
Liraglutide1.8
mg8.979QALYs
Sitagliptin100mg8.624QALYs
Difference
(1.2
mg)0.201QALYs
Difference
(1.8
mg)0.356QALYs
Meandirectcosts:
Liraglutide1.2
mg
1,896€[$81.444]
Liraglutide1.8
mg79,010€[$89.502]
Sitagliptin7322€[$76.262]
Difference
(1.2
mg)4575€[$5182]
Difference
(1.8
mg)11,689€[$13,241]
ICER
(liraglutidevssitagliptin)
1.2
mg22,724€[$25,742]/QALY
1.8
mg32,869€[$37,234]/QALY
Aseries
ofsensitivityanalyses
indicated
that
liraglutidewould
becost-effectiveat
both
1.8-
and1.2-m
gdosages
compared
withsitagliptinover
arangeof
plausible
inputparam
eters.
Cost-effectivenessresults(for
liraglutide1.2
and1.8
mg)
weremost
sensitiveto
the
time-horizonofthe
simulations;when
a10-year
time-horizonwas
usedthe
ICERwas
100,820€
[$114,209]/QALY
for
liraglutide1.8
mgand58,939
€[$66,766]/QALY
for
liraglutide1.2
mg.When
PSA
was
conducted:ICER
for
liraglutide1.8
mgvssitagliptin
was
37,856€[$42,883]/QALY
andforliraglutide1.2
mgvs
sitagliptinwas
31,238
€[$35,386]/QALY
0.743
The place of DPP-4 inhibitors in the treatment algorithm of diabetes type 2: a systematic… 959
123
Ta
ble
3continued
References
Datasourceto
Effectivenessmeasurement
Outcomes/consequences
measurement/utilities
source/Baseutilities
reference
Totalandincrem
entalanalysis
Sensitivityanalysis
Classification
Insulinglargineandsitagliptin
Brownet
al.
(2014)[30]
EASIE
RCT
QALY
UKPDS
0.80Cam
eronandBennett,
2009
Meanlife
expectancy:Insulinglargine11.47years
Sitagliptin11.38years
Difference
years
0.09years
MeanQALYs:
Insulinglargine8.815QALYs
Sitagliptin8.739QALYs
Difference
0.076QALYs
Meandirectcosts:Insulinglargine33,409€
[$CAD45,556]
Sitagliptin33,469€[$CAD45,638]
Difference
-1052€[$CAD1,434]
ICER(insulinglarginevssitagliptin)-13,847€
[$CAD
-18,882]/QALY
Dominant
Changes
inthenumber
ofteststrips
usedforsitagliptinandinsulin
glargineresulted
inthelargest
impactontheICER.Depending
onthenumber
ofteststripsused,
theICERvariedfrom
13,692€to
28,667€
[$CAD18,670–$CAD39,091]
0.800
GLP-1
agonists
(?metform
in)vsDPP-4
inhibitors
(?metform
in)vsNPH
insulin(?
metform
in)
Kiadalirietyal.
(2014)[31]
Ekstrom
etal.(2012)
Observational
study
QALY
EQ-5D
UKPDS
SwedishNational
Diabetes
Register(N
DR)
MeanQALYs:
GLP-1
agonists
4.75QALYs
DPP-4
inhibitors
4.65QALYs
Difference
(GLP-1
vsDPP-4)0,10QALYs
NPH
insulin4.50QALYs
Difference
(DPP-4
vsNPH
insulin)0.15QALYs
Meandirectcosts:GLP-1
agonists
229,430€[SEK
2,162.907]
DPP-4inhibitors
225,732€[SEK
2,128.042]
NPH
insulin225,102€[SEK
2,122.105]
Difference
(GLP-1
vsDPP-4)3,698€[34,865SEK]
Difference
(DPP-4
vsNPH
insulin)
630€[5,936SEK]
ICER(G
LP-1
vsDPP-4):
37,463€[353,172SEK]/QALY
ICER(D
PP-4
vsNPH
insulin)
3,824€[36,050SEK]/QALY
InPSA,theestimated
ICERwas
319,217.AssumingaWTPof
500,000SEK
per
QALY
gained,
strategy1had
a74.7
%
likelihoodofbeingconsidered
cost-effectivein
comparisonto
strategy2
0.885
Total
0.720
Exchangerateswereassessed
on15May
2015usingtheconvertingtoolofthePortugueseNational
Bank(https://www.bportugal.pt/en-U
S/Estatisticas/Dominios%
20Estatisticos/Estatisti
casC
ambiais/Pages/Taxasdereferenciadiarias.aspx)
960 A. Baptista et al.
123
known and widely used model, presented below—because
it includes fewer complications and does not encompass
the interactions between them, and also because the disease
progression is modelled in a limited way for some com-
plications; although, it has also been shown to perform
quite similarly in simulating trial outcomes [33]. The main
contribution was an international comparison including six
countries, which allowed determining the possible dis-
crepancies in cost-effectiveness ratios.
