Following the introduction of effective combination antiviral therapy (ART), hepatitis C virus (HCV) coinfection has emerged as one of the most important comorbidities affecting HIV-positive individuals [1–4]. Approximately 30% of HIV-infected patients in developed countries are coinfected with HCV due to shared routes of transmission [5,6]. The negative impact of HIV on the natural history of HCV has been well established: compared with those infected with HCV alone, coinfected persons experience more rapid progression to end stage liver disease and death [7–9]. Conversely, whether HCV has a negative impact on HIV-disease progression remains debated. In the pre-ART era, HCV coinfection was associated with an increased risk of clinical progression (AIDS, wasting and nonaccidental or overdose death) in some studies [10–12] but not others , with no effects seen on immunologic progression [10–12]. In the post-ART era, several cohort studies reported more rapid progression to AIDS among coinfected persons [13–16], which was only partially explained by injection drug use or reduced exposure to ART. Others have not seen the same association [17–20]. There is fairly consistent evidence, however, that CD4+ T-lymphocyte recovery is blunted following ART initiation in coinfected persons [7,12–15]. But again, several studies have not observed this finding [17,18,20] or have found that delayed CD4 cell recovery among coinfected persons is not sustained .
Active HCV infection could impact the course of HIV infection through a number of pathways. Chronic immune activation and cytokine production in coinfected individuals [22,23] may result in increased HIV replication and diminished CD4 cell counts . Coinfection with HCV has been associated with increased CD4-cell apoptosis in untreated patients, although this appears to be rapidly reversible after ART initiation . Even direct HCV infection of monocytes/macrophages and CD4+ lymphocytes has been proposed as a potential mechanism .
Important limitations exist in previous studies investigating the effects of HCV on the natural history of HIV. First, HCV infection has traditionally been defined by HCV antibody serostatus. However, an important subset of individuals, estimated to be up to 25% in the setting of HCV–HIV coinfection, are exposed to HCV, yet spontaneously clear the virus [27–29]. As these individuals are no longer chronically infected, their inclusion dilutes any potential association of active HCV infection with HIV disease progression. Second, the use of control groups that are HIV monoinfected may introduce bias as the lifestyle and risk behaviours associated with HCV acquisition differ between coinfected and HIV monoinfected persons, and may themselves affect disease progression or adherence to antiretrovirals leading to poorer CD4 cell recovery upon ART initiation.
We took advantage of a prospective cohort of HIV–HCV coinfected patients that includes individuals who both have and have not cleared HCV spontaneously. We compare the rates of CD4 cell loss before, and CD4 gain after, the initiation of ART in order to evaluate the impact of active HCV infection on HIV progression while accounting for behavioural risk factors.
The Canadian Coinfection Cohort Study (CCC) is a prospective open cohort of HIV–HCV coinfected patients recruiting from 16 centres across Canada . These centres routinely screen all HIV-infected patients for HCV infection. Eligible patients are adults aged over 16 years with documented HIV infection (ELISA with western blot confirmation) and with chronic HCV infection or evidence of HCV exposure (e.g. HCV-seropositive by ELISA with RIBA II or EIA confirmation, or if serologically false negative, HCV RNA+). The study was approved by the research ethics boards of the participating institutions.
CCC participants were selected for this study if they had at least two cohort visits between September 2003 and January 2009 and at least two measures of CD4+ T-lymphocytes while either ART naïve or after ART initiation. Participants were followed until July 2009 or censored on the date of the last cohort visit when they began ART (for the naïve analysis), began HCV treatment, died, or, if they were lost to follow-up. Patients were considered lost to follow-up if they missed two or more visits (e.g. 1 year) without having a subsequent visit by the end of the study period.
After informed consent, participants underwent an initial evaluation followed by study visits approximately every 6 months. Sociodemographic, risk behaviours and medical information were collected using questionnaires. Supplementary information was abstracted from medical records and laboratory reports. Blood tests were performed at each visit and included: plasma HIV RNA, lymphocyte subsets (i.e. absolute and relative CD4+ and CD8+ T-lymphocytes), and qualitative plasma HCV RNA (limit of detection: 60 IU/ml; Roche Cobas Amplicor assay).
