Content uploaded by Stuart Mealing
Author content
All content in this area was uploaded by Stuart Mealing on May 12, 2014
Content may be subject to copyright.
R E S E A R C H Open Access
The importance of baseline viral load when
assessing relative efficacy in treatment-naïve
HBeAg-positive chronic hepatitis B: a systematic
review and network meta-analysis
Stuart Mealing
1*
, Isabella Ghement
2
, Neil Hawkins
1
, David A Scott
1
, Benedicte Lescrauwaet
3
, Maureen Watt
1
,
Mark Thursz
4
, Pietro Lampertico
5
, Lorenzo Mantovani
6
, Edith Morais
7
, Bruno Bregman
7
and Michel Cucherat
8
Abstract
Background: To date no network meta-analysis (NMA) has accounted for baseline variations in viral load when
assessing the relative efficacy of interventions for chronic hepatitis B (CHB). We undertook baseline-adjusted and
unadjusted analyses using the same data to explore the impact of baseline viral load (BVL) on CHB treatment response.
Methods: We searched Embase, Medline, Medline in Process and the Cochrane CENTRAL databases for randomised
clinical trials (RCTs) of monotherapy interventions at licensed doses for use in CHB. Search strategies comprised CHB
disease and drug terms (a combination of controlled vocabulary and free text terms) and also a bespoke RCT filter.
The NMA was undertaken in WinBUGs using fixed and random effects methods, using data obtained from a systematic
review. Individual patient data (IPD) from an entecavir clinical trial were used to quantify the impact of different
baseline characteristics (in particular undetectable viral load (UVL) at 1 year) on relative treatment effect. Study level
mean baseline values from all identified studies were used. Results were generated for UVL and presented as relative
risks (RRs) and 95% credible intervals (CrIs) using entecavir as reference treatment.
Results: Overall, for all eight relevant interventions we identified 3,000 abstracts. Following full text review a total of 35
(including the contents of six clinical study reports) met the inclusion critera; 19 were in hepatitis B e antigen
(HBeAg)-positive patients and 14 of the 19 contained outcome information of relevance to the NMA.
Entecavir and tenofovir studies had heterogeneous patient populations in terms of BVL (mean values 9.29 and 8.65
log
10
copies/ml respectively). After adjusting UVL for BVL using an informative prior based on the IPD analysis, the
difference between entecavir and tenofovir was not statistically significant (RR 1.27, 95% CrI 0.96 to 1.47 - fixed effects).
A similar conclusion was found in all sensitivity analyses. Adjusted tenofovir results were more consistent with observed
clinical trial response rates.
Conclusions: This study demonstrates the importance of adjusting for BVL when assessing the relative efficacy of CHB
interventions in achieving UVL. This has implications for both clinical and economic decision making.
Keywords: Network meta-analysis, Relative efficacy, Systematic review, Virologic response, Entecavir
Background
Chronic hepatitis B (CHB) is responsible for about 600,000
deaths worldwide per year, from end-stage liver disease
or hepatocellular carcinoma (HCC) [1]. An estimated 350
to 400 million people have CHB [2], of whom 15 to 40%
will eventually experience serious complications (hepatic
cirrhosis, hepatic decompensation or HCC) [3]. Develop-
ment of complications is associated with persistent replica-
tion of the hepatitis B virus (HBV) [2]; hence, an important
goal of CHB treatment is long-term suppression of HBV
replication to undetectable levels, as measured by serum
HBV DNA (virologic response) [2,4]. Normalization of
serum alanine transaminase (ALT), loss of hepatitis B e
antigen (HBeAg) and improvement in liver histology are
other recognized measures of CHB treatment efficacy.
* Correspondence: stuart.mealing@oxfordoutcomes.com
1
Oxford Outcomes Ltd, Seacourt Tower, West Way, Oxford OX2 0JJ, UK
Full list of author information is available at the end of the article
© 2014 Mealing et al.; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative
Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and
reproduction in any medium, provided the original work is properly credited.
Mealing et al. Systematic Reviews 2014, 3:21
http://www.systematicreviewsjournal.com/content/3/1/21
Current European clinical guidelines recommend the
following treatment options for CHB: entecavir, lamivudine,
telbivudine, adefovir dipivoxil, tenofovir dipivoxil fumarate,
peginterferon-alfa-2a, interferon-alfa-2a, and interferon-
alfa-2b [2]. Information on their relative efficacy is import-
ant in order for healthcare professionals and payers to make
evidence-based decisions on which treatments to prescribe.
Because head-to-head comparisons of competing CHB
treatment options via randomised clinical trials (RCTs)
are not available for all comparators in HBeAg antigen-
positive or -negative CHB, indirect evidence in the form
of network meta-analyses (NMAs) has been used to es-
timate relative efficacy. NMAs extend conventional, pair-
wise meta-analysis, and are based on the principle that
within trial estimates of relative treatment effects can be
added and subtracted [5,6].
An important assumption with NMAs is that the studies
used are sufficiently similar in terms of relative treatment
effect modifiers [7] - that is, study-level factors that may
influence the size of the treatment effect seen with a par-
ticular pair-wise intervention. These include patient char-
acteristics, outcomes measured, and study design. Thus,
to ensure a fair comparison of interventions, it is essential
to control for differences between studies in terms of
potential relative treatment effect modifiers. In particular,
baseline differences in patient characteristics between differ-
ent trials may distort between-trial comparisons if appropri-
ate adjustments are not made.
In CHB, response to treatment varies according to the
outcome of interest, the agent used, and the patient’s
HBeAg status [2]. Patient/disease characteristics that have
been shown to predict response to treatment in at least
some categories include baseline viral load, serum ALT
level, HBV genotype, and activity score on liver biopsy
[2,4]. Ali and colleagues [8] analysed data from 1,353 pa-
tients in two RCTs of entecavir and found that higher
baseline viral load was associated with reduced odds of re-
sponse to treatment: when baseline viral load (by PCR)
was treated as a continuous variable, the odds of achieving
a response were reduced by a factor of 0.38 (62%) for
every one unit increase in log
10
PCR above a threshold of
400 copies/ml.
Given the absence of head-to-head RCTs for all in-
terventions, the objective of the current study was to
generate estimates of relative efficacy of achieving un-
detectable viral load (UVL) that take into account the
potential of baseline viral load to act as a treatment ef-
fect modifier, in order to provide like-for-like compari-
sons between treatments for CHB that take into account
the heterogeneity in baseline viral load across patient
populations in different trials.
In order to compare the results with previously pub-
lished NMAs, as well as demonstrate the implications
for clinical and reimbursement decisions of using such
estimates, we also generated unadjusted relative efficacy
estimates using similar methodologies to those used in
these previous analyses.
Methods
We carried out adjusted and unadjusted analyses, using
the same trial data for each, to explore the impact of
baseline viral load on treatment response at 1 year. The
interventions analysed at licensed doses were interferon
alfa, peginterferon alfa-2a/2b, lamivudine, adefovir dipi-
voxil, entecavir, tenofovir, telbivudine and also placebo.
Trials for inclusion in the NMAs were identified through
a systematic review of the literature.
The efficacy endpoints analysed in the unadjusted ana-
lysis were ALT normalization, histological improvement,
HBeAg seroconversion and achievement of UVL at 1 year.
