Abstract
Background
The clinical and demographic characteristics that predict antiretroviral efficacy among patients co-infected with HIV and hepatitis B virus (HBV) remain poorly defined. We evaluated HIV virological suppression and rebound in a cohort of HIV–HBV co-infected patients initiated on antiretroviral therapy.
Methods
A retrospective cohort analysis was performed with Canadian Observation Cohort Collaboration data. Cox proportional hazards models were used to determine the factors associated with time to virological suppression and time to virological rebound.
Results
HBV status was available for 2,419 participants. A total of 8% were HBV co-infected, of whom 95% achieved virological suppression. After virological suppression, 29% of HIV–HBV co-infected participants experienced HIV virological rebound. HBV co-infection itself did not predict virological suppression or rebound risk. The rate of virological suppression was lower among patients with a history of injection drug use or baseline CD4 cell counts of <199 cells per cubic millimetre. Low baseline HIV RNA and men-who-have-sex-with-men status were significantly associated with a higher rate of virological suppression. Injection drug use and non-White race predicted viral rebound.
Conclusions
HBV co-infected HIV patients achieve similar antiretroviral outcomes as those living with HIV mono-infection. Equitable treatment outcomes may be approached by targeting resources to key subpopulations living with HIV–HBV co-infection.
Key words: antiretroviral efficacy, co-infection, hepatitis B, HIV, virological suppression
Abstract
Historique
Les caractéristiques cliniques et démographiques prédictives de l’efficacité antirétrovirale chez les patients co-infectés par le virus de l’immunodéficience humaine (VIH) et le virus de l’hépatite B (VHB) demeurent mal définies. Les chercheurs ont évalué la suppression et le rebond virologiques du VIH dans une cohorte de patients co-infectés par le VIH et le VHB chez qui on avait entrepris un traitement antirétroviral.
Méthodologie
Les chercheurs ont réalisé une analyse rétrospective de cohorte à l’aide des données de la Canadian Observation Cohort Collaboration. Ils ont utilisé le modèle à risques proportionnels de Cox pour déterminer les facteurs associés à la période jusqu’à la suppression et au rebond virologiques.
Résultats
Les chercheurs ont obtenu le statut de VHB de 2 419 participants. Au total, 8 % étaient co-infectés par le VHB, dont 95 % présentaient une suppression virologique. Après la suppression virologique, 29 % des participants co-infectés par le VIH et le VHB ont subi un rebond virologique du VIH. En elle-même, la co-infection par le VHB n’était pas prédictive de la suppression virologique ou du risque de rebond. Le taux de suppression virologique était plus faible chez les patients ayant des antécédents de consommation de drogues injectables ou une numération des cellules CD4 de référence de moins de 199 cellules par millimètre cube. Un ARN du VIH de référence bas et les hommes ayant des relations sexuelles avec des hommes étaient associés de manière significative avec un taux plus élevé de suppression virologique. La consommation de drogues injectables et les races non blanches étaient prédictives d’un rebond viral.
Conclusion
Les patients atteints du VHB co-infectés par le VIH obtenaient des résultats antirétroviraux semblables à ceux qui étaient seulement infectés par le VIH. On peut anticiper des résultats cliniques équitables des traitements en ciblant les ressources vers les sous-populations atteintes d’une co-infection par le VIH et le VHB.
Mots-clés : co-infection, efficacité antirétrovirale, hépatite B, suppression virologique, VIH
Introduction
HIV and hepatitis B virus (HBV) are among the leading causes of death from communicable diseases worldwide (1). An estimated 5%–20% of the 37 million people infected with HIV are co-infected with HBV (2). The high rate of co-infection with HBV and HIV has been attributed to shared routes of transmission (3,4).
People infected with both HIV and HBV face worse clinical outcomes than those infected with either HIV or HBV alone, which is attributable to interactions between the two infections in the co-infected host. HIV co-infection is known to influence the natural history of HBV (5). HBV-related liver disease is a leading cause of non–AIDS-related morbidity and mortality among co-infected patients on antiretroviral (ARV) therapy (6–10). Among patients with HBV infection, co-infection with HIV has been found to increase viral replication and infectivity (11,12), as well as the risk of HBV chronicity, cirrhosis, hepatocellular carcinoma, and liver-related mortality (11,13–16). HIV co-infection also influences the natural history of hepatitis C virus (HCV), with similar effects on viral load (17,18) and progression to severe liver disease and cirrhosis (19,20).