Because of limited numbers of naïve patients, we took advantage of a clinical database of approximately 3000 patients that have been followed since 1989 at the Montreal Chest Institute Immunodeficiency Service (IDS), a university-based clinic, which is one of the largest centres recruiting to the CCC. Demographic, laboratory and prescription data and clinical diagnoses are prospectively collected. Treatment naïve, HIV-HCV coinfected individuals who were followed at the IDS prior to the CCC study initiation but who otherwise met inclusion criteria for the cohort were selected to increase study power (after applying the exclusion criteria below, this represented: 18 patients five HCV RNA– and 13 HCV RNA+).
Patients were considered to have spontaneously cleared HCV if they had a positive HCV antibody test and no detectable HCV RNA at baseline without having received HCV treatment. Due to the known interaction between chronic hepatitis B virus and HCV, which may render HCV RNA undetectable, we excluded patients with presence of hepatitis B surface antigen [31,32].
Two study periods were considered: ART naïve (no exposure to any antiretroviral) and post-ART. Patients who were initially naïve and subsequently initiated ART whereas enrolled in the cohort were included in both analyses if they had available data in both periods. Patients with prior ART exposure but on treatment interruption at baseline were excluded.
Our primary outcome of interest was change in absolute CD4+ T-lymphocyte count from the first available CD4+ T-lymphocyte measurement until last measure prior to the initiation of ART (for the naïve period) or censoring, according to HCV RNA status. We used a square root transformation of absolute CD4+ T-lymphocyte counts, which has an approximately linear decline and stable variance over time [32,33]. Due to greater ease of clinical interpretation, we also performed the same analyses using absolute CD4 cell count values and report these. However, all goodness-of-fit statistics showed substantially better model fit using square root CD4 cell counts. Given potential effects of advanced liver fibrosis on absolute CD4 cell measures, we also examined the rate of CD4% decline in a similar fashion.
Measurement of potential confounders
We considered the following covariates: sex, age, past and current injection drug use (IDU), estimated duration of HCV infection, year of cohort entry, nadir CD4 cell count, time since nadir CD4+ T-cell count, baseline CD4 cell and follow-up CD8 T-cell counts, highest HIV RNA before therapy, baseline HIV RNA, type of ART (NNRTI vs. protease inhibitor based) and cumulative exposure to ART. The duration of HCV infection was determined using the date of HCV seroconversion, if known, or year of first IDU or blood product exposure as a proxy of HCV infection .
Our primary hypothesis was that CD4+ T-lymphocyte progression would be differential between the two groups with HCV RNA+ patients having slower CD4 recovery, after ART initiation. Further, we hypothesized that CD4 cell decline would be greater in HCV RNA+ patients compared HCV RNA–patients while ART naïve. A statistically significant interaction between HCV RNA status and follow-up time would support our hypotheses.
Baseline was defined as the date of first CD4+ T-lymphocyte measurement in each of the time periods. Baseline demographic and clinical characteristics were compared between HCV RNA+ and HCV RNA– participants using the Mann–Whitney U-test for continuous data, and the χ2 test for frequencies. The rates of change in the square root and absolute CD4+ T-lymphocyte count (or CD4%) in each of the two time periods were determined using linear mixed effect models (SAS PROC mixed). We compared models using random intercept/random slope and random intercept/fixed slope. Although goodness-of-fit was marginally better using the random intercept/random slope model (from likelihood ratio statistics), the estimates of regression parameters from both models were comparable. Consequently, given the number of additional parameters to be estimated with random intercepts/random slopes, the relatively sparse longitudinal CD4 cell data available and the importance of model parsimony, we chose the simpler model (random intercept/fixed slope) for the analyses .
Analyses for the naïve period were truncated at 12 months because of limited number of individuals who remained ART naïve during follow-up. All models were adjusted for age, sex, calendar year, nadir CD4 cell count, IDU, time updated HIV RNA (log copies/ml) and time updated CD8+ T-cells. For the post-ART period, we additionally adjusted for cumulative ART exposure (in years) at baseline and time updated ART exposure. Time updated ART exposure was included as it is important to account for potential interruptions in ART usage, which in turn might impact HIV control and thus CD4 cell recovery, at the time of each CD4 cell measure (e.g. at 6 month intervals).
Planned sensitivity analyses included censoring all patients on first ART interruption, restricting to patients initiating ART after enrolment into the cohort, and restricting to patients with virologic suppression throughout follow-up.