Since Ali and colleagues [8] only generated results for one
endpoint (achievement of UVL at 1 year) the adjusted
analysis was necessarily restricted to this endpoint/time-
point. In all analyses, UVL was defined as reduction in
HBV DNA level (by PCR assay) below the trial specific
lower level of quantification (LLOQ).
Systematic review
We carried out a systematic review of RCTs of the inter-
ventions listed above. The inclusion criteria were RCTs
(phase II or III) of monotherapy interventions at licensed
dose, adults with CHB, reporting any of the endpoints of
interest, and published in English. Papers (full or other-
wise) reporting interim results and studies using the inter-
ventions of interest at non-licensed doses were excluded.
Searches were carried out in the Embase, Medline,
Medline in Process and Cochrane CENTRAL databases
between March and April 2011. No restriction was placed
on the earliest date of publication and all databases were
searched from date of inception. Search strategies com-
prised CHB disease and drug terms (a combination of
controlled vocabulary and free text terms), and also a be-
spoke RCT filter. A search was also made for abstracts
from the European Association for the Study of the Liver
and the American Association for the Study of Liver Dis-
eases 2010 and 2011 annual conferences. Search syntax
for all databases are available on request from the authors.
The search strategy used to search the Embase database is
presented in Additional file 1.
The studies were separated into four clinically distinct pa-
tient groups: treatment-naïve HBeAg-positive or -negative,
lamivudine refractory and ‘other’. Abstract screening was
performed by two authors and included in the full paper re-
view if one reviewer thought it relevant. Formal full paper
review was undertaken by two reviewers against the pre-
specified inclusion criteria with a third acting as mediator
in situations of disagreement. Three authors independently
extracted study characteristics and the outcome data
Mealing et al. Systematic Reviews 2014, 3:21 Page 2 of 12
http://www.systematicreviewsjournal.com/content/3/1/21
required for the NMA using a standard form. Discrepancies
were resolved by one of two other authors. Outcome data
from weeks 48 and 52 were assumed to refer to 1 year. A
risk of bias assessment was carried out using Cochrane
methodology for those RCTs reported as full papers [9]. No
formal protocol was created for this review.
Statistical analyses
Given the lack of head-to-head trial evidence estimating
the relative efficacy of all licensed interventions, we used
an NMA approach to synthesise the evidence. In the NMA
methodology the difference in effect between treatments A
and B is equal to the difference in effects between treat-
ments A and C, and B and C. The analysis can be expanded
to more complex networks of evidence, and can produce
estimates of both mean effect and uncertainty [10].
Fixed effect models were used in the unadjusted analysis.
For the adjusted analyses we used both fixed and random
effects models, and final model choice in all analyses was
based on deviance information criteria (DIC) [11].
Choice of prior distribution for parameters in NMA
models is an important consideration, especially in the
presence of sparse networks of evidence. Uninformative
priors were used in the unadjusted analyses for all model
parameters. In all covariate-adjusted analyses the results
from Ali and colleagues [8] were used to inform the
prior distribution on the regression coefficient associated
with baseline viral load. Variations in baseline viral load
in each study arm (where there were differences) were
incorporated into the adjusted analyses via the use of the
average baseline HBV DNA value across arms within a
given RCT.
Baseline viral load was assumed to modify treatment
effects relative to entecavir (0.5 mg), which was also used
as the baseline against which all relative efficacy estimates
were calculated. To make the results easier to interpret by
a non-statistical audience, we represented relative efficacy
as a relative risk (RR) of response instead of the more nat-
ural odds ratio. We reported the mean of the posterior
probability distribution as well as the 95% credible interval
(CrI) for each RR. When the 95% CrI did not include the
value one, the RR was considered significantly different to
that for entecavir.
In order to compare the results of the analyses with
the input data, as well as presenting the output in an in-
tuitive manner, we also generated the absolute predicted
posterior probabilities of response for each clinical out-
come and treatment combination. In the adjusted NMA
we also undertook a range of sensitivity analyses whereby
in addition to the use of fixed and random effects models,
the impact of adding or removing individual studies due
to heterogeneity was assessed. Caterpillar, density and
Brooks-Gelman-Rubin plots were examined in all analyses
to ensure model convergence.
The analyses were conducted in WinBUGS Version 1.4
(MRC Biostatistics Unit, Cambridge, UK) [12] using Bayesian
Markov Chain Monte-Carlo Gibbs sampling methods.
Results
Search results and summary of studies
Our search of clinical databases identified 3,000 abstracts;
179 articles, including clinical study reports (CSRs), were
ordered/requested for review, of which 35 (six CSRs) met
the inclusion criteria [13-48]. The contents of five of the
CSRs had been reported in peer reviewed publications
already captured by the search and hence the published
data were used [18,26,37,42,44]. One CSR (BMS study
AI463023) [13] and the Summary of Product Characteris-
tics for telbivudine [22] were included in the review. In
total, the review identified 29 unique trials. Of these, 19
contained information in HBeAg-positive patients, and 14
of the 19 reported enough information to warrant inclu-
sion in a NMA, and 13 reported information on UVL at
that timepoint [13-15,18,20-24,26,28,30,32,48].
The study selection process is presented as a PRISMA
diagram in Figure 1. The PRISMA 2009 checklist is repor-
tedin Additional file 2. Study characteristics and reported
UVL at 1 year (defined as either 48 or 52 weeks) are shown
in Table 1. The assessment of study quality undertaken as
part of the systematic review is reported in Additional file
1: Table S1. Studies identified by the systematic review used
a range of LLOQ values from 1,000 to 200 copies/ml.
Unadjusted network meta-analysis
The network of evidence used to generate all results is
presented in Figure 2. The results of the fixed effects
analysis are presented as relative risks in Table 2 and ab-
solute probabilities of response in Additional file 1: Table
S2. There was only one instance where a treatment per-
formed significantly better than entecavir: the RR for
tenofovir achieving UVL was 1.43 (95% CrI 1.30 to 1.54).
With the exception of telbivudine which demonstrated no
statistically significant difference to entecavir (RR 0.88,
95% CrI 0.76 to 1.00) all other interventions performed
significantly less well than entecavir.
Adjusted network meta-analysis
The primary adjusted analysis of achieving UVL at 1 year,
when accounting for baseline viral load, was undertaken
using materials available in the public domain (the “base
case”). Thus, the material extracted from the CSR was
excluded. In addition, the baseline rates for two studies
were very different to the remainder in that they were
assessed using a different assay with very different LLOQ
definitions suggesting that baseline data were collected
in a different manner to all other studies [16,24]. These
studies were also excluded from the base case analysis.
One study, TBVIG, reported median rather than mean
Mealing et al. Systematic Reviews 2014, 3:21 Page 3 of 12
http://www.systematicreviewsjournal.com/content/3/1/21
baseline viral load and was hence also excluded from the
base case-adjusted analysis [30]. Information on this study
is provided in Table 1. Data from the ten studies that re-
ported baseline viral load were used in the adjusted ana-
lyses [14,15,18,20-23,26-28,31,48].
The results are presented as relative efficacy estimates in
the second column of Table 3 and as absolute probabilities
of UVL at 1 year in Figure 3 (fixed effects) and Figure 4
(random effects).