Current evidence is inconclusive as to whether HBV co-infection influences the rate of HIV progression (21). A number of cohorts have demonstrated decreased CD4 cell counts among co-infected patients compared with HIV-infected patients (22–27). However, these findings largely precede the era of or involve patients who have not yet received ARV therapy. More recent cohorts including patients on ARV therapy have generally demonstrated no difference in CD4 cell counts between co-infected and HIV-infected participants (9,15,28,29), although other studies are conflicting (26,30). Few studies have analyzed the effect of HBV status on virological response, and these have found no difference in the time to virological suppression between HIV-infected and HIV–HBV co-infected participants (30–32).
The impact of HIV–HBV co-infection on individuals receiving ARV is unclear. In an effort to address these gaps, we used the Canadian Observation Cohort (CANOC) Collaboration (33), a large national clinical cohort of ARV-naïve HIV-infected patients, to evaluate virological efficacy in a cohort of HIV–HBV co-infected participants initiating ARV therapy.
Methods
A retrospective cohort analysis was performed using data from the CANOC Collaboration. CANOC is a collaboration among eight cohorts from British Columbia, Quebec, and Ontario. A detailed description of the CANOC profile has been published elsewhere (33). Participants were HIV-infected patients with no previous exposure to ARV therapy who initiated combination ARV (use of at least three ARV drugs) between January 1, 2000, and December 14, 2014.
Data collection
Patient selection and data collection were performed at all CANOC sites. All identifying information was removed on site before submission to the CANOC coordinating site. On completion of data collection, CANOC consisted of 10,477 ARV initiators.
Study design and inclusion criteria
Only those participants with established HBV infection status and complete liver enzyme data were included. Baseline data were generally defined as data collected within 12 months before initiating ARV therapy. However, for CD4 cell count and HIV RNA data, baseline was defined as 6 months before initiating ARV therapy. End of follow-up was defined as either December 31, 2014, or any time within 12 months before a participant’s last follow-up date.
HBV co-infection was determined by serology (HBV surface antigen positive), polymerase chain reaction (PCR; HBV DNA positive), or physician report. The extent of liver fibrosis was determined by the aspartate transaminase (AST)-to-platelet ratio index (APRI), a non-invasive, validated biomarker of liver fibrosis in viral hepatitis (34,35). APRI was calculated by the formula [AST/(AST upper limit of normal)/platelets) × 100] (36). The AST upper limit of normal was set at 40 IU/L. APRI ratios of ≤0.50, 0.51–1.49, and ≥1.50 were used to define mild, intermediate, and clinically significant fibrosis, respectively (35). Values of ≥2.0 were used to indicate the presence of advanced fibrosis or cirrhosis (35).
Demographic variables included age, sex, ethnicity, province of residence, men-who-have-sex-with-men (MSM) and people-who-use-injection-drugs (PWID) status, and mortality status. HCV infection was defined by serology, PCR, or physician report. HIV virological suppression was defined as two consecutive viral load measurements of <50 copies/mL measured a minimum of 30 days apart after initiating ARV treatment. HIV virological rebound was defined as two viral load measurements of >200 copies/mL recorded at least 30 days apart after previously achieving virological suppression (9,13–15,30). Participants who did not achieve either of the outcome end points were censored at their last available viral load collection date or, alternatively, on December 31, 2014.
Missing data
A complete case analysis was used for all variables except ethnicity because of the large proportion of missing data for this variable. Participants were excluded from the analysis if data were missing for any other variable, including viral hepatitis co-infection status, HIV risk factors, liver enzymes, baseline CD4 cell count, and HIV viral load.