Results were plotted using predicted CD4 cell counts from multivariate linear mixed effect models. Cox proportional hazards models were used to estimate the hazard ratios for first AIDS defining event in the post ART-period according to exposure group.
Model residuals were examined for normality and homoscedasticity using scatter plots. All hypotheses tests were conducted at 5% significance level. All analyses were performed using SAS software, version 9.1 (SAS Institute, Cary, North Carolina, USA).
After the exclusion of 38 patients with chronic hepatitis B infection, 542 patients (515 from the CCC and 27 from IDS) were available for study. Two hundred and thirty-three of these were excluded due to fewer than two CD4 cell measures (most because they had recently entered the cohort study and only had baseline data available). A further 38 patients (n = 2, HCV RNA– and 36 HCV RNA+) who were ART experienced but on treatment interruption at time of first visit were also excluded. Of the remaining 271, 236 were HCV PCR+ and 35 HCV PCR–; none changed PCR status during follow-up. Baseline characteristics of the study groups are shown in Table 1. There were no significant differences between the HCV RNA+ individuals and the HCV RNA– with respect to demographic, risk behaviours, ART regimens or clinical and laboratory characteristics except for higher liver enzymes and markers of fibrosis among HCV RNA+ participants. Losses to follow-up and number of available CD4+ T-lymphocyte values was similar in both groups, as was the median CD4+ T-lymphocyte count at baseline (367 cells/μl for HCV RNA– and 344 cells/μl for HCV RNA+).
CD4 decline prior to antiretroviral therapy exposure
In total, 95 patients were treatment naïve; 70 HCV RNA+ and 25 HCV RNA−. The adjusted slope [95% confidence interval (CI)] of square root CD4 cell decline was −0.40 (−3.51, 2.72) in HCV RNA− vs. −1.40 (−2.79, −0.02) in HCV RNA+ and was significantly different from zero for HCV RNA+ (P = 0.05), whereas the slope for HCV RNA– patients was not significantly different from zero (P = 0.79). However, the interaction between HCV RNA status and follow-up time did not reach statistical significance (P = 0.65). Crude and adjusted analyses of absolute CD4 T-lymphocyte decline are presented in Table 2. Finally, the adjusted rate of CD4% decline was also not significantly different between HCV RNA− and HCV RNA+ (data not shown). Other factors associated with CD4 cell decline were nadir CD4+ T-cell counts and CD8+ T-cells (see Table 2).
CD4 cell increase during antiretroviral therapy exposure
There were 226 patients who contributed data to the post-ART analyses; 201 HCV RNA+ and 25 HCV RNA– including 76 patients who were initially naïve and initiated ART during follow-up. The median follow up time was 18 months (interquartile range, 10–53) for HCV RNA+ and 15 months (interquartile range, 12–43) for HCV RNA– (P = 0.84). HCV RNA+ individuals had significantly slower recovery of CD4+ T-cells on ART compared with HCV RNA– (on average 7 times lower). The adjusted slope (95% CI) of square root CD4 decline was 0.61 (0.28, 0.95) in HCV RNA– vs. 0.13 (0.01, 0.25) for HCV RNA+; P = 0.004 for the interaction between HCV RNA status and follow-up time. Analyses of absolute CD4 T-lymphocyte change during ART exposure are shown in Table 3 and Fig. 1. CD4% analyses yielded similar results (data not shown).
Other covariates associated with CD4 recovery included higher nadir CD4+ T-cell counts and CD8+ T-cell counts, cumulative ART exposure at baseline and time updated ART exposure; IDU, and higher HIV RNA were negatively associated with CD4+ T-lymphocyte recovery, as shown in Table 3. Including the type of ART regimen (protease inhibitor or NNRTI) did not alter the results. In fact, CD4 cell nadir and HIV viral load accounted for a substantial proportion of CD4 cell variation. After accounting for these variables (sequentially), the CD4 recovery rate was reduced by as much as 50% among the HCV PCR +. There was no evidence for an interaction between HCV RNA status and having HIV RNA less than 50 copies/ml (P = 0.44).