The relative risk estimates produced by the fixed and ran-
dom effects base case analyses were very similar. In particu-
lar, entecavir produced significantly increased RRs of UVL
at 1 year compared with all interventions except telbivudine
and tenofovir, for which the likelihood was similar. In con-
trast to the unadjusted analysis, the relative efficacy of ente-
cavir and tenofovir for achieving UVL was not significantly
different. Thus, baseline viral load is a significant moderator
of the effects of monotherapies for CHB. The DIC estimate
for the fixed effect model was lower than that for the ran-
dom effects model and was thus the preferred approach.
Adjusted network meta-analysis: sensitivity analyses
Exclusion of data from one adefovir study
The reported 1 year UVL rate for adefovir patients
as reported by the 018 Study Group is approximately
two to three times higher than reported for adefovir
in all other studies (Table 1). In contrast, the absolute
response rate for patients receiving telbivudine re-
ported by this study was in line with that observed in
the other studies. The impact of removing this study
is presented in column three of Table 3, and in
Figures 3 and 4.
The DIC statistics for both fixed and random effects
models were similar, with the random effects analysis repre-
senting the best fitting model. While the results overall are
similar to those in the base case analyses, the greatest im-
pact is observed in the tenofovir results, with a relative risk
value of 1.08 (95% CrI 0.22 to 1.52). Of note, the derived
absolute response probabilities for entecavir and tenofovir
in this scenario were 65.9% and 71.4%, respectively (ran-
dom effects model). The corresponding values in the key
regulatory trials were 66.7% and 76.5%, respectively.
Exclusion of data from the 018 Study Group, and inclusion
of data from AI463023 and TBVIG
The systematic review identified two additional studies
which contained information of potential interest: as yet
unpublished data from BMS study AI463023 and median
baseline values from the TBVIG study [13,29]. When
these data were included, but the data from 018 remained
3000 records identified through database searching:
1317 EMBASE
770 MEDLINE® and MEDLINE® In-Process
913 CENTRAL
293 conference abstracts identified
80 from EASL 2010 and 2011 213
from AASLD 2 009 and 2010
2113 records
following
de-duplication
2406 records screened for eligibility
2113 full papers
293 conference abstracts
2224 excluded at abstract and title review
1934 full papers
290 conference abstracts
179 full text articles/ Clinical Study Reports
screened for eligibility
35 distinctive items included in qualitative
synthesis
149 full text articles excluded
9 not appropriate patient group
49 not full paper publication
4 no appropriate endpoints reported
45 not appropriate drug in trial
7 not English Langua ge
21 not randomised controlled trial
9 follow up/further analyses
5 previously reported trials
29 unique trials included
14 trials in HBeAg-positive patients
considered for inclusion in the NMA
10 studies excluded for not being
performed in HBeAg positive CHB
5 studies excluded for not reporting
endpoint data at one year
Figure 1 PRISMA diagram of studies included in the systematic review. AASLD, American Association for the Study of Liver Diseases; CHB,
chronic hepatitis B; EASL, European Association for the Study of the Liver; HBeAg, hepatitis B e antigen; NMA, network meta-analysis.
Mealing et al. Systematic Reviews 2014, 3:21 Page 4 of 12
http://www.systematicreviewsjournal.com/content/3/1/21
Table 1 Study characteristics and 1-year outcomes of studies included in the network meta-analysis (HBeAg-positive patients only)
Source Treatment
duration
Study design Number
of patients
Treatment Age
(years)
Male
(%)
Endpoint
timepoint
Method used to
measure HBV DNA
LLOQ Baseline viral load
(log
10
copies/ml)
Undetectable HBV
DNA at 1 year (%)
018 Study Group [13] 52 weeks Randomised,
controlled, open label
45 TBV
600 mg
34 78 52 weeks Amplicor PCR
Assay (Roche)
300 copies/ml 9.57 60
44 ADV 10 mg 30 91 9.98 40.9
ADV 437 Study
Group [14]
48 weeks Randomised,
single blind
167 Placebo 37 71 48 weeks Amplicor PCR
Assay (Roche)
400 copies/ml 8.12 0
171 ADV 10 mg 34 76 8.25 21.1
AHLSG [15] 52 weeks Randomised,
double blind
72 Placebo 29 72 52 weeks Solution hybridising
assay (Abbott)
1.6 pg/ml 1.85 NR
143 LAM
100 mg
31 74 1.8 NR
AI463023 [12] 96 weeks Phase 3 randomised,
double blind
225 ETV 0.5 mg - - 52 weeks PCR assay (company
unspecified)
300 copies/ml 8.80 73.8
221 LAM
100 mg
- - 8.70 37.6
BeHoLD_I [17] 60 weeks Phase 3 randomised,
double blind
354 ETV 0.5 mg 35 77 48 weeks Amplicor PCR
Assay (Roche)
300 copies/ml 9.62 66.7
355 LAM
100 mg
35 74 9.69 36.3
Globe study group
[19-21]
NR Phase 3 randomised,
double blind
463 LAM
100 mg
33 76 52 weeks Amplicor PCR
Assay (Roche)
300 copies/ml 9.50 40.4
458 TBV
600 mg
32 73 9.50 60
Hou [22] 104 weeks Phase 3 randomised,
double blind
147 TBV
600 mg
28 80 52 weeks Amplicor PCR
Assay (Roche)
300 copies/ml 9.30 66.7
143 LAM
100 mg
29 75 9.70 37.8
ILSG [23] 52 weeks Randomised, partially
double blind
82 LAM
100 mg
30 71 52 weeks Solution hybridising
assay (Abbott)
1.6 pg/ml 2.04 60
69 IFNA 32 81 1.78 29.1
Lau [47] 72 weeks Phase 3 randomised,
double blind
271 PegIFNA 32.5 79 48 weeks Amplicor PCR
Assay (Roche)
400 copies/ml 9.90 25.1
272 LAM
100 mg
31.6 79 10.10 39.7
Leung [25] Minimum 52 weeks Phase 3 randomised,
open label
33 ETV 0.5 mg 37 61 48 weeks Amplicor PCR
Assay (Roche)
300 copies/ml 10.30 57.6
32 ADV 10 mg 32 66 9.88 18.8
Marcellin [26] 48 weeks Phase 3 randomised,
double blind
176 TDF
300 mg
34 68 48 weeks Cobas Taq-Man PCR
Assay (Roche)
169 copies/ml 8.64 76.1
90 ADV 10 mg 34 71 8.88 13.3
Ren [27] 48 weeks Randomised 21 LAM
100 mg
34 52 48 weeks PCR assay (company
unspecified
Unspecified 8.49 38
21 ETV 0.5 mg 31 57 8.52 71.4
Mealing et al. Systematic Reviews 2014, 3:21 Page 5 of 12
http://www.systematicreviewsjournal.com/content/3/1/21
Table 1 Study characteristics and 1-year outcomes of studies included in the network meta-analysis (HBeAg-positive patients only) (Continued)
TBVIG [29] 52 weeks Phase 2 randomised,
double blind
19 LMV
100 mg
34 74 52 weeks Amplicor PCR
Assay (Roche)
200 copies/ml N/R 31.6
22 TBV
600 mg
40 82 N/R 61.4
USLIG [30] 68 weeks Prospective,
randomised,
double blind
71 Placebo 38 80 52 weeks Unspecified Unspecified 5.70 15.9
66 LAM
100 mg
40 86 10.20 44.4
The systematic review identified 21 studies reporting hepatitis B e antigen (HBeAg)-positive patients; this table only shows the 14 studies included in the network meta-analysis. The remaining 7 studies did not report
outcomes at 1 year and so were not included in the network meta-analysis. *Patient numbers for overall population provided, baseline viral load and hepatitis B virus (HBV) DNA reported as HBeAg-positive/HBeAg-
negative, outcomes for HBeAg-positive patients only. ADV, adeforvir; ETV, entecavir; IFNA, interferon-alfa; LAM, lamivudine; LLOQ, lower level of quantification; NR, not reported; PegIFNA, pegylated interferon-alfa 2a;
TBV, telbivudine; TDF, tenofovir.
