World Journal of AIDS, 2013, 3, 36-40
http://dx.doi.org/10.4236/wja.2013.31006 Published Online March 2013 (http://www.scirp.org/journal/wja)
Progression of Platelet Counts in Treatment Naïve
HIV/HCV Co-Infection*
Jonathan E. Schelfhout1, Danijela A. Stojanovic1, Amy Houtchens1,2, Heidi M. Crane3,
Edward R. Cachay4, Elizabeth R. Brown5, Sonia M. Napravnik6, Mari M. Kitahata3, Michael S. Saag7,
Peter W. Hunt8, Teresa L. Kauf1, Joseph A. C. Delaney9
1Department of Pharmaceutical Outcomes & Policy, College of Pharmacy, University of Florida, Gainesville, USA; 2Food and Drug
Administration, Silver Spring, USA; 3Division of Allergy & Infectious Disease, Department of Medicine, University of Washington,
Seattle, USA; 4Department of Medicine, University of California at San Diego, San Diego, USA; 5Vaccine and Infectious Disease
and Public Health Sciences Divisions, Fred Hutchinson Cancer Research Center, Seattle, USA; 6Department of Medicine, University
of North Carolina, Chapel Hill, USA; 7Department of Medicine, University of Alabama at Birmingham, Birmingham, USA;
8Department of Medicine, University of California at San Francisco, San Francisco, USA; 9Department of Epidemiology, University
of Washington, Seattle, USA.
Received November 20th, 2012; revised January 14th, 2013; accepted January 24th, 2013
ABSTRACT
Background: Previous research has suggested an association between infection with hepatitis C virus (HCV) or with
human immunodeficiency virus (HIV) and low platelet counts. This study estimates platelet count changes over time in
HIV/HCV co-infected participants and compares them with the changes in platelet count among HIV mono-infected
participants to test if HIV/HCV co-infection is associated with lower platelet counts. Methods: This retrospective co-
hort study included all HIV treatment naive patients from four sites in the Centers for AIDS Research Network of Inte-
grated Clinical Systems (CNICS) cohort with platelet count measurements between 2002 and 2009. We conducted a
mixed effects linear regression modeling the mean change in platelet count per year while adjusting for age, sex, race,
baseline CD4 cell count, and site. Index date was the first platelet count after 2002, and participants were censored upon
initiation of treatment for HIV or HCV. Results: There were 929 HIV/HCV co-infected and 3558 HIV mono-infected
participants with a mean follow-up time of 1.2 years. HIV/HCV co-infected participants had on average a slighter lower
platelet count at baseline (234,040 vs. 242,780/μL; p-value = 0.004), and a more rapid mean reduction per year (7230 vs.
3580/μL; p-value < 0.001) after adjusting for age, sex, baseline CD4 count. Conclusions: In treatment naïve partici-
pants, HIV/HCV co-infection is associated with a more rapid decline in platelet count compared with HIV mono-infec-
tion.
Keywords: HCV; HIV; AIDS; Co-Infection; Platelet Count; Thrombocytopenia
1. Introduction
Co-Infection with the Hepatitis C virus (HCV) presents
many challenges to the effective management of the hu-
man immunodeficiency virus (HIV). Co-Infection rates
are high, with an estimated 35% of HIV-infected patients
also infected with HCV [1]. Without treatment these pa-
tients progress to cirrhosis three times faster than HCV
mono-infected patients leading to other negative out-
comes of HCV infection including end-stage liver di-
sease, hepatic carcinoma, and death [2-4]. Liver disease
is one of the leading non-AIDS related causes of death in
HIV-infected patients [5].
Thrombocytopenia is characterized by a low blood
platelet count and can be a barrier to successful treatment
of HCV [6]. Patients who begin treatment for HCV with
low platelet counts are at an increased risk of severe
thrombocytopenia during the course of therapy [7]. Se-
vere cases of thrombocytopenia can lead to intestinal
bleeding, intracranial bleeding, and/or death [8]. Throm-
bocytopenia has been linked to HCV [9-11] and HIV [12,
13] infections, as well as treatment for HCV [14,15].