Statistical analysis
Demographic and clinical characteristics were presented using frequencies and proportions for categorical variables and median and interquartile ranges for continuous variables. Categorical variables were compared across HIV–HBV co-infected and HIV-infected groups using χ2 or Fisher exact tests, and continuous variables were compared using Wilcoxon’s rank-sum test.
Cox proportional hazards models were developed to describe the factors associated with time to virological suppression after ARV initiation and time to virological rebound after virological suppression. The proportional hazards assumption was verified both graphically and statistically. Variables that violated this assumption were excluded from multivariable analyses to avoid bias. Variables were selected on the basis of prior background research and preliminary analyses. Unadjusted and adjusted hazard ratios (HRs) are presented along with 95% confidence intervals (CIs).
An exploratory model selection process based on the Akaike information criterion and type III p-values was used to guide final model selection. Statistical tests were considered significant at α = 0.05. Analyses were conducted using SAS version 9.4 software (SAS Institute, Cary, NC, USA).
Results
The CANOC analysis set consisted of 2,419 participants, of whom 8% (199) were HIV–HBV co-infected. Initially, a total of 10,477 HIV-positive participants were identified. One site was excluded from analysis because of possible HBV misclassification (1,188), 2,476 participants were excluded because of unknown HBV status, and 4,394 participants did not have complete AST data to allow for APRI calculations at baseline and at the most recent date of follow-up. In general, the characteristics of the CANOC participants included in our analysis were similar to those of excluded individuals.
The baseline demographic and clinical characteristics of this study cohort are described in detail elsewhere (37; Appendix A). HIV–HBV co-infected participants had lower baseline median CD4 cell counts (188 cells/µL versus 235 cells/µL; p = 0.0002) and were more likely to have had an AIDS-defining illness by the time of ARV treatment initiation (28% versus 20%; p = 0.01). Participants infected with HBV were more likely to be HCV seropositive (31% versus 23%; p = 0.02). HIV–HBV co-infected patients were more likely to have a history of injection drug use (28% versus 21%; p = 0.03), and they had higher APRI scores at baseline (0.50 versus 0.37; p < 0.0001).
HIV virological suppression was achieved by 92% (2,230) of participants. Of 199 HIV–HBV co-infected participants, 95% (190) achieved virological suppression. The median time to suppression for HIV–HBV co-infected patients was 0.33 years (IQR 0.22 to 0.51 y) compared with 0.66 years (IQR 0.32 to 2.1 y) in HIV-infected participants. There was no statistically significant difference in time to virological suppression between HIV–HBV co-infected and HIV-infected groups (Figure 1). HBV status was not statistically associated with time to virological suppression in logistic regression models (data not shown).
Figure 1:
Time to virological suppression by hepatitis B infection status
In adjusted multivariable analyses, the rate of virological suppression was significantly lower among patients who had a history of injection drug use (HR 0.78; 95% CI 0.69 to 0.88; p < 0.0001) or low baseline CD4 cell counts (<199 cells/mm3; HR 0.73; 95% CI 0.63 to 0.85; p = 0.0004) compared with those with >500 cells/mm3 (Table 1). Low baseline HIV RNA and MSM status were significantly associated with higher rate of virological suppression in adjusted analysis. HCV co-infection and fibrosis stage (APRI) were not significantly associated with rate of virological suppression in adjusted models.