Mealing et al. Systematic Reviews 2014, 3:21 Page 6 of 12
http://www.systematicreviewsjournal.com/content/3/1/21
excluded, the corresponding results from this analysis are
presented in column four of Table 3, and in Figures 3 and 4.
The random effects analysis generated the lowest DIC
and is therefore the preferred model. There was no sig-
nificant difference between the relative efficacy of ente-
cavir, telbivudine and tenofovir, but entecavir performed
significantly better than all other interventions. These
results are in contrast to the unadjusted results. The
absolute probabilities derived using a random effects
model for tenofovir, telbivudine and entecavir were simi-
lar to those observed in the landmark RCTs.
Discussion
NMA can be used to generate relative efficacy estimates
of competing treatments in situations where more than
two treatment options are available and direct head-to-
head evidence from RCTs does not exist for all compara-
tors. The NMA approach allows all relevant evidence to
be considered and addresses research questions in the
absence of direct comparative evidence, improving the
precision of estimates by combining direct and indirect
evidence.
One of the key assumptions underpinning this method
is that the studies included in the analysis are homoge-
neous (that is, the trials are sufficiently similar on study
and patient characteristics). The similarity assumption is
violated if one or more study-level covariates act as
modifiers of the relative treatment effects and their dis-
tribution is not balanced across the studies being com-
pared [49,50]. In this case, NMA may be affected by
confounding bias, unless one explicitly controls for these
covariates in the statistical analyses.
Controlling for covariates is particularly important in
cases where response to treatment is defined in terms of
post-treatment level of a measure, and when that base-
line level of this measure is known to vary across studies.
If one study recruits patients with worse levels of a vari-
able that is known to modify the relative impact of treat-
ment, then the level of response achieved is likely to be
smaller compared with another study which primarily
includes patients with better baseline levels, other things
being equal.
The motivation for our work was the belief that such
baseline covariate imbalances had occurred for patients
recruited into studies looking at interventions for CHB.
In particular, it was noted that there were differences in
mean baseline viral load (expressed in terms of log
10
copies/ml when measured using the PCR assay) with
values for entecavir and tenofovir differing by approxi-
mately 1 log
10
copies/ml (Table 1). We hypothesised that
failure to account for these differences in previous ana-
lyses may have led to biased estimates of relative efficacy.
The work contained in this paper supports this hy-
pothesis. When no adjustment was made to account for
differences in baseline viral load among trials, tenofovir
was shown to be significantly better than entecavir in
terms of achieving UVL at 1 year (fixed effects RR 1.43,
95% CrI 1.30 to 1.54). However, when we accounted for
the impact of baseline viral load the difference between
the two treatments was not significant (fixed effects RR
1.27, 95% CrI 0.96 to 1.47; random effects RR 1.21, 95%
Table 2 Unadjusted efficacy estimates relative to
treatment with entecavir
Fixed effects model
Entecavir 0.5 mg 1.00 (Baseline)
Adefovir 10 mg 0.64 (0.42, 0.87)
Lamivudine 100 mg 0.54 (0.46, 0.63)
Placebo 0.10 (0.04, 0.19)
Telbivudine 600 mg 0.88 (0.76, 1.00)
Tenofovir 245 mg 1.43 (1.30, 1.54)
Interferon alfa 0.21 (0.09, 0.38)
Peginterferon alfa-2a/2b 0.34 (0.23, 0.46)
Results are shown as relative risk (95% credible interval). A relative risk <1
should be interpreted as a given treatment being less efficacious (that is,
worse) than entecavir, and a value >1 being more efficacious (that is, better).
Placebo
Entecavir
Adefovir
Lamivudine
Tenofovir
Telbivudine
3 studies
1 study
1 study
1 study
1 study
3 studies
1 study
Interferon
Peg Interferon
1 study
1 study
Figure 2 Evidence networks of studies used to generate unadjusted results for the undetectable viral load endpoint.
Mealing et al. Systematic Reviews 2014, 3:21 Page 7 of 12
http://www.systematicreviewsjournal.com/content/3/1/21
CrI 0.48 to 1.51). The fixed effects adjusted model best fit-
ted the underlying data, although the difference was minor
(fixed effects DIC, 35.56; random effects DIC, 35.86).
Sensitivity analyses highlighted that the relative effi-
cacy of tenofovir versus entecavir was contingent on the
choice of studies included in the meta-analysis, and in
particular whether or not data reported by one study
group [13] were used. When these data were excluded,
there is no significant difference between the two inter-
ventions (RR 1.08, 95% CrI 0.22 to 1.52). A subsequent
sensitivity analysis, whereby this study was removed but
two other studies were included (AI463023 and TBVIG),
generated similar non-significant results (RR 1.15, 95%
CrI 0.39 to 1.50). In both sensitivity analyses the most
appropriate model, based on DIC, consisted of random
as opposed to fixed effects approaches. Close examin-
ation of the published paper [14] has identified no rea-
son why this result should occur, and so there may be
some other form of study level heterogeneity as yet un-
accounted for that is influencing the results.
Our paper is the first to generate baseline viral load
adjusted and unadjusted NMA results using data from
the same set of studies, and the results from the un-
adjusted analyses are very similar to those generated by
other research groups [51,52]. Accepting that NMA is
based on relative efficacy, the results from all three un-
adjusted analyses for UVL appear to be at odds with
those provided by the clinical trials included in the NMA.
The systematic review identified one study of tenofovir
[27] and the observed response rate was 76%. The corre-
sponding value arising from our NMA was 93.2% (95%
CrI 85.6% to 97.6%). Similar values were generated by two
other research groups [51,52]. One other NMA has been
recently published [53]. This analysis, however, contains a
number of methodological flaws, the most notable being
the pooling of data from HBeAg-positive and -negative in-
dividuals. We have therefore not extracted results from
this paper for the purposes of discussion.