Sitagliptin was beneficial as compared with sulfony-
lureas by the reduction of hypoglycemia episodes and
avoidance of weight gain [4]. The ICER of sitagliptin
versus the sulfonylureas varied from 5949 €/QALY in
Portugal to 20,350 €/QALY in Austria [12]. Discrepancies
in incremental effectiveness may contribute to these dif-
ferences, from 0.037 QALYs in Austria to 0.056 QALYs in
Portugal. The Portuguese population considered in this
study had a larger body mass index (BMI) (34.77 kg/m2,
for men) as compared with Austria (26.12 kg/m2, for men),
possibly explaining the higher benefits of sitagliptin. There
were also discrepancies in incremental costs, from 331 € in
Portugal to 760 € in Austria. This was partly explained by
the difference in price between sitagliptin and sulfony-
lureas, from 1.55 € in Portugal to 1.78 € in Austria. The
higher costs of macro- and micro-vascular complications in
Austria might have been compensated for by their lower
probability of occurrence, given the lower BMI and zero-
percent smoking rate in the sample. Note that a more recent
study for Portugal, which replicated the same analysis,
found a value of 11,198 €/QALY [13]. The higher ICER,
compared with the value obtained for Portugal in the
international comparison, is explained by the higher treat-
ment costs.
Second, we analysed the cost-effectiveness of sax-
agliptin compared with sulfonylureas [14–18], mainly as
add-ons to metformin, in patients not controlled with
metformin monotherapy. The studies used a stochastic
simulation model especially designed to evaluate the
impact of new therapies in people with T2DM (Cardiff
Diabetes model) [34–36]. Although possibly less compre-
hensive than the IMS core model, this model performed
comparably when compared with trials outcomes [34]. It
provided a reasonable prediction of treatment effects but
tended to underestimate or overestimate the risks of
complications.
The major advantages of saxagliptin as compared with
sulfonylurea were the reduction in the number of hypo-
glycemia episodes, which influences the quality of life, and
the avoidance of weight increases [16]. The incremental
effectiveness was rather similar across studies, with values
of 0.10 QALYs in Sweden [16], 0.12 in Germany [15], and
0.14 in Portugal [18]. A higher value was observed for
Argentina [14], of 0.22 QALYs, possibly due to the older
base population (64 years old, compared with 60 or
younger in the other studies), and longer duration of dia-
betes (more than 10 years, compared with less than 6 in
other studies).
The US study was a clear outlier, indicating an incre-
mental effectiveness of 2.65 QALYs [17]. This very
favourable effect of saxagliptin in the US study was related
to the much lower QALYs for the patients treated with
sulfonylureas, of 8.37, compared with values above 9.32 in
the other studies. We interpret this discrepancy through the
base characteristics of the population considered in the US
study, which had a much higher average BMI (34.01 kg/m2
versus lower than 31.20 kg/m2 in the other studies, from
our own calculations), explaining the largely unfavourable
outcomes for the patients treated with sulfonylureas.
The incremental costs varied little across studies, from
761 € in Portugal [18] to 2,447 € in the US [17]. The ICER
values ranged from 5,307 €/QALY to 13,931 €/QALY.The US case was an outlier in terms of ICER, as expected
from the incremental effectiveness outcome, with a much
lower value of 924 €/QALY.Third, we observed that saxagliptin in combination with
metformin had an ICER of 6790 €/QALY when compared
with insulin; the ICER was 6100 €/QALY in combination
with sulfonylurea [19]. The benefits were driven by the
lower risk of hypoglycaemic events and the neutral effect
on weight [19]. A quite similar ratio was obtained in
Sweden, by Kiadaliri et al. [31], which compared the DPP-
4 inhibitors to insulin, finding an ICER of 3824 €/QALY.Fourth, a single study compared saxagliptin with
pioglitazone, in combination with metformin, and found
that saxagliptin was dominant (greater effectiveness and
lower cost) [20]. The price of saxagliptin is lower, while
the benefits are greater, namely the higher glycaemic
control.
