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MAJOR ARTICLE
Determinants of Hepatitis C Virus Treatment
Completion and Efficacy in Drug Users
Assessed by Meta-analysis
Rositsa B. Dimova,
1
Marija Zeremski,
1
Ira M. Jacobson,
1
Holly Hagan,
2
Don C. Des Jarlais,
3
and Andrew H. Talal
1,4
1
Weill Cornell Medical College,
2
New York University College of Nursing,
3
Beth Israel Medical Center, New York, New York; and
4
State University of
New York at Buffalo
Background. Hepatitis C virus (HCV)–infected drug users (DUs) have largely been excluded from HCV care.
We conducted a systematic review and meta-analysis of the literature on treatment completion and sustained
virologic response (SVR) rates in DUs. We assessed the effects of different treatment approaches and services to
promote HCV care among DUs as well as demographic and viral characteristics.
Methods. Studies of at least 10 DUs treated with pegylated interferon/ribavirin that reported SVR were ana-
lyzed. Heterogeneity was assessed (Cochran test) and investigated (meta- regression), and pooled rates were esti-
mated (random effects).
Results. Thirty-six studies comprising 2866 patients were retrieved. The treatment completion rate among DUs
was 83.4% (95% confidence interval [CI], 77.1%–88.9%). Among studies that included addiction-treated and untreat-
ed patients during HCV therapy, the higher the proportion of addiction-treated patients, the higher the HCV treat-
ment completion rate (P < .0001). After adjusting for human immunodeficiency virus (HIV)/HCV coinfection, sex,
and treatment of addiction, support services during antiviral therapy increased treatment completion (P < .0001).
The pooled SVR rate was 55.5% (95% CI, 50.6%–60.3%). Genotype 1/4 (P = .0012) and the proportion of HIV-
coinfected DUs (P =.0173) influenced the SVR rate. After adjusting for HCV genotype 1/4 and HIV/HCV coinfec-
tion, the SVR rate was positively correlated with involvement of a multidisciplinary team (P <.0001).
Conclusions. Treatment of addiction during HCV therapy results in higher treatment completion. Our pooled
SVR rate is similar to that obtained in registration trials in the general population. Treatment of addiction during
HCV therapy will likely be important for HCV-infected DUs undergoing treatment with more complex regimens
including direct-acting antivirals.
Keywords. drug users; hepatitis C virus; treatment completion; SVR; meta-analysis.
An estimated 170 million people globally and 5
million people in the United States are infected with
hepatitis C virus (HC V), with injection drug use as
the major transmission route [1]. Fifty percent to
80% of those exposed to HCV will develop chronic
infection that can ultimately lead to hepatic fibrosis,
hepatocellular carcinoma, and cirrhosis [2]. Until
recently, pegylated interferon/ribavirin (PEG-IFN/
RBV) had been the standard treatment for all hepatitis
C genotypes, resulting in viral eradication in approxi-
mately 50% of treated patients [3, 4]. Recent approval
of boceprevir [5] and telaprevir [6] for HCV genotype
1–infected patients simultaneously increased treatment
efficacy and its complexity, necessitating rigorous
adherence to medication administration to mitigate
development of resistant variants.
In the United States, the majority of prevalent and
incident HCV infections occur in drug users (DUs) [7].
Unfortunately, however, HCV treatment uptake remains
low among DUs. Namely, less than one-third of pa-
tients referred to specialty clinics appear for evaluation
and <20% of those evaluated initiate antiviral therapy
Received 27 June 2012; accepted 19 November 2012; electronically published
7 December 2012.
Correspondence: Rositsa B. Dimova, PhD, Weill Cornell Medical College, 1300
York Ave, Box 319, New York, NY 10065 (rbd2005@med.cornell.edu).
Clinical Infectious Diseases 2013;56(6):806–16
© The Author 2012. Published by Oxford University Press on behalf of the Infectious
Diseases Society of America. All rights reserved. For Permissions, please e-mail:
journals.permissions@oup.com.
DOI: 10.1093/cid/cis1007
806
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[8–10]. DUs often cite discomfort encountered in convention-
al medical venues as a primary obstacle limiting pursuit of an
HCV evaluation [8]. Consequently, HCV therapeutic effective-
ness in DUs is an issue of treatment access, acceptance, and
adherence rather than drug ef ficacy [11].
Understanding the factors that influence adherence of DUs to
PEG-IFN/RBV has relevance to more complex treatment regi-
mens, such as those that include boceprevir and telaprevir.
While many factors that influence treatment outcome are
unmodifiable, treatment approaches tailored to DUs could be
pursued. To determine the influence of support services on
HCV treatment completion and therapeutic success, we conduct-
ed a meta-analysis of studies on DUs treated with PEG-IFN/
RBV. Because most of these studies have relatively small sample
sizes, their aggregation through meta-analysis increases statistical
power and facilitates generation of evidence-based conclusions.