In contrast, with the exception of placebo and interferon-
based therapies, the CrIs for the values derived in the
Table 3 Adjusted relative risk estimates for virologic response, expressed as relative risk of achieving undetectable
viral load
Intervention Base case Base case without
018 study group
Base case without 018 study group;
with AI4463023 + TBVIG
Fixed effects analyses
Entecavir 0.5 mg 1.00 (Baseline) 1.00 (Baseline) 1.00 (Baseline)
Adefovir 10 mg 0.33 (0.14, 0.62) 0.23 (0.05, 0.56) 0.33 (0.10, 0.70)
Lamivudine 100 mg 0.38 (0.22, 0.58) 0.38 (0.22, 0.58) 0.52 (0.41, 0.64)
Placebo 0.01 (0.00, 0.03) 0.00 (0.00, 0.02) 0.01 (0.00, 0.03)
Telbivudine 600 mg 0.67 (0.43, 0.92) 0.67 (0.44, 0.92) 0.86 (0.71, 1.01)
Tenofovir 245 mg 1.27 (0.96, 1.47) 1.12 (0.61, 1.43) 1.25 (0.84, 1.48)
Interferon alpha 0.14 (0.05, 0.29) 0.13 (0.05, 0.29) 0.20 (0.08, 0.37)
Peginterferon alpha-2a/2b 0.23 (0.11, 0.39) 0.22 (0.11, 0.39) 0.32 (0.21, 0.46)
Residual deviance 19.48 17.10 21.54
DIC 35.56 32.14 39.15
Random effects analyses
Entecavir 0.5 mg 1.00 (Baseline) 1.00 (Baseline) 1.00 (Baseline)
Adefovir 10 mg 0.33 (0.07, 0.82) 0.27 (0.03, 0.95) 0.29 (0.04, 0.78)
Lamivudine 100 mg 0.37 (0.09, 0.84) 0.42 (0.07, 1.09) 0.51 (0.23, 0.86)
Placebo 0.01 (0.00, 0.06) 0.01 (0.00, 0.07) 0.01 (0.00, 0.04)
Telbivudine 600 mg 0.64 (0.18, 1.19) 0.72 (0.12, 1.39) 0.86 (0.41, 1.27)
Tenofovir 245 mg 1.21 (0.48, 1.51) 1.08 (0.22, 1.52) 1.15 (0.39, 1.50)
Interferon alpha 0.16 (0.01, 0.67) 0.20 (0.01, 0.94) 0.22 (0.03, 0.67)
Peginterferon alpha-2a/2b 0.25 (0.03, 0.88) 0.30 (0.02, 1.13) 0.34 (0.07, 0.88)
Residual deviance 18.23 16.12 19.78
DIC 35.86 32.10 39.07
Results are shown as relative risk (95% credible interval). “Base case”refers to the adjusted analysis undertaken using the 10 studies listed in the document
containing appropriate information. As with the unadjusted analyses, a relative risk <1 should be interpreted as a given treatment being less efficacious (that is,
worse) than entecavir and a value >1 being more efficacious (that is, better). DIC, deviance information criteria.
Mealing et al. Systematic Reviews 2014, 3:21 Page 8 of 12
http://www.systematicreviewsjournal.com/content/3/1/21
adjusted analyses all contain the observed trial values, and
the RR estimates are close to the trial values once the 018
Study Group data are removed (Figures 3 and 4). Hence,
we would argue that the adjusted results are of greater clin-
ical relevance than the unadjusted results.
Generating ‘like-for-like’estimates of relative efficacy
by controlling for covariates believed to be modifiers of
relative treatment effects is not just of clinical interest
but is essential for the purposes of reimbursement deci-
sions. Such estimates are used by agencies such as the
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
Absolute response probabilities
Tenofovir
245mg
Entecavir
0.5mg
Telbivudine
600mg
Lamivudine
100mg
Peginterferon
alpha-2a/2b
600m
g
Interferon
alpha
Adefovir
10mg
Placebo
Key trial data
Unadjusted
Basecase
Basecase without 018 study group
Basecase without 018 study group;
with AI4463023 + TBVIG
Figure 4 Absolute probability of undetectable viral load at 1 year (random effects). “Basecase”refers to the adjusted analysis undertaken
using the ten studies listed in the document containing appropriate information.
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
Absolute response probabilities
Tenofovir
245mg
Entecavir
0.5mg
Telbivudine
600mg
Lamivudine
100mg
Peginterferon
alpha-2a/2b
600m
g
Interferon
alpha
Adefovir
10mg
Placebo
Key trial data
Unadjusted
Basecase
Basecase without 018 study group
Basecase without 018 study group;
with AI4463023 + TBVIG
Figure 3 Absolute probability of undetectable viral load at 1 year (fixed effects). “Basecase”refers to the adjusted analysis undertaken
using the ten studies listed in the document containing appropriate information.
Mealing et al. Systematic Reviews 2014, 3:21 Page 9 of 12
http://www.systematicreviewsjournal.com/content/3/1/21
National Institute for Health and Care Excellence in their
appraisal processes when assessing the clinical efficacy in a
given disease area [54]. In addition, such values are also
used in economic models to evaluate the cost-effectiveness
of interventions. A number of such models have been de-
veloped in CHB [55-59], of which one [57] used the results
from their unadjusted analysis directly as model inputs.
Another [59] used UVL as a surrogate variable for risk of
cirrhosis using information from the REVEAL-HBV study
[60], which quantified the relationship between HBV DNA
and the likelihood of being diagnosed with cirrhosis. Over-
estimation of virologic response would thus correspond to
underestimation of the likelihood of cirrhosis, which has
been identified as a key driver of cost-effectiveness.
Despite the review finding a decent number of studies
overall, as can be seen from Figure 2, the presence of a
large number of treatment options means that the ma-
jority of the branches in the network are informed by
the findings of a single study. This increases the uncer-
tainty surrounding all results and means that baseline
imbalances in other potential treatment effect modifiers
may have influenced the results.
Further work is needed to complement the work con-
tained in this paper in connection with the achievement
of UVL at 1 year in order to explore the impact of other
potentially clinically relevant covariates on the relative
effects of comparators and the probability of achieving
UVL. Exploring the impact of other areas of potential
heterogeneity (for example, study design, impact of dif-
ferent LLOQ definitions) is also important. In addition,
Ali and collagues [8] identified the time of assessment as
a treatment effect modifier in addition to baseline viral
load. The studies included in this analysis were very simi-
lar in terms of assessment times and so the exclusion of
this variable is likely to have had a modest effect. None-
theless, it would be interesting to replicate the analyses
contained in this paper when controlling for these
slight differences. Furthermore, expanding this type of
analysis to other clinically relevant endpoints is also
worthwhile.
Conclusions
The analysis showed that baseline viral load is a treat-
ment effect modifier in CHB and that failure to cor-
rect for this variable inflates the relative efficacy estimates
for some interventions. Since these estimates are often
used in economic models to generate cost-effectiveness
estimates, failure to adjust for baseline viral load will gen-
erate erroneous ICERs, resulting in poor use of scarce
healthcare resources. As such, reimbursement agencies
should therefore only use covariate-adjusted relative
efficacy estimates in their decision making surrounding
treatments for CHB.
Additional files
Additional file 1: Supplementary material, including Embase search
strategy, assessment of study quality for all included trials (Table S1)
and comparison of current and previous NMA results (Table S2).
Additional file 2: PRISMA 2009 checklist.
Abbreviations
ALT: alanine transaminase; CHB: chronic hepatitis B; CrI: credible interval;
CSR: clinical study report; DIC: deviance information criteria; HBeAg: hepatitis
B e antigen; HBV: hepatitis B virus; HCC: hepatocellular carcinoma; LLOQ: lower
level of quantification; NMA: network meta-analysis; PCR: polymerase chain
reaction; RCT: randomised clinical trials; RR: relative risk; UVL: undetectable viral load.
Competing interests
SM, MW, NH and DAS all work for an international consultancy and have
received funding from numerous pharmaceutical companies including
Bristol-Myers Squibb. BL and IG are independent consultants and have
received funding from numerous pharmaceutical companies including
Bristol-Myers Squibb. EM and BB are employees of Bristol-Myers Squibb. PL,
MT, LM and MC have all received speaking bureau (paid speaking invitation)
from multiple pharmaceutical companies including Bristol-Myers Squibb.