Table 1:
Unadjusted and adjusted Cox regression proportional HR examining factors associated with time to virological suppression (N = 2,230)
| Variable | Time to suppression since first ARV initiation, y | |||
|---|---|---|---|---|
| Univariable analysis | Multivariable analysis | |||
| Hazard ratio (95% CI) | Wald p | Hazard ratio (95% CI) | Wald p | |
| Hepatitis B | ||||
| Not co-infected (ref.) | — | |||
| Co-infected | 0.96 (0.83 to 1.12) | 0.62 | ||
| Hepatitis C | ||||
| Not co-infected (ref.) | — | |||
| Co-infected | 0.69 (0.63 to 0.77) | <0.0001 | ||
| Race | ||||
| White (ref.) | ||||
| Black | 1.17 (1.04 to 1.31) | 0.007 | 1.16 (1.01 to 1.33) | 0.03 |
| Indigenous | 0.65 (0.54 to 0.79) | <0.0001 | 0.83 (0.68 to 1.00) | 0.05 |
| Asian | 1.13 (0.95 to 1.34) | 0.16 | 1.08 (0.91 to 1.28) | 0.36 |
| Hispanic | 1.13 (0.93 to 1.37) | 0.23 | 1.01 (0.83 to 1.23) | 0.91 |
| Other | 1.04 (0.98 to 1.25) | 0.72 | 1.15 (0.92 to 1.44) | 0.22 |
| Unknown | 1.00 (0.89 to 1.13) | 0.99 | 0.93 (0.82 to 1.05) | 0.26 |
| Birth sex | ||||
| Female (ref.) | ||||
| Male | 1.21 (1.08 to 1.35) | 0.0007 | 1.16 (1.02 to 1.32) | 0.03 |
| Province | ||||
| British Columbia (ref.) | ||||
| Ontario | 1.11 (1.01 to 1.22) | 0.03 | ||
| Quebec | 1.27 (1.13 to 1.42) | <0.0001 | ||
| Age at first ARV | 1.00 (1.00 to 1.01) | 0.19 | 1.01 (1.00 to 1.01) | 0.0008 |
| MSM | 1.29 (1.19 to 1.41) | <0.0001 | 1.25 (1.11 to 1.40) | 0.0002 |
| PWID | 0.65 (0.59 to 0.73) | <0.0001 | 0.78 (0.69 to 0.88) | <0.0001 |
| Baseline HIV viral load (log10 copies/mL) | ||||
| <4 (ref.) | ||||
| 4–5 | 0.64 (0.57 to 0.72) | <0.0001 | 0.65 (0.57 to 0.74) | <0.0001 |
| >5 | 0.46 (0.40 to 0.52) | <0.0001 | 0.48 (0.45 to 0.52) | <0.0001 |
| Baseline CD4 count (cells/mm3) | ||||
| >500 (ref.) | ||||
| ≤200 | 0.60 (0.52 to 0.70) | <0.0001 | 0.73 (0.63 to 0.85) | 0.0004 |
| 200–349 | 0.71 (0.61 to 0.83) | <0.0001 | 0.73 (0.62 to 0.84) | 0.0001 |
| 350–499 | 0.81 (0.68 to 0.95) | 0.01 | 0.76 (0.64 to 0.90) | 0.006 |
| Baseline APRI | ||||
| Mild (ref.) | — | |||
| Intermediate | 0.83 (0.75 to 0.91) | <0.0001 | ||
| Clinically significant | 0.89 (0.65 to 1.22) | 0.47 | ||
| Advanced fibrosis/cirrhosis | 0.93 (0.76 to 1.14) | 0.48 | ||
Note: Dashes indicate not included in multivariable analysis
ARV = antiretroviral; ref. = Reference; MSM = Men who have sex with men; PWID = People who use injection drugs; APRI = aspartate aminotransferase-to-platelet ratio index
After virological suppression, 29% (56/190) of HIV–HBV co-infected participants experienced HIV virological rebound. The median time to rebound was 1.93 years (IQR 0.99 to 3.76) among HIV–HBV co-infected participants and 4.5 years (IQR 2.31 to 7.79) among HIV-infected patients. No significant difference in virological rebound incidence was identified between HIV–HBV co-infected and HIV-infected groups (Figure 2). Male gender (HR 0.67; 95% CI 0.54 to 0.83; p = 0.0002), older age (HR 0.98; 95% CI 0.97 to 0.99; p < 0.0001), and residing in Ontario (HR 0.75; 95% CI 0.61 to 0.94; p = 0.01) compared with British Columbia, were associated with decreased rate of virological rebound in adjusted analyses (Table 2). Participants with HCV co-infection (HR 1.87; 95% CI 1.45 to 2.40; p < 0.0001) compared with no HCV infection, injection drug use (HR 1.39; 95% CI 1.06 to 1.81; p = 0.02) compared with no use, and Black (HR 1.38; 95% CI 1.05 to 1.81; p = 0.02) or Indigenous (HR 1.46, 95% CI 1.09 to 1.96, p = 0.01) ethnicity compared with White ethnicity experienced increased rate of virological rebound. Baseline viral load and APRI level were not statistically associated with time to virological rebound.