The purpose of this study was to better understand the
clinical factors and patient characteristics related to the
rate of platelet count changes over time among patients
with HIV infection. Specifically, we modeled change in
platelet count over time among treatment naïve HIV/
HCV co-infected and HIV mono-infected participants.
*Conflict of Interest: Non.

Progression of Platelet Counts in Treatment Naïve HIV/HCV Co-Infection 37
2. Methods
2.1. Data Source
This retrospective study was comprised of participants
enrolled in the Centers for AIDS Research Network of
Integrated Clinical Systems (CNICS) cohort. The CNICS
study contains a large and diverse population of HIV-
infected patients initiating care at eight clinical sites from
January 1995 until the present. Participants from four of
these sites were included in the analysis (University of
California San Diego, University of California San Fran-
cisco, University of North Carolina, and University of
Alabama, Birmingham). The characteristics of the entire
CNICS cohort have been described in further detail
elsewhere [16].
2.2. Study Subjects
HIV-infected individuals 18 years of age or older who re-
ceived care in CNICS at any time from 2002 to 2009 were
eligible for inclusion. This time frame represents the release
of the first guidelines for the treatment of HCV in
HIV/HCV co-infected patients and their adoption by the
CNICS network [17]. Index date was defined as the date of
the first platelet count recorded during the study window.
Participants were excluded from the analysis if they
had a history of antiretroviral (ARV) or interferon (INF)
based therapy prior to their index date, if the start date of
these treatments could not be determined, or if they had
incomplete information on age, sex, or race. Censoring
occurred at the start of ARV or INF therapy, end of fol-
low-up, upon leaving the CNICS cohort, or death. This
study is approved by the Institutional Review Board
(IRB) at each CNICS site.
2.3. Measures
Participants were considered HCV-infected if they had a
positive enzyme-linked immunosorbent assay (ELISA)
HCV surface antibody test, or a clinical diagnosis of
HCV. Laboratory test results, including platelet counts,
liver function tests, and HCV genotype (when available)
were measured as part of routine clinical care. Interferon
based therapy for HCV was defined as receiving either
pegylated interferon (peg-INF) α-2A or α-2B, or first
generation interferon based therapies. ARV therapy was
determined based on receiving a regimen included in US
guidelines for the use of antiretroviral agents in HIV-
infected adults and adolescents [18].
Participants were classified with low platelet counts at
levels of <150 × 109/L (low), <100 × 109/L (very low),
and <50 × 109/L (severe). Although definitions of thro-
mbocytopenia vary, these levels are believed to represent
commonly used and clinically significant thresholds for
dose adjustments and/or treatment discontinuation during
HCV therapy [19-21].
2.4. Statistical Analysis
Descriptive statistics were presented using mean and
standard deviations (SD) for continuous variables or fre-
quencies and percentages for dichotomous variables. A
mixed-effects linear regression model with random in-
tercepts was used to estimate the average change in
platelet count by year. This model used a random inter-
cept for each participant to measure the mean change of
all participants’ platelet counts while controlling for re-
peated measures.
The primary analysis explored whether the yearly
change in platelet counts for HIV/HCV co-infected par-
ticipants differed from that of HIV mono-infected par-
ticipants by including a time from index by HIV/HCV
co-infection interaction variable in the model. The model
was adjusted for age, sex, race, baseline CD4 cell count
(at index date), and CNICS site. All analyses were con-
ducted in SAS version 9.2 and all tests are two-sided at
the 5% level of significance.
3. Results
There were 4487 participants who met the inclusion cri-
teria for the study. Of these, 3558 were HIV mono-in-
fected and 929 were co-infected with HCV. Table 1
contains information on baseline characteristics of the
population. HCV co-infected participants had a longer
mean follow-up (1.7 years vs. 1.1 years; p-value < 0.001)
and more platelet count results on average when com-
pared to HIV mono-infected participants (14 vs. 8; p-
value < 0.001). Similar numbers of HCV co-infected and
HIV mono-infected participants were censored (72% vs.
73%; p-value = 0.7) with HCV co-infected participants
being censored less frequently due to ARV therapy (65%
vs. 71%; p-value < 0.001) and more frequently because
of mortality (6% vs. 2%; p-value < 0.001). Only 1.4% of
HCV co-infected participants were censored due to ini-
tiation of peg-INF therapy and no participant began first
generation INF therapy during the study window.