Authors’contributions
IG performed and validated all network meta-analyses. NH and DAS performed
and validated all network meta-analyses and also acted as adjudicators in the
systematic review process as well as acting as co-supervisors for the project. SM
assisted in all aspects of the systematic review, led the preparation of the
manuscript, worked with SA in developing the patient level data analysis and
performed day-to-day management of the project. MW designed all search
strategies used in the systematic review and performed additional systematic
review tasks including checking data extraction. BB and EM obtained funding
for the project, contributed to the project analysis protocol (unpublished) and
acted as external clinical reviewers to the process. As such the authors
performed technical and clinical validation on all inputs and outputs to the
process. BL contributed to the project analysis protocol (unpublished) and acted
as external clinical reviewer to the process. As such the author performed
technical and clinical validation on all inputs and outputs to the process, and
was also responsible for developing the study concept. MT, PL, LM and MC
contributed to the project analysis protocol (unpublished) and acted as external
clinical reviewers to the process. As such the authors performed technical and
clinical validation on all inputs and outputs to the process. All authors read and
approved the final manuscript.
Acknowledgements
The authors thank Jo Whelan (Textpharm Ltd) and Juliette Thompson
(Oxford Outcomes) for providing medical writing assistance. The project was
funded via a consultancy agreement between Bristol-Myers Squibb and
Oxford Outcomes.
Author details
1
Oxford Outcomes Ltd, Seacourt Tower, West Way, Oxford OX2 0JJ, UK.
2
Ghement Statistical Consulting Company Ltd, Richmond, Canada.
3
Xintera
Consulting, Leuven, Belgium.
4
Department of medicine, Imperial College,
London, UK.
5
1st Division of Gastroenterology, A.M. e A. Migliavacca Centre
for the Study of Liver Disease, Milan, Italy.
6
School of Pharmacy at the
University of Milan, Milan, Italy.
7
Bristol-Myers Squibb, Rueil-Malmaison,
France.
8
University Claude Bernard Lyon 1, Lyon, France.
Received: 27 June 2013 Accepted: 11 February 2014
Published: 7 March 2014
References
1. World Health Organization: Hepatitis B: Fact Sheet 204. http://who.int/
mediacentre/factsheets/fs204/en/.
2. European Association for the Study of the Liver: EASL clinical practice
guidelines: management of chronic hepatitis B virus infection. J Hepatol
2012, 57:167–185.
3. Bosch FX, Ribes J, Cléries R, Díaz M: Epidemiology of hepatocellular
carcinoma. Clin Liver Dis 2005, 9:191–211.
Mealing et al. Systematic Reviews 2014, 3:21 Page 10 of 12
http://www.systematicreviewsjournal.com/content/3/1/21
4. Lok ASF, McMahon BJ: AASLD practice guidelines. Chronic hepatitis B:
update 2009. Hepatology 2009, 50:661–662.
5. Caldwell D, Ades AE, Higgins JP: Simultaneous comparison of multiple
treatments: combining direct and indirect evidence. BMJ 2005, 331:897–900.
6. Lu G, Ades AE: Combination of direct and indirect evidence in mixed
treatment comparisons. Stat Med 2004, 23:3105–3124.
7. Song F, Loke YK, Walsh T, Glenny AM, Eastwood AJ, Altman DG:
Methodological problems in the use of indirect comparisons for
evaluating healthcare interventions: survey of published systematic
reviews. BMJ 2009, 338:b1147.
8. Ali S, Mealing S, Hawkins N, Lescrauwaet B, Bjork S, Mantovani L, Lampertico P:
The use of individual patient data (IPD) to quantify the impact of
pre-treatment predictors of response to treatment in chronic hepatitis B
patients. BMJ Open 2013, 24:3.
9. Cochrane Handbook for Systematic Reviews of Interventions Version 5.0.2.
http://www.cochrane.org/training/cochrane-handbook.
10. Hoaglin DC, Hawkins N, Jansen JP, Scott DA, Itzler R, Cappelleri JC, Boersma C,
Thompson D, Larholt KM, Diaz M, Barrett A: Conducting indirect-treatment-
comparison and network-meta-analysis studies: report of the ISPOR Task
Force on Indirect Treatment Comparisons Good Research Practices: part 2.
Value Health 2011, 14:429–437.
11. Spiegelhalter DJ, Best NG, Carlin BP, Van Der Linde AJ: Bayesian measures
of model complexity and fit. Royal Stat Soc: Series B (Stat Methodol) 2002,
64:583–639.
12. Lunn DJ, Thomas A, Best N, Spiegelhalter D: WinBUGS –a Bayesian
modelling framework: concepts, structure, and extensibility. Stat Comput
2000, 10:325–337.
13. Bristol-Myers Squibb Ltd: Trial AI463023 Clinical Study Report. Data on file.
14. Chan HL, Heathcote EJ, Marcellin P, Lai CL, Cho M, Moon YM, Chao YC,
Myers RP, Minuk GY, Jeffers L, Sievert W, Bzowej N, Harb G, Kaiser R, Qiao XJ,
Brown NA, 018 Study Group: Treatment of hepatitis B e antigen positive
chronic hepatitis with telbivudine or adefovir: a randomized trial.
Ann Intern Med 2007, 147:745–754.
15. Marcellin P, Chang TT, Lim SG, Tong MJ, Sievert W, Shiffman ML, Jeffers L,
Goodman Z, Wulfsohn MS, Xiong S, Fry J, Brosgart CL, Adefovir Dipivoxil
437 Study Group: Adefovir dipivoxil for the treatment of hepatitis B e
antigen-positive chronic hepatitis B. N Engl J Med 2003, 348:808–816.
16. Lai CL, Chien RN, Leung NW, Chang TT, Guan R, Tai DI, Ng KY, Wu PC, Dent JC,
Barber J, Stephenson SL, Gray DF: A one-year trial of lamivudine for chronic
hepatitis B. N Engl J Med 1998, 339:61–68.
17. Bristol-Myers Squibb Ltd: Trial AI463022 Clinical Study Report. Data on file.
18. Chang TT, Gish RG, de Man R, Gadano A, Sollano J, Chao YC, Lok AS, Han KH,
Goodman Z, Zhu J, Cross A, DeHertogh D, Wilber R, Colonno R, Apelian D,
BEHoLD AI463022 Study Group: A comparison of entecavir and lamivudine
for HBeAg-positive chronic hepatitis B. N Engl J Med 2006, 354:1001–1010.
19. Cooksley WG, Piratvisuth T, Lee SD, Mahachai V, Chao YC, Tanwandee T,
Chutaputti A, Chang WY, Zahm FE, Pluck N: Peginterferon alpha-2a
(40 kDa): an advance in the treatment of hepatitis B e antigen-positive
chronic hepatitis B. J Viral Hepat 2003, 10:298–305.
20. Liaw YF, Gane E, Leung N, Zeuzem S, Wang Y, Lai CL, Heathcote EJ, Manns M,
Bzowej N, Niu J, Han SH, Hwang SG, Cakaloglu Y, Tong MJ, Papatheodoridis G,
Chen Y, Brown NA, Albanis E, Galil K, Naoumov NV, GLOBE Study Group:
2-Year GLOBE trial results: telbivudine is superior to lamivudine in patients
with chronic hepatitis B. Gastroenterology 2009, 136:486–495.