Figure 2:
Time to virological rebound by hepatitis B infection status
Table 2:
Unadjusted and adjusted Cox regression proportional HR examining factors associated with time to virological rebound (N = 2,230)
| Variable | Time to rebound since first ARV initiation, y | |||
|---|---|---|---|---|
| Univariable analysis | Multivariable analysis | |||
| Hazard ratio (95% CI) | Wald p | Hazard ratio (95% CI) | Wald p | |
| Hepatitis B | ||||
| Not co-infected (ref.) | — | |||
| Co-infected | 1.21 (0.92 to 1.60) | 0.17 | ||
| Hepatitis C | ||||
| Not co-infected (ref.) | ||||
| Co-infected | 2.45 (2.06 to 2.91) | <0.0001 | 1.87 (1.45 to 2.40) | <0.0001 |
| Race | ||||
| White (ref.) | ||||
| Black | 1.26 (1.00 to 1.57) | 0.05 | 1.38 (1.05 to 1.81) | 0.02 |
| Indigenous | 2.95 (2.26 to 3.86) | <0.0001 | 1.46 (1.09 to 1.96) | 0.01 |
| Asian | 0.64 (0.41 to 0.98) | 0.04 | 0.71 (0.46 to 1.11) | 0.13 |
| Hispanic | 0.91 (0.60 to 1.39) | 0.66 | 1.05 (0.68 to 1.62) | 0.83 |
| Other | 1.57 (1.05 to 2.34) | 0.03 | 1.60 (1.07 to 2.39) | 0.02 |
| Unknown | 0.86 (0.63 to 1.15) | 0.30 | 0.90 (0.66 to 1.22) | 0.48 |
| Birth sex | ||||
| Female (ref.) | ||||
| Male | 0.55 (0.46 to 0.67) | <0.0001 | 0.67 (0.54 to 0.83) | 0.0002 |
| Province | ||||
| British Columbia (ref.) | ||||
| Ontario | 0.68 (0.56 to 0.82 ) | <0.0001 | 0.75 (0.61 to 0.94) | 0.01 |
| Quebec | 0.74 (0.58 to 0.95) | 0.02 | 0.89 (0.68 to 1.17) | 0.40 |
| Age at first ARV | 0.98 (0.97 to 0.99) | <0.0001 | 0.98 (0.97 to 0.99) | <0.0001 |
| MSM | 0.59 (0.50 to 0.70) | <0.0001 | — | |
| PWID | 2.40 (2.01 to 2.85) | <0.0001 | 1.39 (1.06 to 1.81) | 0.02 |
| Baseline HIV viral load (Log10 copies/mL) | ||||
| <4 (ref.) | — | |||
| 4–5 | 1.07 (0.83 to 1.39) | 0.60 | ||
| >5 | 1.01 (0.77 to 1.31) | 0.97 | ||
| Baseline CD4 count, cells/mm3 | ||||
| >500 (ref.) | ||||
| ≤200 | 1.31 (0.91 to 1.87) | 0.14 | 1.06 (0.73 to 1.53) | 0.77 |
| 200–349 | 0.99 (0.68 to 1.43) | 0.95 | 0.81 (0.60 to 1.28) | 0.49 |
| 350–499 | 0.6 (0.39 to 0.96) | 0.03 | 0.56 (0.37 to 0.92) | 0.02 |
| Baseline APRI | ||||
| Mild (ref.) | — | |||
| Intermediate | 0.87 (0.79 to 0.96) | 0.004 | ||
| Clinically significant | 0.99 (0.72 to 1.36) | 0.95 | ||
| Advanced fibrosis or cirrhosis | 0.94 (0.77 to 1.14) | 0.52 | ||
Note: Dashes indicate not included in multivariable analysis
HR = Hazard ratio; ARV = Antiretroviral; CI = Confidence interval; ref. = Reference; MSM = Men who have sex with men; PWID = People who use injection drugs; APRI = aspartate aminotransferase-to-platelet ratio index
Discussion
Data evaluating ARV outcomes in HIV–HBV co-infection are scarce. We identified no association between HBV and ARV response as measured by time to HIV virological suppression or rebound. This is consistent with the findings of other studies conducted in North America (28,38–41), Europe (9), and China (42). In contrast, HCV co-infection is well recognized as a negative predictor of viral suppression and risk for rebound. There is little evidence to suggest that viral infection with HBV or HCV itself influences HIV ARV response. A large proportion of people living with HCV face challenges with HIV ARV initiation and adherence. These challenges include substance use, poverty, food insecurity, and mental health challenges. The burden of these challenges is much lower among those living with HBV and explains why viral outcomes differ between HIV–HCV co-infected and HIV-seropositive patients but not between HIV–HBV co-infected and HIV-seropositive patients.