Analyses restricted to individuals who initiated ART after entry into the cohort showed similar results. The adjusted change (95% CI) of absolute CD4+ T-cell counts was 26 (12,41; P = 0.0004) for those HCV RNA– and 3.5 (−0.64, 7.7; P = 0.097) for HCV RNA+, with the interaction between HCV RNA status and follow-up time highly significant at P < 0.0001.
Censoring ART exposed patients at the time of first treatment interruption also resulted in similar findings (interaction between HCV RNA status and follow-up time; P = 0.0036). Finally, when restricting to patients with an undetectable viral load throughout follow-up (n = 178), the impact of HCV RNA was attenuated. HCV PCR + patients still had slower CD4 cell recovery (square root CD4, 0.29 vs. 0.51/year) but the interaction term was no longer significant (P = 0.28).
There were only 31 first AIDS defining events in the post-ART period, nondifferentially distributed between HCV RNA– (n = 4, 20%) and HCV RNA+ (n = 27, 15%) individuals. There was no significant difference in the time to AIDS according to HCV PCR status before (hazard ratio 0.62, 95% CI, 0.22–1.80), or after adjustment for baseline CD4 cell and HIV RNA (hazard ratio 0.46, 95% CI, 0.16–1.39).
Understanding the impact of HCV infection on the progression of HIV has important implications for the management of patients with HIV–HCV coinfection. Although it is well established that chronic HCV infection causes premature liver disease in HIV-positive individuals [4,35], the impact of HCV on HIV progression has been thought to be negligible [17,18]. To the best of our knowledge, this is the first study to specifically examine the impact of spontaneous HCV RNA clearance on HIV-disease progression in the setting of HIV–HCV coinfection. We show that after accounting for many clinical and demographic factors that affect HIV progression, spontaneous clearance of HCV infection is independently associated with a better rate of CD4 cell recovery once ART is introduced. There was also a trend to greater CD4 cell decline prior to ART initiation among those chronically infected with HCV when compared with individuals who spontaneously cleared, although this did not reach statistical significance probably due to lack of power.
Our findings were robust with large differences in CD4 cell recovery seen in analyses using both absolute CD4 cell count and CD4%, and in sensitivity analyses restricting to naïve patients initiating ART. The effect of chronic HCV on CD4 cell recovery seen in those initiating ART persisted to a similar degree throughout stable ART, suggesting a continued impact of active HCV replication on immune restoration and potentially on immune function even after years of ART exposure. This effect was not explained by differences in CD4 cell set point, baseline HIV RNA or ART regimen between those chronically infected and spontaneous clearers. The negative association remained after accounting for IDU, updated ART exposure and HIV replication. We could not, however, detect a difference in clinical AIDS events, which were relatively few in number in this cohort of individuals largely well controlled virologically on HIV treatment.
Although data have been conflicting as to the impact of HCV coinfection on immune restoration in patients who commence ART compared with those with HIV infection alone, a metanalysis of eight studies involving 6216 patients concluded that coinfected patients had an increase in CD4 cell count that was on average 33.4 cells/μl (95% CI, 23.5–43.3 cells/μl) lower after at least 1 year of ART . This difference is similar to what we observed between HCV RNA negative and positive persons from the cohort. A recent paper however found no difference in CD4 cell responses after ART initiation among virologically suppressed HCV antibody positive patients according to the presence of HCV viremia  raising possibility that non-adherence or HCV-driven HIV replication may account for poorer CD4 cell outcomes among HCV RNA positive individuals. Although adjusting for HIV RNA in follow-up did not remove the independent effect of HCV RNA in our analyses, when we evaluated CD4 cell responses among those with complete HIV suppression in follow-up, the impact of HCV replication was attenuated. It is, however, difficult to draw conclusions from such post-hoc analyses given the smaller sample size and the biases inherent in selecting individuals based on future HIV response profiles.
The mechanism by which chronic HCV replication may have deleterious effects on CD4 cell count reconstitution cannot be determined from our study. Ongoing T-cell activation related to HCV infection may limit the immunologic responses of patients with sustained viral suppression on ART. For example, for every 5% increase in the proportion of activated CD8+ T-cells, 35 fewer CD4+ T-cells were gained . Significantly elevated CD38 expression in both CD8+ and CD4+ T-cells has been described in HIV–HCV coinfected compared with HCV monoinfected persons and healthy controls, indicating that coinfection is associated with high levels of chronic activation of both T-cell compartments despite effective control of HIV replication by HAART . Interestingly, a reduction in the frequency of activated CD8+ and CD4+ T-cells has been observed after HCV treatment . In fact, we observed higher CD8 cell counts were associated with better CD4 cell responses. However, adjusting for CD8 cell counts did not remove the independent effect of HCV RNA on CD4 cell slope.