21. Lai CL, Gane E, Liaw YF, Hsu CW, Thongsawat S, Wang Y, Chen Y, Heathcote EJ,
Rasenack J, Bzowej N, Naoumov NV, Di Bisceglie AM, Zeuzem S, Moon YM,
Goodman Z, Chao G, Constance BF, Brown NA, Globe Study Group:
Telbivudine versus lamivudine in patients with chronic hepatitis B.
N Engl J Med 2007, 357:2576–2588.
22. Telbivudine Summary of Product Characteristics. http://www.ema.europa.eu/
docs/en_GB/document_library/EPAR_-_Product_Information/human/
000713/WC500049337.pdf.
23. Hou J, Yin YK, Xu D, Tan D, Niu J, Zhou X, Wang Y, Zhu L, He Y, Ren H, Wan M,
Chen C, Wu S, Chen Y, Xu J, Wang Q, Wei L, Chao G, Constance BF, Harb G,
Brown NA, Jia J: Telbivudine versus lamivudine in Chinese patients with
chronic hepatitis B: results at 1 year of a randomized, double-blind trial.
Hepatology 2008, 47:447–454.
24. Schalm SW, Heathcote J, Cianciara J, Farrell G, Sherman M, Willems B,
Dhillon A, Moorat A, Barber J, Gray DF: Lamivudine and alpha interferon
combination treatment of patients with chronic hepatitis B infection: a
randomised trial. Gut 2000, 46:562–568.
25. Bristol-Myers Squibb Ltd: Trial AI463079 Clinical Study Report. Data on file.
26. Leung N, Peng CY, Hann HW, Sollano J, Lao-Tan J, Hsu CW, Lesmana L,
Yuen MF, Jeffers L, Sherman M, Min A, Mencarini K, Diva U, Cross A, Wilber R,
Lopez-Talavera J: Early hepatitis B virus DNA reduction in hepatitis B e
antigen-positive patients with chronic hepatitis B: a randomized
international study of entecavir versus adefovir. Hepatology 2009, 49:72–79.
27. Marcellin P, Heathcote EJ, Buti M, Gane E, de Man RA, Krastev Z, Germanidis G, Lee
SS, Flisiak R, Kaita K, Manns M, Kotzev I, Tchernev K, Buggisch P, Weilert F, Kurdas
OO, Shiffman ML, Trinh H, Washington MK, Sorbel J, Anderson J, Snow-Lampart A,
Mondou E, Quinn J, Rousseau F: Tenofovir disoproxil fumarate versus adefovir
dipivoxil for chronic hepatitis B. NEnglJMed2008, 359:2442–2455.
28. Ren FY, Piao DM, Piao XX: A one-year trial of entecavir treatment in
patients with HBeAg-positive chronic hepatitis B. World J Gastroenterol
2007, 13:4264–4267.
29. Shindo M, Chayama K, Mochida S, Toyota J, Tomita E, Kumada H, Yokosuka O,
Sata M, Hayashi N, Suzuki K, Okanoue T, Tsubouchi H, Ishikawa H, Seriu T,
Omata M: Antiviral activity, dose–response relationship, and safety of
entecavir following 24-week oral dosing in nucleoside-naive Japanese adult
patients with chronic hepatitis B: a randomized, double-blind, phase II
clinical trial. Hepatol Int 2009, 3:445–452.
30. Lai CL, Leung N, Teo EK, Tong M, Wong F, Hann HW, Han S, Poynard T,
Myers M, Chao G, Lloyd D, Brown NA, Telbivudine Phase II Investigator
Group: A 1-year trial of telbivudine, lamivudine, and the combination in
patients with hepatitis B e antigen-positive chronic hepatitis B.
Gastroenterology 2005, 129:528–536.
31. Dienstag JL, Schiff ER, Wright TL, Perrillo RP, Hann HW, Goodman Z,
Crowther L, Condreay LD, Woessner M, Rubin M, Brown NA: Lamivudine as
initial treatment for chronic hepatitis B in the United States. N Engl J Med
1999, 341:1256–1263.
32. Yao G, Wang B, Cui Z, Yao J, Zeng M: A randomized double-blind
placebo-controlled study of lamivudine in the treatment of patients with
chronic hepatitis B virus infection. Chin Med J (Engl) 1999, 112:387–391.
33. Zeng M, Mao Y, Yao G, Wang H, Hou J, Wang Y, Ji BN, Chang CN, Barker KF:
A double-blind randomized trial of adefovir dipivoxil in Chinese subjects
with HBeAg-positive chronic hepatitis B. Hepatology 2006, 44:108–116.
34. ZhengMH,ShiKQ,DaiZJ,YeC,ChenYP:A 24-week, parallel-group, open-
label, randomized clinical trial comparing the early antiviral efficacy of telbivu-
dine and entecavir in the treatment of hepatitis B e antigen-positive chronic
hepatitis B virus infection in adult Chinese patients. Clin Ther 2010, 32:649–658.
35. Hadziyannis SJ, Tassopoulos NC, Heathcote EJ, Chang TT, Kitis G, Rizzetto M,
Marcellin P, Lim SG, Goodman Z, Wulfsohn MS, Xiong S, Fry J, Brosgart CL,
Adefovir Dipivoxil 438 Study Group: Adefovir dipivoxil for the treatment of
hepatitis B e antigen-negative chronic hepatitis B. [Erratum appears in N
Engl J Med. 2003 Mar 20;348(12):1192]. N Engl J Med 2003, 348:800–807.
36. Bonino F, Lau G, Marcellin P, Hadziyannis S, Kitis G, Jin R: The first detailed
analysis of predictors of response in HBeAg-negative chronic hepatitis B:
data from a multicenter, randomized, partially double-blind study of
peginterferon alfa-2a (40KD) (PEGASYS) alone or in combination with
lamivudine vs lamivudine alone. Hepatology 2004, 40:659A.
37. Lai CL, Shouval D, Lok AS, Chang TT, Cheinquer H, Goodman Z, DeHertogh D,
Wilber R, Zink RC, Cross A, Colonno R, Fernandes L, BEHoLD AI463027 Study
Group: Entecavir versus lamivudine for patients with HBeAg-negative
chronic hepatitis B. NEnglJMed2006, 354:1011–1020.
38. Chan HL, Wang H, Niu J, Chim AM, Sung JJ: Two-year lamivudine
treatment for hepatitis B e antigen-negative chronic hepatitis B: a
double-blind, placebo-controlled trial. Antiviral Therapy 2007, 12:345–353.
39. Tassopoulos NC, Volpes R, Pastore G, Heathcote J, Buti M, Goldin RD,
Hawley S, Barber J, Condreay L, Gray DF: Efficacy of lamivudine in patients
with hepatitis B e antigen-negative/hepatitis B virus DNA-positive (pre-
core mutant) chronic hepatitis B. Hepatology 1999, 29:889–896.
40. Marcellin P, Lau GK, Bonino F, Farci P, Hadziyannis S, Jin R, Lu ZM,
Piratvisuth T, Germanidis G, Yurdaydin C, Diago M, Gurel S, Lai MY, Button P,
Pluck N, Peginterferon Alfa-2a HBeAg-Negative Chronic Hepatitis B Study
Group: Peginterferon alfa-2a alone, lamivudine alone, and the two in
combination in patients with HBeAg-negative chronic hepatitis B. N Engl
J Med 2004, 351:1206–1217.