Results of the adjusted model are provided in Table 2.
Participants with HCV had 9.1 (95% confidence interval
(CI): 2.9, 15.2; p-value = 0.004) × 109/L fewer platelets
at baseline than HIV mono-infected participants. HIV
mono-infected participants had an average reduction of
3.1 (95% CI: 2.1, 4.1; p-value < 0.001) × 109/L platelets
per year, with HCV co-infected participants losing an
additional 3.6 (95% CI: 2.1, 5.2; p-value < 0.001) ×
109/L platelets per year relative to HIV mono-infected
participants. Figure 1 depicts the cumulative effects of
adjusted yearly changes in platelet counts.
4. Discussion
The present study found that HIV-infected individuals
without HCV who were ARV naïve, on average, had a

Progression of Platelet Counts in Treatment Naïve HIV/HCV Co-Infection
38
3.1 × 109/L decline in platelet count per year. HIV/HCV
co-infected participants had more than a two times
Table 1. Baseline characteristics of HCV-infected and HCV-
uninfected participants.
Characteric HCV (n = 929) Non-HCV (n = 3558)
Age, mean (sd) 42.4 (9.0) 36.9 (9.7)
Sex, n (%)
Male 694 (75) 2982 (84)
Female 235 (25) 576 (16)
Race, n (%)
African–American/Black 412 (44) 1261 (35)
White 330 (36) 1560 (37)
Hispanic or Latino 100 (11) 599 (17)
Other/unknown 87 (9) 496 (14)
Platelets at baseline
(× 109/L), mean (sd) 234.0 (98.8) 242.8 (88.6)
CD4, mean (sd) 414.0 (315.7) 366.2 (285.5)
Diabetes, n (%) 64 (7) 143 (4)
Hypertension, n (%) 206 (22) 632 (18)
Previous Liver Diagnosis, n (%) 103 (11) 199 (6)
Injection Drug User, n (%) 477 (51) 223 (6)
Bilirubin (mg/dL), mean (sd) 64.78 (60.3) 65.27 (44.4)
ALTa (Iu/L), mean (sd) 39.7 (21.8) 30.9 (17.6)
ASTb (Iu/L), mean (sd) 42.9 (20.0) 32.0 (15.0)
Albumin (g/dL), mean (sd) 3.6 (0.7) 3.9 (0.7)
HCV genotype, n (%)
1 188 (85) -
2 13 (6) -
3 20 (9) -
Platelets, n (%)
<150,000 150 (16) 387 (11)
<75,000 27 (3) 59 (2)
<40,000 6 (1) 21 (1)
aAlanine aminotransferase
bAspartate aminotransferase
Table 2. Adjusted difference in platelet counts by key vari-
ables among HIV-infected and HCV co-infected participants.
Group
Difference in
platelet count
(109/L)
95%
Confidence
interval
P-value
One year increase in age −0.49 (−0.74, −0.24) <0.001
HCV co-infection at baseline −9.05 (−15.24, −2.88) 0.004
Per year follow-up with
HIV-infection −3.09 (−4.10, −2.08) <0.001
Per year follow-up with
HIV/HCV co-infection above
that of HIV-infection alone
−3.63 (−5.17, −2.09) <0.001
Figure 1. Conceptual model of platelet count changes over
time based on results of adjusted model. This figure dem-
onstrates that as 1 year passes, a patient has an estimated
reduction of (all platelet counts × 109/L) 0.49 due to age,
3.58 due to age and HIV infection combined, and −7.21 due
to age, HIV and HCV co-infection.
greater a reduction in platelets per year (additional 3.6 ×
109/L) and were more likely to have low platelet counts
at baseline when compared to HIV mono-infected par-
ticipants.
Previous research has shown that low platelet counts
are strongly correlated with liver fibrosis [22,23], pro-
gression of liver damage [24], and have been proposed as
a component of a non-invasive method to predict liver
damage in patients with HCV [25]. Liver disease, and its
progression, is prominent in HCV infection [26], and it
appears it is accelerated in the presence of HIV co- infec-
tion [27]. Low platelet counts in HIV mono-infected pa-
tients are thought to be due to increased immune-me-
diated platelet destruction and to reduced platelet pro-
duction by the infected megakaryocytes of the bone
marrow [28].