Low baseline CD4 cell counts and high HIV RNA levels at baseline were associated with greater time to achieving virological suppression. This further supports an association between CD4 cell count (43–48) and HIV RNA level (47–50) and ARV efficacy and treatment success. Neither baseline CD4 counts nor HIV viral load was associated with time to virological rebound. Liver fibrosis also did not influence time to virological suppression or rebound.
Non-adherence to ARV is the single strongest factor in virological suppression (51–53) and virological rebound (54,55). Virological rebound has been shown to be associated with progression of fibrosis in HIV–HCV co-infected patients (56). Although we did not measure self-reported adherence, our findings demonstrate that virological outcomes were influenced by various demographic factors that may be related to adherence. Injection drug use was independently associated with decreased virological suppression, which is in keeping with the findings of a previous CANOC cohort analysis (50).
We demonstrated an association between MSM status and improved time to virological suppression and reduced virological rebound. This is consistent with the findings with a UK cohort of 3,258 HIV-infected patients from eight clinics that demonstrated significantly reduced virological rebound and a trend toward improved time to virological suppression among MSM compared with heterosexual men (55). We also found an association between younger age and suboptimal virological outcomes (virological failure and virological rebound), which has been demonstrated in previous studies in which younger age was also independently associated with non-adherence (50,55). Female gender was associated with increased virological rebound. Although this has not been demonstrated with other cohorts, this finding suggests a need for further research on how barriers to adherence faced by women (57–60) may affect HIV infection outcomes. Race influenced the likelihood of maintaining virological suppression. This is a critical reminder of the need for focused resourcing of health care programs to ensure optimal and equitable HIV treatment access and retention in care.
The findings of our study are widely generalizable, given the breadth of the CANOC cohort included in our analysis. Our findings include data from three provinces and eight clinics, ultimately including approximately 20% of all HIV-infected individuals in Canada. An in-depth description of the demographic and clinical characteristics of this same cohort has been published elsewhere (61). Although our dataset captured information for 2000–2014, we believe that that information is still relevant to the Canadian context because the characteristics of people living with HIV and the standard-of-care ARVs used for treatment have not changed markedly in Canada since this time period. However, we acknowledge certain limitations. We did not have access to data such as HBV infection date, measures of ongoing infection or clearance, or whether patients had received HBV treatment at baseline or during the observation period. Therefore, misclassification of patients who previously achieved spontaneous clearance of HBV may have biased our results to the null. Second, the large proportion of missing data resulted in a reduced sample size. This was largely attributable to missing baseline APRI measurements, HBV data, and the exclusion of one site because of possible misclassification of HBV infection. Data from British Columbia were obtained from a provincial registry, whereas data from other provinces were collected from clinical databases. This may have introduced bias and could explain why viral rebound was more likely among British Columbians than among Ontarians. There was a higher proportion of PWID, Indigenous, and female participants among British Columbian patients. Finally, we did not have access to end-of-follow-up CD4 counts and were thus unable to evaluate immunologic recovery with ARV treatment or whether this varied by HBV status.
Our study is the first to describe key HIV- and HBV-related clinical outcomes in a large cohort of ARV-treated, HIV-infected, and HBV–HIV co-infected patients in Canada. Reassuringly, we identified no HBV-specific influence on ARV efficacy.