Fifth, one single study was obtained for vildagliptin,
compared with sulfonylureas [21], all as add-ons to met-
formin, in patients not controlled with metformin
monotherapy. The vildagliptin versus sulfonylurea model
was constructed as a patient-level simulation model, uti-
lizing the risk equations from the UKPDS outcomes model
to predict microvascular and macrovascular complications
and mortality (both disease-specific and all-cause) over a
40-year horizon [21]. Vildagliptin had a similar clinical
benefit in comparison to sulfonylurea; namely it avoids the
weight gain and reduces the risk of hypoglycemia [4].
Vildagliptin had an ICER of 9072 €/QALY compared with
sulfonylureas, using the Portuguese National Health Ser-
vice perspective.
Sixth, we examined the comparison between liraglutide
and sitagliptin [22–29]. The studies that compared liraglu-
tide with sitagliptin, all as add-ons to metformin as second-
line therapy, used the CORE diabetes model (IMS Health,
The place of DPP-4 inhibitors in the treatment algorithm of diabetes type 2: a systematic… 961
123
Basel, Switzerland). This model, widely used and validated,
allows estimating the long-term health outcomes and eco-
nomic consequences of diabetes, with the possibility also of
measuring the impact of different treatments and patient
management strategies [37]. It has become a reference in the
field because it integrates a comprehensive set of compli-
cations, and accounts for multiple risk factors. Also, it
combines aMarkov structure with Monte Carlo simulations,
which allows measuring the joint progression and interac-
tions between complications, and the effect of event history.
On the one hand, most of the studies were based on the
same measurements of benefits, so that the incremental
effectiveness was quite similar across studies. In particular,
six out of eight studies were based on the same random
clinical trial, by Pratley et al. [38]. According to Li et al.
[22], using effectiveness measures (i.e., from the real
world), the benefits of liraglutide compared with sitagliptin
are driven by improved HbA1c and by greater weight loss.
Noticeably, all studies considered a population with a BMI
higher than 30 kg/m2, so that the results must be inter-
preted as relevant for this specific sub-population. For the
1.2-mg dosage, the incremental effectiveness varied from
0.17 QALYs in Spain [27] to 0.20 in the US [29]; for the
1.8-mg dosage, it varied from 0.31 QALYs in the UK [28]
to 0.40 in Spain [26].
On the other hand, the variations in incremental costs
ranged between 2297 € in Spain [27] to 6110 € in Sweden
[23], for the 1.2-mg dosage. This resulted in ICERs of
relatively similar values, from 13,266 €/QALY in Spain
[27] to 22,724 €/QALY in the US [29]. For the 1.8-mg
dosage, the values varied between 4000 € and 5000 €except for the US, where the incremental cost rose to
11,689 € [29]. This resulted in a much higher ICER in the
US, of 32,869 €/QALY, compared with values below
15,000 €/QALY in other countries. This much higher
incremental cost in the US, driving a much less favourable
ICER, was mainly due to the discrepancy in treatment
costs: in the US, the liraglutide treatment is twice as costly
as the sitagliptin, while it is only 16 % higher in the UK
(according to our own calculation) [28]. Note also that the
US study adopted a time-horizon of 3 years only, possibly
omitting potential long-term consequences of treatments,
so that its findings are hardly comparable.
Seventh, insulin glargine was compared with sitagliptin
as add-ons to metformin [30], and was found to be domi-
nant in Canadian settings. The model also used the IMS
CORE diabetes model [37]. The model considered a time-
horizon of 50 years, and was populated with data from the
EASIE trial. The insulin glargine increased the number of
hypoglycaemic episodes but achieved a greater reduction
of HbA1c [30]. This resulted in a slight benefit, of 0.08
QALYs, obtained with a lower treatment cost, due to the
lower costs of treatment and disease complications.