METHODS
Search Methodology
We searched multiple electronic resources (including PubMed,
ClinicalTrials.gov, EMBASE) for studies of HCV treatment in
DUs using combinations of relevant keywords (hepatitis C
virus, drug users, substance use, sustained virological response
[SVR], pegylated interferon, ribavirin). We also reviewed refer-
ences from the retrieved articles. The last search was per-
formed in September 2011, resulting in 1144 studies screened
for eligibility.
The inclusion criteria for studies were (1) a population of at
least 10 DUs treated with PEG-IFN/RBV and (2) a reported
treatment outcome. Successful treatment outcome was defined
as achieving a sustained virologic response (SVR), that is, un-
detectable HCV RNA 24 weeks after treatment cessation. DUs
were defined as individuals who reported exposure to illicit
drugs (including injection and noninjection). Illicit drug expo-
sure was defined as the nonmedical use of drugs prohibited by
international law. We only included papers published in
English except for 1 Serbian study included because of a
native Serbian speaker on our team. Papers that did not satisfy
the inclusion criteria were excluded.
Thirty-four publications (published 2004–2011) comprising
a total of 2866 patients were included (Table 1). Because 2 pub-
lications [12, 13] contained independent arms, they were con-
sidered separately; thus, a total of 36 studies were evaluated.
Data Extraction
To facilitate data coding and extraction, we designed a form
(Supplementary Data). We collected information on treatment
completion rates and success, study design, demographic and
hepatic characteristics, treatment of addiction, support servic-
es, and methods to deliver HCV treatment. Each study was
coded independently by 2 investigators (R.B.D. and M.Z.),
coding results were compared, and discrepancies were resolved
by discussion between the 2 reviewers.
Statistical Analysis
Units in the meta-ana lysis were the independent studies. Main
variables of interest were the treatment completion and SVR
rates. We considered HCV treatment not completed if patients
were discontinued for any reason other than lack of viral re-
sponse (which is a standard PEG-IFN/RBV discontinuation
rule). Reasons for noncompletion included nonadherence,
substance abuse, patient unwillingness to complete therapy,
loss to follow-up, death, adverse events, or other reasons. The
SVR rate was determined by intention to treat as the propor-
tion of patients (DUs) who achieved an SVR among all DUs.
We used as outcomes the log odds for achieving an SVR and
the Freeman-Tukey double arcsine transformed [14] treatment
completion rates (due to rates equal to 1). Heterogeneity of
the effect sizes between the studies was investigated, tested
(Cochran test) and quantified through the Q and I
2
statistics
(proportion of total variation due to heterogeneity between
studies). If heterogeneity was present, a random effects model
was used for inference and the DerSimon ian-Laird estimator
[15] was used for the heterogeneity parameter.
We verified the assumptions of the model and investigated
for outliers using the Shapiro-Wilk normality test, as well as
weighted normal plots of the elements of Q [16]. In order to
determine the influence of the individual studies, we per-
formed influential analysis. Furthermore, interstudy variability
due to different study characteristics and factors, including
treatment of addiction, were assessed through meta-regression
analysis. Treatment of addiction was defined as participation
in a pharmacological maintenance, pharmacological detoxifi-
cation, or behavioral program, or a medication regimen for
individuals with drug addiction disorders. We also analyzed
specific support services designed to increase treatment adher-
ence including needle exchange, counseling, educational inter-
ventions for HCV, case management, directly observed
therapy, motivational interviewing, and peer support groups.
We also sought to determine whether involvement of a multi-
disciplinary team (defined as a systematic program for treat-
ment of HCV patients that includes specialists from 2 or more
areas) affected the treatment completion and SVR rates. These
teams were typically comprised of different specialists including
hepatologists, addiction medicine specialists, psychologists/
psychiatrists, infectious diseases specialists, and general practi-
tioners. We investigated the potential for publication bias
through funnel plots and Egger regression test of funnel plot
asymmetry. The significance level in all tests was .05, and all
analyses were conducted using SAS (SAS Institute, Cary,
North Carolina) and R (http://www.r-project.org/).
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RESULTS
Characteristics of the Studies
Thirty-six studies, ranging in size from 11 to 822 individuals,
were included (Table 1). All patients had a history of illicit
drug use, 77% (1606/2087) were male (10 studies did not
describe sex distribution), and the median age (across 24
studies that reported age) was 38.2 years (interquartile range
[IQR], 33.0 –42.5 years). Active/former DU definitions varied
with respect to the required duration of abstinence or were
missing across the 15 studies that considered these variables.
Based on the latter, 38.2% (656/1719) of the patients were
Table 1. Characteristics of Individual Studies Included in Meta-Analysis
a
Study
ID
First Author,
Year of Publication Location Study Design
Type of
Enrollment
Enrollment
Start Date
Enrollment
End Date No.