Treatment of a low platelet count is not typically rec-
ommended until severely low levels, usually less than 50
× 109/L [29]. The average HIV/HCV participant began
their observation period with a platelet level four to five
times this amount. It seems implausible that most
HIV/HCV co-infected participants will be treatment na-
ïve long enough to reach severely low levels of platelets.
The etiology of platelet decreases in HIV/HCV individu-
als cannot be determined in an observational study, but
progression of liver disease is a possible cause. De-
creases in platelet counts among HIV-infected individu-
als may raise more concerns about the ongoing progres-
sion of liver disease leading to morbidity and mortality
than for the risk of bleeding events. Liver disease has
become the leading cause of death in HIV-infected pa-
tients [5], while bleeding events are rare even at low
platelet counts [13].
Low platelet counts may not only be reflective of liver

Progression of Platelet Counts in Treatment Naïve HIV/HCV Co-Infection 39
disease progression, but may also be reflective of a more
limited ability for physicians to halt its progression
through treatment. Thrombocytopenia is one of the most
frequent contraindications to peg-INF therapy and a ma-
jor cause of dose reduction [30]. Previous studies have
shown that low platelet counts are correlated with a re-
duced likelihood of achieving a sustained virologic re-
sponse to HCV due to their relationship with adverse
events and lower rates of treatment completion [11].
The ability to examine platelet counts in a large and
diverse sample of HIV-infected patients in care with
comprehensive data is a strength of this study. Previous
research has lacked the ability to analyze longitudinal
changes in platelet count at a patient level [31], or lacked
generalizability due to strict inclusion and exclusion cri-
teria [32]. Because the focus of CNICS is to follow HIV
patients through routine clinical care, this analysis was
able to study changes in platelet count levels for treat-
ment naïve participants. This is typically not possible
with other data commonly used to study HIV or HCV
infection, like clinical trials or claims databases, due to
an emphasis on treatment.
Despite these strengths, the study has limitations. The
mixed effects regression model accounts for irregularities
in the length of follow-up, conditional upon a “missing at
random” assumption. However, it is possible the likeli-
hood of censoring is not completely independent from a
participant’s platelet count. Antiretroviral therapy for
HIV has been shown to increase platelet counts [33], and
it is possible that this could make censoring more likely
as platelet counts fall. HIV/HCV co-infected participants
with low or decreasing platelet counts may be less likely
to be censored due to initiation of peg-INF therapy.
It is important to note that the effects shown in this
study are average associations and may not be gener-
alizable to patients at all levels of platelet counts. It is
possible that small groups of participants, like those with
very high or very low platelet counts, could see associa-
tions that differ from the average association found in
this study. The analysis fit the model with splines to de-
termine possible non-linearity. The model fit did not im-
prove significantly (as determined by Baysian informa-
tion criterion) and none of the estimates of the yearly
effects or covariates changed more than 1% from their
original values.
To our knowledge, this is the first observational study
to analyze platelet count trajectories in treatment naïve
HIV mono-infected and HCV/HIV co-infected partici-
pants. This study provides important information on how
HIV/HCV co-infection can result in additional morbidity
in a high risk population.
5. Acknowledgements
This work was supported by grants from AHRQ
(R21HS019516), the American Heart Association Grant-
in-Aid grant (09050129G), the CNICS grant (R24
AI067039), University of North Carolina Center for
AIDS Research grant (P30-AI50410), and the University
of Washington Center for AIDS Research NIAID grant
(P30-AI027757). The funding agreements ensured the
authors’ independence in design and conduct of the study;
collection, management, analysis and interpretation of
the data; and preparation, review and approval of the
manuscript.
Publication of this article was funded in part by the
University of Florida Open Access Publishing Fund, and
by the American Foundations for Pharmaceutical Educa-
tion (AFPE) Predoctoral Fellowship in the Pharmaceuti-
cal Sciences.
6. FDA/CDER Disclaimer
Amy Houtchens is employed by the Food and Drug Ad-
ministration (FDA). This article reflects the views of the
authors and should not be construed to represent the
FDA’s views or policies.
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