Other potential explanations include direct infection of CD4+ T-cells by HCV that has been shown to be lymphotropic in the setting of HIV coinfection. Negative strand RNA has been detected in both CD4+ and CD8+ T-cells as well as in monocyte/macrophages which may lead to direct interactions between these viral pathogens that could influence CD4 cell recovery . Finally, HCV coinfection has been reported to sensitize CD4+ T-cells towards apoptosis in untreated HIV that could explain more rapid CD4 cell loss prior to ART. However, this effect is rapidly lost under ART . Alternatively, the differences in CD4 cell count progression observed might have been due to innate differences in the immune system of individuals that allowed them to spontaneously clear HCV and also have a more favourable prognosis with respect to HIV.
Even though we did not observe an impact of poor CD4 cell recovery on AIDS-related outcomes, there may be other important potential consequences to HCV-associated blunted immune recovery. Persistently lower CD4 cell counts while virologically controlled have been associated with higher rates of ART toxicities (e.g. peripheral neuropathy, lipoatrophy, renal dysfunction) . There is also a growing recognition of the importance of immune activation in driving other conditions that are resulting in excess morbidity and mortality in the post-ART era (e.g. liver, cardiovascular and renal disease) [40,41]. Chronic HCV infection may thus handicap the immune system and eradicating HCV through successful HCV treatment may be necessary to allow more robust immune reconstitution and possibly mitigate the effects of chronic HCV on these comorbidities. It would also be of interest to determine in future if differential CD4 cell recovery rates observed might have implications for the risk of these other non-AIDS events in the coinfected population.
A strength of our study is that we compared patients derived from similar populations with similar risk behaviours and lifestyles with and without active HCV RNA replication. Further, we were able to account for IDU and other clinical confounders, as well as for, potential treatment interruptions.
Our primary limitation was insufficient numbers of naïve patients who spontaneously cleared their infection with too short a follow-up time to conclusively determine if chronic HCV infection also impacts CD4 cell count progression prior to ART. Observational studies such as ours are also subject to potential cohort effects. Although we accounted for known factors that might influence outcome measurements, we cannot exclude the possibility of residual confounding. Finally, we were not able to evaluate T-cell function beyond absolute lymphocyte quantification to determine to what degree chronic immune activation or other mechanisms are potentially explanatory.
We found that CD4 cell progression is negatively affected by the presence of ongoing HCV replication in coinfected individuals who are taking ART. Our data support the need to study individuals with chronic replicating HCV separately from those who have cleared their infection when conducting research into HIV–HCV coinfection. Elucidating the mechanisms by which this difference occurs and investigating the impact of HCV treatment on CD4 cell progression should be prioritized. When successful, HCV treatment might have an important role not only in improving HCV related outcomes, but for HIV-related prognosis as well for coinfected persons.
The Canadian co-infection cohort investigators (CTN222) are Drs Jeff Cohen, Windsor Regional Hospital Metroplitan Campus, Windsor, ON; Brian Conway, Downtown IDC, Vancouver, BC; Curtis Cooper, Ottawa General Hospital, Ottawa, ON; Pierre Côté, Clinique du Quartier Latin, Montreal, QC; Joseph Cox, Montreal General Hospital; Montreal, QC; John Gill, Southern Alberta HIV Clinic, Calgary, AB; Mark Tyndall; Native Health Cente, Vancouver, ON; Shariq Haider, McMaster University, Hamilton, ON; Marrianne Harris St Paul's Hospital, Vancouver, BC; David Hasse, Capital District Health Authority, Halifax, NS; Julio Montaner, St Paul's Hospital, Vancouver, BC; Erica Moodie, McGill University, Montreal, QC; Neora Pick Oak Tree Clinic, Vancouver, BC; Annita Rachlis Sunnybrook & Women's College Health Sciences Centre, Toronto, ON; Roger Sandre, HAVEN Program, Sudbury, ON; Danielle Rouleau, Centre Hospitalier de l'Université de Montréal, Montréal, QC; David Wong University Health Network, Toronto, ON; Mark Hull, BC Centre for Excellence in HIV/AIDS, Vancouver, BC; and Sharon Walmsley, Toronto General Hospital, Toronto, ON.