1 Grebely, 2007 [17] Canada Observational Prospective 1 Jan 2001 1 July 2003 28
5 Alvarez-Uria, 2009 [18] UK Observational Retrospective 1 Nov 2003 1 Aug 2006 70
6 Gazdik, 2009 [19] Slovakia Observational Prospective 1 Jan 2003 1 July 2006 92
10 Ebner, 2009 [20] Austria Randomized control Prospective 1 Aug 2003 1 Feb 2006 17
11 Waizmann, 2010 [21] Germany Observational Retrospective 1 Sept 2005 1 May 2008 49
12 Belfiori, 2009 [22] Italy Observational Prospective 1 Sept 2003 1 Dec 2006 52
13 Guadagnino, 2007 [23] Italy Observational Prospective 1 Dec 2002 1 Nov 2003 53
14 Bonkovsky, 2008 [12]
b,c
US Randomized control Prospective 24
14 Bonkovsky, 2008 [12]
b,c
US Randomized control Prospective
15 Schaefer, 2007 [24] Germany Case control Prospective 1 Jan 2001 1 Jan 2003 31
16 Litwin, 2009 [25] US Observational Retrospective 1 Jan 2003 15 Dec 2005 73
17 Mauss, 2004 [26]
b
Germany Nonrandomized
concurrent control trial
Prospective 50
18 Harris, 2010 [27] US Observational Retrospective 1 July 2003 1 July 2005 21
20 Grebely, 2010 [10] Canada Observational Retrospective 1 March 2005 1 March 2008 19
35 Krook, 2007 [28] Norway Nonrandomized
concurrent control trial
Prospective 1 Jan 2003 1 Jan 2004 17
42 Bruggmann, 2008 [29] Switzerland Observational Retrospective 1 Sept 2000 31 May 2006 199
66 Dimitroulopoulos, 2009 [30] Greece Observational Retrospective 1 Nov 2001 1 Jan 2003 45
69 Fried, 2008 [31] Switzerland Observational Prospective 1 March 2002 1 June 2004 67
73 Hallinan, 2007 [32] Australia Observational Prospective 1 Dec 2002 1 Nov 2005 11
75 Jack, 2009 [33] UK Observational Prospective 1 Feb 2005 1 Jan 2008 21
76 Jeffrey, 2007 [34] Australia Observational Prospective 1 Oct 2002 1 March 2005 50
85 Schulte, 2010 [35] Germany Observational Prospective 1 Sept 2002 1 Dec 2007 26
89 Papadopoulos, 2010 [36] Greece Observational Prospective 1 Jan 2004 1 Jan 2010 48
91 Melin, 2010 [37] France Observational Prospective 1 Nov 2002 1 Jan 2005 822
92 John-Baptiste, 2010 [38] Canada Observational Retrospective 1 Nov 2002 1 Jan 2006 109
98 Sasadeusz, 2011 [39] Australia Observational Prospective 1 Feb 2004 1 Jan 2006 53
99 Taylor, 2011 [40]
b
USA Observational Prospective 11
107 Jovanovi
c, 2007 [41] Serbia Observational Retrospective 1 Jan 2005 1 Jan 2007 31
129 Wilkinson, 2009 [42] UK Observational Prospective 1 March 2005 1 March 2007 58
130 Manolakopoulos, 2010 [43] Greece Observational Retrospective 1 Jan 2000 1 Dec 2007 175
133 Lindenburg, 2011 [44] Netherlands Observational Prospective 1 Jan 2005 1 July 2009 58
134 Tait, 2010 [45] Scotland UK Observational Retrospective 1 Jan 2004 1 Jan 2007 42
135 Mauss, 2010 [46] Germany Observational Retrospective 1 Jan 2000 31 Dec 2007 407
136 Martinez, 2012 [47] USA Observational Retrospective 1 July 2006 1 June 2008 24
137 Curcio, 2010 [13]
c
Italy Matched control Prospective 1 Jan 2004 1 Jan 2008 16
137 Curcio, 2010 [13]
c
Italy Matched control Prospective 1 Jan 2004 1 Jan 2008 32
a
Of the studies that offered support services, 3 offered needle exchange, 5 counseling for risk reduction, 10 psychological counseling, 3 educational
intervention, 8 directly observed therapy, and 3 case management, while some offered multiple support services simultaneously.
b
Information on enrollment dates not included in manuscript.
c
Study includes independent arms, which were treated as separate studies.
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active DUs. Eight studies defined former drug use as at least 6
months of abstinence prior to HCV treatment, whereas one
study required at least 4 months, one 12 months, and an addi-
tional one had a me dian of 24 months of abstinence. Addic-
tion treatment during HCV therapy occurred in 61.6% of
patients (1303/2115 from 28 studies). Provision of support
services was described in 31 studies, 15 with services and 16
without (Table 1). Twenty-two studies treated HCV using a
multidisciplinary team.