Eighth, the GLP-1 receptor agonists (exenatide and
liraglutide) were compared with DPP-4 inhibitors as add-
ons to metformin [31]. The authors used the IHECM-
T2DM model, which was previously described and used to
compare cost-effectiveness of one of the GLP-1 receptor
agonists, liraglutide, versus sulfonylureas or sitagliptin in
Sweden. This model includes yearly cycles and a time-
horizon of up to 40 years. The macrovascular health states
were based on the UKPDS models and on the Swedish
national diabetes register equations [31]. The authors cal-
culated a gain of 0.10 QALYs for GLP-1 receptor agonists,
driven by the better control of glycemia and weight
reductions. These benefits were achieved at an additional
cost of 3698 €, resulting in an ICER of 37,463 €/QALY in
Swedish settings.
Discussion
The DPP-4 inhibitors represent substantial benefits in the
treatment of type-2 diabetes, but also a considerable chal-
lenge for health systems due to their high prices. There is
thus a clear need to perform economic evaluations of these
new therapies, to guide policy-makers in their decisions
regarding co-payments, therapeutic guidelines, and reim-
bursement strategies.
Key findings
This systematic review of the literature shows first and
foremost that the evidence on cost-effectiveness is still
recent and scarce, but is based on studies of overall high
quality. In particular, most of the studies were based on
published clinical trials for the measurement of conse-
quences, and on official unit prices and country-specific
resource use for costs. The studies used different but val-
idated models, with comparable characteristics and pre-
dictive power, which all considered long time-horizons and
the various health consequences of diabetes.
According to our findings, the DPP-4 inhibitors
appear as highly cost-effective in most of the cases,
following the WHO criterion and using the Organisation
for Economic Co-operation and Development (OECD)
GDP per capita values for 2015 as Ref. [39]. All as add-
ons to metformin, sitagliptin, saxagliptin, and vilda-
gliptin had an ICER below 25,000 €/QALY when
compared with sulfonylureas. When compared with
NPH insulin, saxagliptin as add-on to metformin or
sulfonylurea had an ICER below 10,000 €/QALY.Saxagliptin was dominant as compared with pioglita-
zone. These ratios were driven mainly by the reduction
in the risk of hypoglycaemic events, and in the avoid-
ance of weight gain.
962 A. Baptista et al.
123
Some variations across studies are worth mentioning. In
particular, the ratios for sitagliptin and saxagliptin varied
due to differences in baseline patient characteristics. The
findings were more favourable, from an economic view-
point, for the sub-group of patients with a higher BMI, who
were older, and who had been suffering from long-standing
diabetes. By contrast, in most cases there was little varia-
tion in incremental costs, so that these may not be con-
sidered as a major cause of ICER discrepancies.
Some studies evaluated more recent alternative thera-
pies, namely the GLP-1 receptor agonists and insulin
glargine. When compared with sitagliptin, liraglutide was
highly cost-effective. Note that this result was obtained
only for populations with an average BMI higher than
30 kg/m2; the favourable results are mainly explained by
the reduction in weight and better control of glycemia
achieved by GLP-1 receptor agonists. The insulin glargine
was demonstrated to be dominant when compared with
sitagliptin, related to the higher decrease in HbA1c and the
lower price of the drug.
Comparison with earlier literature
To the best of our knowledge, two earlier systematic reviews
of economic evaluations of DPP-4 inhibitors have been
performed, in 2010 [40] and 2015 [41]. Given the rapid
introduction of new drugs, we considered only the last
review as a relevant comparison for our study. The major
difference is that we retrieved 20 studies, in comparison to 11
in the reviewbyGeng et al. [41],mainly due to the analysis of
recently introduced GLP-1 receptor agonists.
Our findings were quite similar in regard to the com-
parison between DPP-4 inhibitors and sulfonylureas, both
as add-ons to metformin, concluding that DPP-4 inhibitors
are cost-effective in patients who do not achieve glycaemic
targets with metformin. In comparison with thiazolidine-
diones, Geng et al. [41] found five papers that came to
uncertain conclusions; in comparison, we only retrieved
one single paper, because we did not consider comparisons
with rosiglitazone, whose marketing authorization was
suspended in Europe due to safety issues.
Limitations
This study has some limitations. First, a relatively small
number of articles met the inclusion criteria for some
comparisons, namely DPP-4 inhibitors versus thiazo-
lidinediones (one single study), and DPP-4 inhibitors ver-
sus insulin (two studies). Obviously, this represents too
little evidence to draw robust conclusions. Regarding thi-
azolidinediones, this does not represent a major problem
given their low utilization in current practice [42]. For
insulin, this is a more serious issue given the high number
of users; in this sense, the lack of economic evaluations
was quite surprising, and further research is needed to
elaborate solid recommendations.