We thank Alex Schnubb, Manon Desmarais, Curtis Sikora, Christine O'Reilly, Brenda Beckthold, Heather Haldane, Laura Puri, Nancy McFarland, Claude Gagne, Elizabeth Knight, Lesley Gallagher, Warmond Chan, Sandra Gordan, Judy Latendre-Paquette, Natalie Jahnke, Viviane Josewski, Evelyn Mann, and Anja McNeil for their assistance with study coordination, participant recruitment and care. We thank Jim Young for statistical advice.
This work was presented in part at the 16th Conference on Retroviruses and Opportunistic Infections (Montreal, February 2009; abstract #836).
This study was funded by the Fonds de recherche en santé du Québec, Réseau SIDA/maladies infectieuses (FRSQ), the Canadian Institutes of Health Research (CIHR MOP-79529) and the CIHR Canadian HIV Trials Network (CTN222). Dr Martin Potter is supported by a CTN Postdoctoral Fellowship award. Dr Marina Klein is supported by a Chercheur-Boursier clinician senior career award from the FRSQ.
M.B.K. is the principal investigator for the study and with M.P. formulated the project, analysed the data and drafted the manuscript. A.O. and H.Y. performed statistical analyses. S.S. managed the study. All of the authors contributed to the acquisition and/or interpretation of the data and revising the manuscript. All of the authors approved the final version of the manuscript for publication.
1. Martin-Carbonero L, Soriano V, Valencia E, Garcia-Samaniego J, Lopez M, Gonzalez-Lahoz J. Increasing impact of chronic viral hepatitis on hospital admissions and mortality among HIV-infected patients. AIDS Res Hum Retroviruses 2001; 17:1467–1471.
2. Bica I, McGovern B, Dhar R, Stone D, McGowan K, Scheib R, Snydman DR. Increasing mortality due to end-stage liver disease in patients with human immunodeficiency virus infection. Clin Infect Dis 2001; 32:492–497.
3. Pol S, Vallet-Pichard A, Fontaine H. Hepatitis C and human immune deficiency coinfection at the era of highly active antiretroviral therapy. J Viral Hepat 2002; 9:1–8.
4. Rosenthal E, Pialoux G, Bernard N, Pradier C, Rey D, Bentata M, et al
. Liver-related mortality in human-immunodeficiency-virus-infected patients between 1995 and 2003 in the French GERMIVIC Joint Study Group Network (MORTAVIC 2003 Study). J Viral Hepat 2007; 14:183–188.
5. Alter MJ. Epidemiology of viral hepatitis and HIV co-infection. J Hepatol 2006; 44:S6–9.
6. Shepard CW, Finelli L, Alter MJ. Global epidemiology of hepatitis C virus infection. Lancet Infect Dis 2005; 5:558–567.
7. Miller MF, Haley C, Koziel MJ, Rowley CF. Impact of hepatitis C virus on immune restoration in HIV-infected patients who start highly active antiretroviral therapy: a meta-analysis. Clin Infect Dis 2005; 41:713–720.
8. Puoti M, Bonacini M, Spinetti A, Putzolu V, Govindarajan S, Zaltron S, et al
. Liver fibrosis progression is related to CD4 cell depletion in patients coinfected with hepatitis C virus and human immunodeficiency virus. J Infect Dis 2001; 183:134–137.
9. Pineda JA, Garcia-Garcia JA, Aguilar-Guisado M, Rios-Villegas MJ, Ruiz-Morales J, Rivero A, et al
. Clinical progression of hepatitis C virus-related chronic liver disease in human immunodeficiency virus-infected patients undergoing highly active antiretroviral therapy. Hepatology 2007; 46:622–630.
10. Piroth L, Duong M, Quantin C, Abrahamowicz M, Michardiere R, Aho LS, et al
. Does hepatitis C virus co-infection accelerate clinical and immunological evolution of HIV-infected patients? AIDS 1998; 12:381–388.