Treatment Completion Rates in DUs Treated With PEG-IFN/RBV
We calculated the pooled treatment completio n rate as 83.4%
(95% confidence interval [CI], 77.1%–88.9%) from 32 studies
(Figure 1A). We identified heterogeneity in the treatment
completion rates (I
2
= 90.2%, P < .0001). We identified neither
publication bias (P = .30; Figure 1B) nor any particular study
as influential.
The influence of various factors on treatment completion
rates, estimated coefficients, and P values are shown in
Table 2. Twenty-five studies that reported treatment comple-
tion also specified the number of addiction-treated patients
during HCV therapy. From these 25 studies, we identified a
trend in increased treatment completion when the proportion
of patients treated for addiction during HCV therapy in-
creased (P = .105). In 19 studies, all patients were treated for
addiction, and only 5 studies [20, 24, 37, 43, 44] (the control
group from [13] was excluded as an outlier) included both ad-
diction-treated and untreated patients during HCV therapy. In
these studies, 1061 patients were treated for HCV, and 348 of
them received addiction treatment. We found that the higher
the proportion of patients treated for addiction during HCV
therapy, the higher the treatment completion rate (P < .0001).
Further, among these studies, only Manolakopoulos et al [43]
specified the proportion of patients who used illicit drugs
during HCV therapy (16.5%). Thirteen of the studies that
specified the treatment completion rate also specified the num-
ber of active DUs, but this observation was not significantly
associated with treatment completion (P = .93). Additionally,
we identified a trend of increasing treatment completion with
increasing baseline substitution therapy (P = .058).
Factors such as HCV infection with genotype 1/4 (from 12
studies, P = .026) and HIV infection (P = .044) were associated
with lower treatment completion. For genotype 1/4 infection,
the pooled rate was 80.0% (95% CI, 66.0%–91.3%; I
2
= 85.7%).
We observed the opposite association among those with geno-
type 2/3 infection; that is, the higher the genotype 2/3
Figure 1. A, Forest plot demonstrating the treatment completion rates and associated 95% confidence intervals for each of the studies included
in the meta-analysis. Column labeled “Tx compl.” refers to the number of patients who completed treatment, and column labeled “% compl.” refers to
the percentage of patients in each study who completed treatment. Treatment completion ranged between 36.4% and 100%. In 7 studies, all
patients completed treatment including 5 studies that reported extremely high sustained virologic response rates [19–21, 28, 41] and 2 that had small
sample sizes [10 , 32]. B, Funnel plot assessing publication bias for studies reporting treatment completion rates for hepatitis C virus infection.
Treatment completion rates were transformed using the Freeman-Tukey double arcsine transformation [14] by the following formula:
1=2ðarcsinð
ffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi
N
compl
=ðN þ 1
p
ÞÞ þ arcsinð
ffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi
N
compl
þ 1=ðN þ 1
p
ÞÞÞ. Abbreviation: CI, confidence interval.
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proportion, the higher the treatment completion rate
(P = .0007). For genotype 2/3, the pooled completion rate was
90.8% (95% CI, 77.3%–99.1%; I
2
= 88.2%). For HCV monoin-
fection studies, the pooled rate was 87.0% (95% CI, 79.0%–
93.3%; I
2
= 89.9%), whereas the pooled rate of studies that in-
cluded HCV/HIV-coinfected patients was 67.9% (95% CI,
53.0%–81.3%; I
2
= 79.0%). Additionally, the higher the pro-
portion of male DUs, the lower the treatment completion rate
(P = .051). Among 3 US studies with African American pa-
tients (9/56), treatment completion rates were lower (P = .004).
None of the other variables evaluated were significantly associ-
ated with treatment completion.
We also investigated the heterogeneity among the treatment
completion rates through multivariable meta-regression. Sev-
enteen studies simultaneously included data on the treatment
of addiction during HCV therapy, HIV/HCV coinfection, and
sex as well as the availability of support services. Based on these
analyses, we found a significant negative correlation between
treatment completion and HIV/HCV coinfection (P <.0001)
and male sex (P < .0001), as well as a positive correlation with
availability of support services (P < .0001). From this model, the
heterogeneity parameter was estimated as 0 (P =.58).
Treatment Efficacy in DUs
We calculated an SVR rate of 59.4% (95% CI, 54.0%–64.7%)
based on all 36 studies (Figure 2A). We identified significant
heterogeneity (P < .0001) and estimated I
2
as 83.5% (95% CI,
78%–87.6%).