Second, as mentioned by Waugh et al. [40], most studies
were funded by manufacturers. Even though these studies
were often carried out by independent consultants, this can
lead to a publication bias, the unfavourable findings not
being diffused [43]. More generally, these limitations
highlight the urgent need for independent economic eval-
uations of DPP-4 inhibitors and other new treatments, e.g.
by State agencies.
Third, the health consequences were measured in most
studies using the same randomized control trials. For
example, the D1680C00001 trial was used in the studies for
Argentina, Germany, Portugal Sweden, and the US. On the
one hand, observational studies should be carried out to
confirm the favourable outcomes in real-world practice,
which may produce different outcomes according to pop-
ulation characteristics, patients’ attitudes, and physicians’
practices. There is evidence, for example, of the use in
actual practice of DPP-4 inhibitors as single compounds or
in combination with sulfonylureas [44]. On the other hand,
the reliance on a few trials is problematic because it may
not encompass the possible different outcomes according
to populations’ characteristics. In particular, the ADA/
EASD guidelines mention that the choice of the second-
lines should be based on ‘‘a variety of patient and disease
specific factors’’ (p. 145) [4]. The lack of variety in the
populations under scrutiny limits the contributions of the
studies for drug evaluation across sub-populations.
Finally, relevant databases such as Econlit, CINAHL,
EMBASE, and Psychoinfo were not included in the search
strategy, because they were not accessible for free. Note,
however, that we have used the most commonly used
databases in systematic reviews of economic evaluations.
Future cost-effectiveness studies should be repeated during
the lifecycle of medicines under real-world utilization and
incorporate budget impact analysis.
Conclusions
According to WHO thresholds, there is consistent evidence
about the cost-effectiveness of DDP-4 inhibitors as second-
line, as add-ons to metformin, in comparison with sul-
fonylureas. More recent therapies, namely the GLP-1
receptor agonists, were, however, demonstrated to be
highly cost-effective in comparison to DPP-4 amongst
populations with an average BMI higher than 30 kg/m2.
Also, insulin glargine was demonstrated to be dominant
when compared with DPP-4 inhibitors.
These results were, however, obtained on the basis of
a limited number of studies, relying on the same few
The place of DPP-4 inhibitors in the treatment algorithm of diabetes type 2: a systematic… 963
123
clinical trials, and financed by manufacturers, raising the
issue of a possible publication bias. Further independent
research is needed, with more experimental but also
observational studies, to confirm these findings and
incorporate them into therapeutic guidelines.
Acknowledgments This research had no external funding.
Compliance with ethical standards
Conflict of interest The authors declare that they have no conflict of
interest. The authors have no affiliations or financial involvement that
conflicts with the material presented in this paper. The authors are not
employed in the pharmaceutical industry and, at the time of this
research, had not performed nor were conducting any research study
pertaining to the DPP-4 inhibitors group, nor were conducting any
research for any of the marketing authorization holders of those
therapeutic agents.
Appendix
See Table 3.
Template for each study extracted and recorded
information:
• Title [incl. author(s) and journal]
• Type of economic evaluation
• Objective
• Interventions
• Comparators
• Methods (Analytical approach; Perspective; Time
Horizon; Population; Effectiveness data; Monetary
benefit and utility valuation; Measure of benefit; Cost
data; Discount rate; Analysis of uncertainty)
• Results
• Authors’ Conclusions
• Limitations
• Affiliation to pharmaceutical industry
Search strings for search:
• Sitagliptin OR Saxagliptin OR Vildagliptin OR Alo-
gliptin OR Linagliptin assessed in March 2015
• Sitatgliptin AND Saxagliptin assessed in March 2015
• Sitagliptin AND Vildagliptin assessed in March 2015
• Sitagliptin AND Alogliptin assessed in March 2015
• Sitagliptin AND Linagliptin assessed in March 2015
• Saxagliptin AND Vildagliptin assessed in March 2015
• Saxagliptin AND Alogliptin assessed in March 2015
• Saxagliptin AND Linagliptin assessed in March 2015
• Vildagliptin AND Alogliptin assessed in March 2015
• Vildagliptin AND Linagliptin assessed in March 2015
• Alogliptin AND Linagliptin assessed in March 2015
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