11. Piroth L, Grappin M, Cuzin L, Mouton Y, Bouchard O, Raffi F, et al
. Hepatitis C virus co-infection is a negative prognostic factor for clinical evolution in human immunodeficiency virus-positive patients. J Viral Hepat 2000; 7:302–308.
12. Carlos Martin J, Castilla J, Lopez M, Arranz R, Gonzalez-Lahoz J, Soriano V. Impact of chronic hepatitis C on HIV-1 disease progression. HIV Clin Trials 2004; 5:125–131.
13. Dorrucci M, Valdarchi C, Suligoi B, Zaccarelli M, Sinicco A, Giuliani M, et al
. The effect of hepatitis C on progression to AIDS before and after highly active antiretroviral therapy. AIDS 2004; 18:2313–2318.
14. De Luca A, Bugarini R, Lepri AC, Puoti M, Girardi E, Antinori A, et al
. Coinfection with hepatitis viruses and outcome of initial Antiretroviral regimens in previously naive HIV-Infected subjects. Archives of Internal Medicine 2002; 162:2125–2132.
15. Greub G. Clinical progression, survival, and immune recovery during antiretroviral therapy in patients with HIV-1 and hepatitis C virus coinfection: the Swiss HIV Cohort Study (vol 356, pg 1800, 2000). Lancet 2001; 357:1536–11536.
16. Stebbing J, Waters L, Mandalia S, Bower M, Nelson M, Gazzard B. Hepatitis C virus infection in HIV type 1-infected individuals does not accelerate a decrease in the CD4(+) cell count but does increase the likelihood of AIDS-defining events. Clin Infect Dis 2005; 41:906–911.
17. Rockstroh JK, Mocroft A, Soriano V, Tural C, Losso MH, Horban A, et al
. Influence of hepatitis C virus infection on HIV-1 disease progression and response to highly active antiretroviral therapy. J Infect Dis 2005; 192:992–1002.
18. Sulkowski MS, Moore RD, Mehta SH, Chaisson RE, Thomas DL. Hepatitis C and progression of HIV disease. JAMA 2002; 288:199–206.
19. Carmo RA, Guimaraes MDC, Moura AS, Neiva AM, Versiani JB, Lima LV, et al
. The influence of HCV coinfection on clinical, immunological and virological responses to HAART in HIV-patients. Braz J Infect Dis 2008; 12:173–179.
20. Sullivan PS, Hanson DL, Teshale EH, Wotring LL, Brooks JT. Effect of hepatitis C infection on progression of HIV disease and early response to initial antiretroviral therapy. AIDS 2006; 20:1171–1179.
21. Law WP, Duncombe CJ, Mahanontharit A, Boyd MA, Ruxrungtham K, Lange JMA, et al
. Impact of viral hepatitis co-infection on response to antiretroviral therapy and HIV disease progression in the HIV-NAT cohort. AIDS 2004; 18:1169–1177.
22. Lauer GM, Nguyen TN, Day CL, Robbins GK, Flynn T, McGowan K, et al
. Human immunodeficiency virus type 1-hepatitis C virus coinfection: intraindividual comparison of cellular immune responses against two persistent viruses. J Virol 2002; 76:2817–2826.
23. Graham CS, Curry M, He Q, Afdhal N, Nunes D, Fleming C, et al
. Comparison of HCV-specific intrahepatic CD4+ T cells in HIV/HCV versus HCV. Hepatology 2004; 40:125–132.
24. Hunt PW, Martin JN, Sinclair E, Bredt B, Hagos E, Lampiris H, Deeks SG. T cell activation is associated with lower CD4+ T cell gains in human immunodeficiency virus-infected patients with sustained viral suppression during antiretroviral therapy. J Infect Dis 2003; 187:1534–1543.
25. Korner C, Kramer B, Schulte D, Coenen M, Mauss S, Fatkenheuer G, et al
. Effects of HCV co-infection on apoptosis of CD4(+) T-cells in HIV positive patients. Clin Sci 2009; 116:861–870.
26. Laskus T, Radkowski M, Piasek A, Nowicki M, Horban A, Cianciara J, Rakela J. Hepatitis C virus in lymphoid cells of patients coinfected with human immunodeficiency virus type 1: evidence of active replication in monocytes/macrophages and lymphocytes. J Infect Dis 2000; 181:442–448.