We initially detected potential publication bias in the SVR
rates among the included studies (P = .015). After removal of
Table 2. Results From Univariable Meta-regression on Transformed Treatment Completion Rates
a,b
Variable
No. of
Studies
Coefficient
Estimate 95% CI P Value
c
Pearson
Correlation
Coefficient
Heterogeneity
Parameter (I
2
)
d
P Value
(Heterogeneity)
Treatment of addiction during
HCV therapy
25 0.2773 −.0582, .6128 .1053 0.2651 0.0249 (0.8061) <.0001
Treatment of addiction during
HCV therapy (in studies with
patients who were not treated
for addiction)
5 0.589 .4117, .7663 <.0001* 0.9664 0.0017 .2059
Substitution therapy at baseline
e
22 0.3201 −.0113, .6516 .0584* 0.3503 0.024 (0.8084) <.0001
Drug use during HCV treatment 15 0.2584 −.0226, .5395 .0715 0.4699 0.0172 (0.7444) <.0001
Genotype 1 or 4 27 −0.4243 −.7981, −.0506 .0261* −0.4462 0.0369 (0.8930) <.0001
Human immunodeficiency virus
infection
24 −0.4628 −.9134, −.0122 .0441* −0.4416 0.041 (0.9125) <.0001
Male 22 −0.6648 −1.3326, .0031 .0511* −0.4502 0.0448 (0.9167) <.0001
African American from US studies 3 −1.8556 −3.1240, −.5872 .0041* −0.9681 0 .3347
Caucasians from US studies 5 0.0905 −.7991, .9802 .8419 0.1415 0.0174 (0.6058) .0174
Study design (randomized or
matched control vs other)
32 −0.0686 −.2843, .1470 .5327 −0.0979 0.0404 (0.9022) <.0001
Location in United States 32 −0.1272 −.3446, .0902 .2515 −0.2438 0.0403 (0.9023) <.0001
Age 23 −0.0116 −.0266, .0034 .1304 −0.3188 0.0414 (0.8691) <.0001
Psychiatric comorbidities 15 −0.2312 −.6217, .1593 .2459 −0.3378 0.05 (0.9251) <.0001
Biopsy performed 15 0.0208 −.3646, .4062 .9157 0.0218 0.0665 (0.9365) <.0001
Multidisciplinary team involved 32 0.0313 −.1250, .1875 .6951 0.0501 0.0403 (0.8885) <.0001
Support services offered 31 0.101 −.0463, .2482 .1789 0.1859 0.0353 (0.8799) <.0001
Methadone maintenance during
HCV treatment
20 −0.1042 −.3794, .1709 .4578 −0.2296 0.027 (0.8064) <.0001
Abbreviations: CI, confidence interval; HCV, hepatitis C virus.
a
Results listed in order as presented in the text.
b
Results from the univariable meta-regression expressed as
u
i
¼
b
0
þ b
i
þ
b
1
x
i
þ 1
i
, where θ
i
is the Freeman-Tukey double arcsine transformed treatment
completion rate from study i, β
0
is intercept, b
i
is random effect for study i, x
i
is the value of the covariate from study i, and ɛ
i
is the within study error. The
covariates are expressed either as proportions (treatment of addiction during HCV therapy, substitution therapy at baseline, drug use during HCV treatment,
genotype 1 or 4, human immunodeficiency virus infection, male, Afric an American from US studies, Caucasians from US studies, psychiatric comorbidities,
biopsy performed, methadone maintenance during HCV treatment), as categorical variables (study design, location in United States, multidisciplinary team
involved, support services offered) or as continuous variables (median/mean age).
c
Significant P values are indicated with an asterisk.
d
I
2
added if heterogeneity is present.
e
Substitution therapy included patients on either methadone or buprenorphine.
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4 outlying studies [19, 21, 28, 41], publication bias resolved
(P = .175; Figure 2B), I
2
decreased to 78.6% (heterogeneity re-
mained significant, P < .0001), and the pooled SVR rate
became 55.5% (95% CI, 50.6%– 60.3%). The outlying studies had
SVR rates ≥94% [19, 21, 41] and included relatively younger
patients (median/mean ages of 27.0, 30.1, and 32.9 years, respec-
tively). These studies were excluded in all subsequent analyses.
Differences in the proportions of patients treated for addic-
tion during HCV therapy did not explain the heterogeneity
between the SVR rates (P = .930; Table 3). The pooled SVR
rate among addiction-treated patients was 53% (95% CI,
49.4%–56.6%) from 20 homogeneous (I
2
= 25%, P =.15)
studies that reported the respective rates. Moreover, among
the studies which included addiction-treated and untreated
patients, only Manolakopoulos et al [43] specified the propor-
tion of patients using illicit drugs during HCV therapy
(16.5%). Thirteen of the studies specified how many patients
were active drug users, but this observation was not associated
with SVR (P = .76).