41. Bristol-Myers Squibb Ltd: Trial AI463026 Clinical Study Report. Data on file.
42. Sherman M, Yurdaydin C, Sollano J, Silva M, Liaw YF, Cianciara J, Boron-Kaczmarska
A, Martin P, Goodman Z, Colonno R, Cross A, Denisky G, Kreter B, Hindes R,
AI463026 BEHoLD Study Group: Entecavir for treatment of lamivudine-refractory,
HBeAg-positive chronic hepatitis B. Gastroenterology 2006, 2006:2039–2049.
Mealing et al. Systematic Reviews 2014, 3:21 Page 11 of 12
http://www.systematicreviewsjournal.com/content/3/1/21
43. Bristol-Myers Squibb Ltd: Trial AI463014 Clinical Study Report. Data on file.
44. Chang TT, Gish RG, Hadziyannis SJ, Cianciara J, Rizzetto M, Schiff ER, Pastore G,
Bacon BR, Poynard T, Joshi S, Klesczewski KS, Thiry A, Rose RE, Colonno RJ,
Hindes RG, BEHoLD Study Group: A dose-ranging study of the efficacy and
tolerability of entecavir in lamivudine-refractory chronic hepatitis B
patients. Gastroenterology 2005, 129:1198–1209.
45. Liaw YF, Sheen IS, Lee CM, Akarca US, Papatheodoridis GV, Suet-Hing Wong F,
Chang TT, Horban A, Wang C, Kwan P, Buti M, Prieto M, Berg T, Kitrinos K,
Peschell K, Mondou E, Frederick D, Rousseau F, Schiff ER: Tenofovir disoproxil
fumarate (TDF), emtricitabine/TDF, and entecavir in patients with
decompensated chronic hepatitis B liver disease. Hepatology 2011, 53:62–72.
46. Liaw YF, Sung JJ, Chow WC, Farrell G, Lee CZ, Yuen H, Tanwandee T, Tao QM,
Shue K, Keene ON, Dixon JS, Gray DF, Sabbat J, Cirrhosis Asian Lamivudine
Multicentre Study Group: Lamivudine for patients with chronic hepatitis B
and advanced liver disease. N Engl J Med 2004, 351:1521–1531.
47. Lai CL, Rosmawati M, Lao J, Van Vlierberghe H, Anderson FH, Thomas N,
Dehertogh D: Entecavir is superior to lamivudine in reducing hepatitis B
virus DNA in patients with chronic hepatitis B infection. Gastroenterology
2002, 123:1831–1838.
48. Lau GK, Piratvisuth T, Luo KX, Marcellin P, Thongsawat S, Cooksley G, Gane E,
Fried MW, Chow WC, Paik SW, Chang WY, Berg T, Flisiak R, McCloud P, Pluck N,
Peginterferon Alfa-2a HBeAg-Positive Chronic Hepatitis B Study Group:
Peginterferon alfa-2a, lamivudine, and the combination for HBeAg-positive
chronic hepatitis B. NEnglJMed2005, 352:2682–2695.
49. Jansen JP, Naci H: Is network meta-analysis as valid as standard pairwise
meta-analysis? It all depends on the distribution of effect modifiers.
BMC Med 2013, 11:159.
50. Salanti G: Indirect and mixed-treatment comparison, network, or
multiple-treatments meta-analysis: many names, many benefits, many
concerns for the next generation evidence synthesis tool. Res Synth
Method 2012, 3:80–97.
51. Dakin H, Fidler C, Harper C: Mixed treatment comparison meta-analysis
evaluating the relative efficacy of nucleos(t)ides for treatment of nucleos(t)
ide-naive patients with chronic hepatitis B. Value Health 2010, 13:934–945.
52. Woo G, Tomlinson G, Nishikawa Y, Kowgier M, Sherman M, Wong DK, Pham B,
Ungar WJ, Einarson TR, Heathcote EJ, Krahn M: Tenofovir and entecavir are
the most effective antiviral agents for chronic hepatitis B: a systematic
review and Bayesian meta-analyses. Gastroenterology 2010, 139:1218–1229.
53. Wiens A, Lenzi L, Venson R, Correr CC, Inajara I, Pedroso ML, Pontarolo R:
Comparative efficacy of oral nucleoside or nucleotide analog
monotherapy used in chronic hepatitis B: a mixed-treatment comparison
meta-analysis. Pharmacotherapy 2013, 33:144–151.
54. National Institute for Health and Clinical Excellence: Guideline to the Methods
of Technology Appraisal; 2012. http://www.nice.org.uk/aboutnice/
howwework/devnicetech/guidetothemethodsoftechnologyappraisal.jsp.
55. Veenstra DL, Sullivan SD, Clarke L, Iloeje UH, Tafesse E, Di Bisceglie A, Kowdley KV,
Gish RG: Cost effectiveness of entecavir versus lamivudine with adefovir salvage
in HBeAg-positive chronic hepatitis B. Pharmacoeconom 2007, 25:963–977.
56. Veenstra DL, Sullivan SD, Dusheiko GM, Jacobs M, Aledort JE, Lewis G, Patel KK:
Cost-effectiveness of peginterferon alpha-2a compared with lamivudine
treatment in patients with HBe-antigen-positive chronic hepatitis B in the
United Kingdom. European J Gastroenterol Hepatol 2007, 19:631–638.
57. Dakin H, Bentley A, Dusheiko G: Cost-utility analysis of tenofovir disoproxil
fumarate in the treatment of chronic hepatitis B. Value Health 2010, 13:922–933.
58. Shepherd J, Gospodarevskaya E, Frampton G, Cooper K: Entecavir for the treatment
of chronic hepatitis B infection. Health Technol Assess 2009, 13(Suppl 3):31–36.
59. Bristol-Myers Squibb Ltd: Entecavir (Baraclude) for the Treatment of Chronic Hepatitis
B: Single Technology Appraisal Submission to the National Institute for Health and
Clinical Excellence. http://www.nice.org.uk/nicemedia/live/11833/40303/40303.pdf.
60. Iloeje UH, Yang HI, Su J, Jen CL, You SL, Chen CJ, Risk Evaluation of Viral Load
Elevation and Associated Liver Disease/Cancer-In HBV (the REVEAL-HBV) Study
Group: Predicting cirrhosis risk based on the level of circulating hepatitis B
viral load. Gastroenterology 2006, 130:678–686.
doi:10.1186/2046-4053-3-21
Cite this article as: Mealing et al.:The importance of baseline viral load
when assessing relative efficacy in treatment-naïve HBeAg-positive
chronic hepatitis B: a systematic review and network meta-analysis.
Systematic Reviews 2014 3:21.
Submit your next manuscript to BioMed Central
and take full advantage of:
• Convenient online submission
• Thorough peer review
• No space constraints or color figure charges
• Immediate publication on acceptance
• Inclusion in PubMed, CAS, Scopus and Google Scholar
• Research which is freely available for redistribution
Submit your manuscript at
www.biomedcentral.com/submit
Mealing et al. Systematic Reviews 2014, 3:21 Page 12 of 12
http://www.systematicreviewsjournal.com/content/3/1/21