27. Netski DM, Mosbruger T, Depla E, Maertens G, Ray SC, Hamilton RG, et al
. Humoral immune response in acute hepatitis C virus infection. Clin Infect Dis 2005; 41:667–675.
28. Soriano V, Mocroft A, Rockstroh J, Ledergerber B, Knysz B, Chaplinskas S, et al. Spontaneous viral clearance, viral load, and genotype distribution of hepatitis C virus (HCV) in HIV-infected patients with anti-HCV antibodies in Europe
. J Infect Dis
29. Hofer H, Watkins-Riedel T, Janata O, Penner E, Holzmann H, Steindl-Munda P, et al
. Spontaneous viral clearance in patients with acute hepatitis C can be predicted by repeated measurements of serum viral load. Hepatology 2003; 37:60–64.
30. Klein MB, Saeed S, Yang H, Cohen J, Conway B, Cooper C, et al. Cohort profile: the Canadian HIV-hepatitis C co-infection Cohort Study
. Int J Epidemiol
2009. [Epub ahead of print]
31. Wang YM, Ng WC, Lo SK. Suppression of hepatitis C virus by hepatitis B virus in coinfected patients at the National University Hospital of Singapore. J Gastroenterol 1999; 34:481–485.
32. Koike K, Yasuda K, Yotsuyanagi H, Moriya K, Hino K, Kurokawa K, Iino S. Dominant replication of either virus in dual infection with hepatitis viruses B and C. J Med Virol 1995; 45:236–239.
33. Bacchetti P, Tien PC, Seaberg EC, O'Brien TR, Augenbraun MH, Kral AH, et al
. Estimating past hepatitis C infection risk from reported risk factor histories: implications for imputing age of infection and modeling fibrosis progression. BMC Infect Dis 2007; 7:145.
34. Diggle PJ, Heagerty P, Liang K-Y, Zeger SL. Analysis of Longitudinal Data
. 2nd ed. New York: Oxford University Press; 2002.
35. Macias J, Melguizo I, Fernandez-Rivera FJ, Garcia-Garcia A, Mira JA, Ramos AJ, et al
. Mortality due to liver failure and impact on survival of hepatitis virus infections in HIV-infected patients receiving potent antiretroviral therapy. Eur J Clin Microbiol Infect Dis 2002; 21:775–781.
36. Peters L, Mocroft A, Soriano V, Rockstroh JK, Losso M, Valerio L, et al
. Hepatitis C virus coinfection does not influence the CD4 cell recovery in HIV-1-infected patients with maximum virologic suppression. J Acquir Immune Defic Syndr 2009; 50:457–463.
37. Gonzalez VD, Falconer K, Blom KG, Reichard O, Morn B, Laursen AL, et al
. High levels of chronic immune activation in the T-cell compartments of patients coinfected with hepatitis C virus and human immunodeficiency virus type 1 and on highly active antiretroviral therapy are reverted by alpha interferon and ribavirin treatment. J Virol 2009; 83:11407–11411.
38. Laskus T, Radkowski M, Jablonska J, Kibler K, Wilkinson J, Adair D, Rakela J. Human immunodeficiency virus facilitates infection/replication of hepatitis C virus in native human macrophages. Blood 2004; 103:3854–3859.
39. Lichtenstein KA, Armon C, Buchacz K, Chmiel JS, Moorman AC, Wood KC, et al
. Initiation of antiretroviral therapy at CD4 cell counts >/=350 cells/mm3 does not increase incidence or risk of peripheral neuropathy, anemia, or renal insufficiency. J Acquir Immune Defic Syndr 2008; 47:27–35.
40. Friis-Moller N, Sabin CA, Weber R, d'Arminio Monforte A, El-Sadr WM, Reiss P, et al
. Combination antiretroviral therapy and the risk of myocardial infarction. N Engl J Med 2003; 349:1993–2003.
41. El-Sadr WM, Lundgren JD, Neaton JD, Gordin F, Abrams D, Arduino RC, et al
. CD4+ count-guided interruption of antiretroviral treatment. N Engl J Med 2006; 355:2283–2296.
Keywords:© 2010 Lippincott Williams & Wilkins, Inc.
antiretroviral therapy; CD4+ T-lymphocytes; coinfection; disease progression; Hepatitis C virus; HIV