The median proportion of patients infected with HCV ge-
notype 1/4 was 44.7% (IQR, 37.1%–57.5%), which signifi-
cantly affected the SVR rate (P = .001). Moreover, when the
effects of the proportions of genotypes 1 and 4 patients were
assessed separately, the SVR rate was negatively correlated
with the proportion of genotype 1 patients ( P = .0065), but
not significantly correlated with genotype 4 patients (P = .56).
Similarly, higher proportions of HIV-infected patients were
associated with lower SVR rates (P = .017). For HCV genotype
1/4, the SVR rate was 44.9% (95% CI, 41.0%–48.9%) from 19
homogeneous studies (I
2
= 0%, P = .637). For HCV genotype
2/3, the SVR rate was 70.0% (95% CI, 62.9%–76.3%) from 18
heterogeneous studies (I
2
= 57%, P = .002). Among 7 hom oge-
neous (I
2
= 44.4%, P = .095) studies with HIV-coinfected pa-
tients, the SVR rate was 41.3% (95% CI, 38.2%–44.4%).
Among 15 homogeneous (I
2
= 24.5%, P = .183) studies
without HIV-coinfected patients, the SVR rate was 58.1%
(95% CI, 54.6%–61.5%). Neither the median baseline HCV
RNA level (available in 4 studies) nor the proportion of pa-
tients with advanced fibrosis (Scheuer stage ≥3; from 9
studies), were significantly associated with SVR. Additionally,
in comparison with the SVR rate obtained from other coun-
tries, a significantly lower SVR rate of 44.6% (95% CI, 37.3%–
52.2%, P = .035) was obtained among the 6 homogeneous
(I
2
= 28.1%, P = .224) studies from the United States
(Figure 3). The lower SVR rate may result from inclusion of
significantly more HCV genotype 1/4–infected subjects in US
studies (P = .003). None of the other variables assessed were
significantly associated with treatment efficacy (Table 3).
Figure 2. A, Forest plot demonstrating the sustained virologic response (SVR) rate and associated 95% confidence interval for each of the studies
included in the meta-analysis. Column labeled “SVR pts.” refers to the number of patients who achieved an SVR in the individual study. SVR was
defined as absence of detectable peripheral hepatitis C virus RNA 24 weeks after treatment cessation. B, Funnel plot assessing publication bias for rate
of sustained virologic response. Abbreviations: CI, confidence interval; SVR, sustained virologic response.
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In addition, we investigated the heterogeneity among the
SVR rates through multivariable meta-regression. Nineteen
studies simultaneously included data on the proportion of
HCV genotype 1/4 patients, HIV infection, and treatment of
HCV through a multidisciplinary team. On the basis of this
analysis, we found a significant negative correlation between
SVR and genotype 1/4 (P = .0003) and positive correlation
with involvement of a multidisciplinary team (P < .0001). We
also found a nonsignificant negative correlation with HIV/
HCV coinfection (P = .19) and a heterogeneity parameter esti-
mated as 0.0009 (P = .28).
Finally, we sought to assess whether treatment of addiction
affects the early virologic respo nse (EVR) rate. EVR was
defined as either undetectable HCV RNA or a 2 log
10
decrease
in HCV RNA by week 12. EVR rates were reported in 8
studies (Figure 4), which were heterogeneous (I
2
= 82.7%,
P < .0001). The pooled EVR rate across all studies was 84.4%
(95% CI, 73.3%–93.2%). Seven of these 8 studies reported that
all of their patients were treated for addiction during HCV
therapy (1 study did not specify), which did not enable us to
evaluate the effect of treatment of addiction on EVR. The
higher the proportion of genotype 1/4 patients, the lower the
EVR rate (P < .0001).