Acknowledgements:
The authors thank the participants for allowing their information to be a part of the CANOC Collaboration. The CANOC Centre is supported by the Canadian Institutes of Health Research (CIHR) and the CIHR Canadian HIV Trials Network (CTN 242).
Appendix A
Table A1:
Demographic and clinical characteristics of participants by HBV infection status (N = 2,419)
| Characteristics | No. (%)* | p value† | |
|---|---|---|---|
| HBV-negative; n = 2,220 | HBV-positive; n = 199 | ||
| Demographic | |||
| Age, y, median (IQR) | 40 (32.0 to 46.0) | 39 (33.0 to 45.0) | 0.69 |
| Male sex | 1,806 (81) | 164 (82) | 0.71 |
| Ethnicity | 0.11 | ||
| White | 967 (44) | 78 (39) | |
| Black | 408 (18) | 50 (25) | |
| Indigenous | 138 (6) | 10 (5) | |
| Asian | 147 (7) | 20 (10) | |
| Hispanic | 116 (5) | 9 (5) | |
| Other | 82 (4) | 5 (3) | |
| Unknown | 362 (16) | 27 (14) | |
| Hepatitis C coinfection | 520 (23) | 61 (31) | 0.02 |
| Risk factors | |||
| MSM | 998 (45) | 93 (47) | 0.63 |
| PWID | 467 (21) | 55 (28) | 0.03 |
| Clinical | |||
| Baseline CD4 cell count, cells/mm3, median (IQR) | 235 (120 to 360) | 188 (85 to 294) | 0.0002 |
| Baseline AIDS-defining illness‡ | 0.01 | ||
| ≥1 | 446 (20) | 55 (28) | |
| None | 1,774 (80) | 144 (72) | |
| Years on ARV therapy, median (IQR) | 5.01 (2.50 to 8.75) | 5.97 (3.11 to 9.94) | 0.003 |
| Suppressed since FARVDT | 2,040 (92) | 190 (95) | 0.07 |
| Rebound (since first VS) | 481 (24) | 56 (29) | 0.07 |
| Baseline APRI, median (IQR) | 0.37 (0.27 to 0.59) | 0.50 (0.35 to 1.04) | <0.0001 |
| End-of-follow-up APRI, median (IQR) | 0.30 (0.22 to 0.43) | 0.32 (0.23 to 0.56) | 0.03 |
* Unless otherwise indicated
† p values for continuous variables were calculated using X2 or Fisher exact tests; those for continuous variables were calculated using Wilcoxon’s rank-sum tests.
‡ AIDS-defining illness present before or before first naïve ARV date
HBV = Hepatitis B virus; IQR = Interquartile range; MSM = Men who have sex with men; PWID = people who inject drugs; ARV = Antiretroviral; FARVDT = First naïve ARV date; VS = Virological suppression; APRI = Aspartate-aminotransferase-to-platelet ratio index
Funding Statement
CANOC has received funding from the Canadian Institutes of Health Research.
Ethics Approval:
The human subjects activities of the Canadian Observational Cohort (CANOC) have been approved by the Simon Fraser University Research Ethics Board and the University of British Columbia Research Ethics Board as well as the local institutional review boards at each of the participating cohorts.
Informed Consent:
N/A
Funding:
CANOC has received funding from the Canadian Institutes of Health Research.
Disclosures:
SW reports grants, personal fees, non-financial support, and other from Merck, Gilead, GSK, ViiV Healthcare, and Janssen outside the submitted work. MK reports personal fees from ViiV Healthcare, Bristol-Meyers Squibb, AbbVie, and Merck, outside the submitted work. DK reports grants and personal fees from Gilead Sciences, Merck Canada, and ViiV Healthcare and grants from AbbVie Canada, outside the submitted work. RH reports grants from CIHR during the conduct of the study and grants from CIHR outside the submitted work. CLC reports grants and personal fees from Merck, Gilead, AbbVie, and Bristol-Meyers-Squibb, outside the submitted work.
Peer Review:
This manuscript has been peer reviewed.
Animal Studies:
N/A
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