DISCUSSION
Despite high HCV prevalence and incident infections, DUs
may have difficulty adhering to the therapeutic regimen for
HCV. Understanding whether various support services for
HCV can assist DUs to complete HCV therapy and improve
treatment outcome could have important clinical and public
health implications. In this study, we observed that addiction-
treated DUs have higher PEG-IFN/RBV completion rates than
Table 3. Results From Univariable Meta-regression on Log Odds of Sustained Virologic Response
a,b
Variable
No. of
Studies
Coefficient
Estimate 95% CI P Value
c
Pearson
Correlation
Coefficient
Heterogeneity
Parameter (I
2
)
d
P
Value
Treatment of addiction during
HCV therapy
26 −0.0426 −.9784, .8932 .9289 −0.0468 0.2014 (0.7020) <.0001
Genotype 1 or 4 26 −1.7062 −2.7413, −.6712 .0012* −0.7058 0.1349 (0.7031) <.0001
Human immunodeficiency virus 22 −1.5767 −2.8753, −.2781 .0173* −0.5921 0.1418 (0.6794) <.0001
Location in United States 32 −0.5847 −1.1294, −.0401 .0354* −0.4929 0.2077 (0.7777) <.0001
Support services offered 31 −0.0245 −.4556, .4067 .9114 −0.0967 0.2343 (0.7909) <.0001
Multidisciplinary team involved 32 0.0626 −.3506, .4759 .7665 0.0830 0.2265 (0.7800) <.0001
Methadone maintenance during
HCV treatment
20 −0.4157 −1.1916, .3602 .2937 −0.4871 0.163 (0.6029) .0002
Study design (randomized or
matched control vs other)
32 −0.1484 −.7701, .4733 .6399 0.0747 0.2133 (0.7847) <.0001
Age 20 −0.0088 −.0486, .0311 .6656 −0.3288 0.1191 (0.5187) .0025
Male 22 0.1513 −1.3726, 1.6752 .8457 0.0123 0.2541 (0.7993) <.0001
Caucasians from US studies 6 0.0424 −1.1812, 1.2659 .9459 0.0987 0.1405 .1386
African American from US studies 4 −4.8407 −11.1615, 1.4801 .1333 −0.8544 0.039 .2711
Psychiatric comorbidities 14 −0.151 −1.1111, .8092 .758 −0.3007 0.1704 (0.7117) <.0001
Substitution therapy at baseline
e
24 −0.246 −1.2266, .7345 .6229 −0.1652 0.2163 (0.7224) <.0001
Drug use during HCV treatment 15 0.346 −.1833, .8754 .2001 0.3777 0.0462 .0887
Biopsy performed 14 −0.2575 −.9557, .4407 .4697 −0.1952 0.071 (0.4498) .0228
Abbreviations: CI, confidence interval; HCV, hepatitis C virus.
a
Results listed in order as presented in the text.
b
Results from the univariable meta-regression expressed as
u
i
¼
b
0
þ b
i
þ
b
1
x
i
þ 1
i
, where θ
i
is the log odds for achieving a sustained virologic response from
study i, β
0
is intercept, b
i
is random effect for study i, x
i
is the value of the covariate from study i, and ɛ
i
is the within study error. The covariates are expressed
either as proportions (treatment of addiction during HCV therapy, substitution therapy at baseline, drug use during HCV treatment, genotype 1 or 4, human
immunodeficiency virus infection, male, African American from US studies, Caucasians from US studies, psychiatric comorbidities, biopsy performed,
methadone maintenance during HCV treatment), as categorical variables (study design, location in United States, multidisciplinary team involved, support
services offered) or as continuous variables (median/mean age).
c
Significant P values are indicated with an asterisk.
d
I
2
added if heterogeneity is present.
e
Substitution therapy included patients on either methadone or buprenorphine.
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nonaddiction-treated DUs. In addition, we observed lower
rates of treatment completion among DUs infected with geno-
type 1/4 as well as among HIV-infected individuals as com-
pared to genotype 2/3 and HCV-monoinfected DUs,
respectively. After adjusting for HIV/HCV coinfection, sex,
and treatment of addiction during HCV therapy, we observed
that the availability of support services during HCV treatment
significantly increased the treatment completion rates among
DUs. We also observed that our SVR rate of 55.5% among all
PEG-IFN/RBV-treated DUs and of 53% for those treated for
Figure 3. Box plot illustrating sustained virologic response (SVR) rates by country of origin and includes all studies analyzed as part of meta-analysis
as well as 4 outliers from Slovakia, Germany, Norway, and Serbia. The numbers in parentheses are the number of studies from each location. The SVR
rate reported in US studies is signi ficantly lower in comparison with other countries (P = .035). The box extends from the 25th to the 75th percentile.
The line in the middle of the box is the median and the lines extending from either end of the box indicate the extent of the data beyond the 25th and
75th percentiles, and outliers, if any. Abbreviation: SVR, sustained virologic response.
Figure 4. Forest plot demonstrating the early virologic response (EVR) rate and associated 95% confidence interval for each of the included studies
that specified EVR rate. EVR was defined as undetectable hepatitis C virus (HCV) RNA or a 2 log
10
decrease in HCV RNA by week 12. Column labeled
“EVR pts.” refers to the number of patients who achieved an EVR in the individual study. Abbreviations: CI, confidence interval; EVR, early virologic
response.
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addiction during HCV treatment are comparable to those ob-
tained in PEG-IFN/RBV registration trials (54% and 56%, re-
spectively [3, 4]). After adjusting for HCV genotype 1/4 and
HIV/HCV coinfection, we observed that involvement of mul-
tidisciplinary team led to higher SVR rates among DUs.
The treatment completion rate among all DUs was estimat-
ed to be 83.4% (from 32 studies), which is comparable to the
14%–22% of patients who discontinued PEG-IFN/RBV treat-
ment in registration trials [3, 4]. Decreased treatment comple-
tion among patients with genotype 1/4 could be explained by
the longer course of PEG-IFN/RBV treatment for these geno-
types. Similarly, HIV infection may affect PEG-IFN/RBV
completion by adding to the complexity of the treatment
regimen.
We observed a trend between treatment completion and the
proportion of male DUs: the higher the proportion of males,
the lower the treatment completion. We previously reported
that male DUs were more likely to pursue HCV evaluation
after at least 3 years of substitution therapy [47]. These, com-
bined with similar results [48, 49], suggest that sex-based in-
terventions may increase pursuit of and adherence to HCV
care. In addition, regional variations in HCV disease charac-
teristics may influence intervention design and execution. For
example, US studies showed that an increased prevalence of
genotype 1 infection potentially contributed to a significantly
lower SVR rate than that observed in other countries.
Morbidity due to HCV continues to increase. The number
of individuals with cirrhosis in the United States is expected
to reach 1 million by 2020, and the number of HCV-
attributable deaths is predicted to increase 5-fold between
2030 and 2050 [50, 51]. We recently reported that 84%
(n = 54) of methadone-maintained patients had at least mod-
erate hepatic fibrosis (Scheuer stage ≥2) [47]. Although we
demonstrated the importance of addiction treatment during
HCV therapy and the availability of support services in
general, we were unable to demonstrate the effectiveness of
any specific intervention. Studies included in our meta-analy-
sis were largely designed as efficacy studies, which varied
widely in the description of services offered and complicated
cross-study comparisons. Furthermore, these studies may have
excluded patients not on addiction treatment or who were
current DUs. To that end, we found a significant result of the
role of addiction treatment on treatment completion among 5
European studies with addiction-treated and untreated pa-
tients. However, patients not treated for addiction during
HCV therapy were mostly former drug users.
While publication bias was not a factor in the treatment
completion rate, it was detected in the assessment of SVR
likely due to few studies with large samples, studies with high
SVR rates (>88%), and no studies with SVR rates in the inter-
val of 70%–88%. Elimination of 4 outlier studies mitigated the
publication bias. Although we demonstrated that treatment of
addiction is associated with higher HCV treatment completion
rates, our study was likely underpowered to demonstrate that
treatment of addiction increases the SVR rate. Additional limi-
tations include the paucity of papers on DUs not in drug
treatment and the small number of African Americans in
these studies.
In conclusion, published data suggest that the overall rates
for treatment completion and SVR for PEG-IFN/RBV–treated
DUs are comparable to registration trials. Further work should
evaluate care models in DUs. On the basis of our results, we
recommend that DUs treated for addiction should be consid-
ered for HCV treatment under the same circumstances as the
non-DUs.
Supplementary Data
Supplementary materials are available at Clinical Infectious Diseases online
(http://cid.oxfordjournals.org/). Supplementary materials consist of data
provided by the author that are published to benefit the reader. The
posted materials are not copyedited. The contents of all supplementary
data are the sole responsibility of the authors. Questions or messages re-
garding errors should be addressed to the author.
Notes
Acknowledgments. We acknowledge the assistance of Ray Peterson
and Julio Quintero for helpful discussions.
Financial support. This work was supported as an investigator-
initiated project by Merck, Inc, and by the National Institutes of Health
(DA 003574 to D. C. D.). The authors wrote the protocol, conducted the
study, performed the statistical analysis, and wrote the manuscript. Al-
though Merck reviewed the final manuscript prior to submission, the
authors take full responsibility for the data and the conclusions reported.
Potential conflicts of interest. R. B. D., M. Z., D. C. D., and
H. H. received research support by Merck for the conduct of this
study. A. H. T. has been a consultant/advisor for Merck, Genentech,
Vertex, Boerhinger-Ingelheim, Pfizer, and Bayer/Onyx; has received re-
search support from Merck, Genentech, Vertex, Boehringer-Ingelheim,
Gilead, Tibotec, Abbott, and BMS; and is a member of the speakers’
bureaus for Vertex and Genentech. I. M. J. has received grant/research
support from Schering/Merck, Tibotec/Janssen, Roche/Genentech, Phar-
masset, Achillion, Anadys, Boehringer Ingelheim, Novartis, Gilead, Vertex,
GlobeImmune, Pfizer, Bristol-Myers Squibb, and Zymogenetics; has been
a consultant/advisor for Abbott, Achillion, Boehringer Ingelheim, Bristol-
Myers Squibb, Gilead, GlaxoSmithKline, GlobeImmune, Inhibitex,
Kadmon, Novartis, Pharmasset, Presidio, Roche/Genentech, Schering/
Merck, Tibotec/Janssen, and Vertex; and is on the speakers’ bureaus for
Schering/Merck, Gilead, Bristol-Myers Squibb, Roche/Genentech, and
Vertex.
All authors have submitted the ICMJE Form for Disclosure of Potential
Conflicts of Interest. Conflicts that the editors consider relevant to the
content of the manuscript have been disclosed.
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