Hepatitis B virus (HBV) is more common in HIV-infected individuals than in the general population because of similar routes of transmission for viral acquisition.1–3 Current evidence suggests that HIV infection has an adverse impact on HBV-related liver disease progression, with an increase in HBV replication, reduction in the rate of clearance of serum hepatitis B e antigen, and increased risk of cirrhosis, liver-related mortality, and hepatocellular carcinoma at lower CD4+ T-cell counts.1,4–6 Coinfection rates are estimated between 5% and 10%, with up to 40% of immunocompromised patients developing chronic infection.6
Clinical studies before the general availability of highly active antiretroviral therapy (HAART) evaluating the impact of HB on HIV progression have been mixed.7–9 Some studies found no differences in HIV progression between those with and without chronic HB,1,8,10 whereas other studies have shown that chronic HB may negatively impact HIV progression with a significant increased risk of AIDS or death.11–13
Studies evaluating the influence of HIV-HBV coinfection on HIV RNA suppression, immunologic CD4 cell count recovery, and clinical outcomes in individuals on HAART have been limited and conflicting, with several studies finding no difference.14–18 Several studies from HBV-endemic countries have also found no difference on HIV outcomes.19–22 Law et al showed a smaller early increase in CD4 response after HAART initiation (HI), however, this was not sustained.23 Hawkins et al24 showed that coinfected compared with monoinfected individuals had significantly lower CD4+ counts throughout the period of recovery. Other studies have shown that coinfected individuals are less likely to achieve virologic suppression (VS) as compared with HIV-monoinfected individuals.25,26 Recent studies have for the most part failed to show a substantial impact of HBV coinfection on immunologic or HIV virologic responses to antiretroviral therapy (ART).21,24,27 Idoko et al, 22 however, found a lower proportion of HBeAg-positive individuals achieving HIV VS at 24 weeks as compared with HBeAg-negative or HIV-monoinfected individuals, but the findings were not seen at 48 weeks. One recent study evaluating HIV outcomes during the first 3 years of ART found impaired CD4 cell recovery in hepatitis B surface antigen (HsAg)-positive and anti-HBc patients as compared with HBV-uninfected patients.28 Heterogeneity of available data warrants further evaluation of this key question.
Limitations and heterogeneity of results from other studies may be attributed to the small number of individuals analyzed, defining patients with chronic HB sometimes with only 1 positive test for HBsAg, or limited follow-up after HI. We sought to evaluate the impact of HBV infection in HIV-coinfected HAART recipients in a large cohort with known and limited duration of HIV infection, free access to health care, racial diversity, minimal injection drug use (IDU), and long-term follow-up.
Study Participants and Definitions
The US Military HIV Natural History Study (NHS) is a prospective multicenter continuous enrollment observational cohort of HIV-infected active duty military personnel and other beneficiaries (spouses, adult dependents, and retired military personnel), with over 5400 HIV-infected participants from the Army, Navy/Marines, and Air Force enrolled since 1986. Participants are followed at 5 military medical centers in the United States. Demographics, medical and medication histories, and standard laboratory studies are collected biannually as previously described.13 In the NHS, dates of death are collected through the review of death certificates and medical records by study staff, as well as by searching the Social Security Death Index and National Death Index databases annually. Although not captured in the NHS database, IDU has been reported to be very rare in this cohort.29 All NHS participants provided informed consent, and approval for this research was obtained from the institutional review board at each participating site.
NHS participants with a documented HIV diagnosis who ever received HAART and had a categorizable HB status were considered for these analyses. HAART was defined according to guidelines from the DHHS/Kaiser Panel and was defined as: (1) 2 or more nucleoside reverse transcriptase inhibitors (NRTIs) in combination with at least 1 protease inhibitor (PI) or 1 nonnucleoside reverse transcriptase inhibitor (NNRTI) (88% of observations classified as HAART); (2) 1 NRTI in combination with at least 1 PI and at least 1 NNRTI (5%); (3) a regimen containing ritonavir and saquinavir in combination with 1 NRTI and no NNRTIs (1%); and (4) an abacavir or tenofovir containing regimen of 3 or more NRTIs in the absence of both PIs and NNRTIs (6%), except for the 3-NRTI regimens consisting of abacavir + tenofovir + lamivudine or didanosine + tenofovir + lamivudine.30 HBV-active HAART was defined as HAART containing lamivudine, emtricitabine, or tenofovir disoproxil fumarate.
Screening for HB was performed in accordance with clinical standards of care and practice guidelines at the time and included HBsAg, total antibody to hepatitis B core antigen (HBcAb), and hepatitis B surface antibody. Those whose HB status could not be categorized were excluded from these analyses. The remaining participants were classified into one of 4 mutually exclusive groups determined by HB status in the HAART initiation window (HIW, −396 to +90 days from HI), defined as follows: (1) chronic HB: HBsAg reactivity on 2 or more separate occasions at least 6 months apart with at least 1 positive HBsAg within the HIW or 1 positive HBsAg before HI and one after HI; (2) isolated HBcAb: HBcAb reactivity on 2 or more occasions without any other reactive HBV marker; (3) resolved HB: a panel with markers reactive for HBcAb and hepatitis B surface antibody concurrently closest to HI, or before and after the HIW and HBsAg negative; or (4) HB negative: both HBsAg and HBcAb negative in the HIW or after the HIW with no previous positive panels.
Hepatitis C virus (HCV) infection was defined as having at least 1 positive HCV antibody test before or in the HIW without any negative HCV antibody thereafter. For those not classified as positive for HCV infection, a negative HCV antibody anytime after HI was used to classify individuals as HCV antibody negative at HI. An HIV seroconverter was defined as having a documented negative and positive HIV date.
HIV VS after HI was defined as having at least 1 viral load (VL) assay <400 copies per milliliter within 6 months or 1 year after HI. Among subjects having ever suppressed VL, virologic failure (VF) was defined as having 2 consecutive VL assays ≥400 copies per milliliter.
AIDS-defining illnesses were defined using the 1993 Centers for Disease Control and Prevention classification excluding an isolated CD4 count <200 cells per microliter.31 Individuals whose visit occurred after HI were included in this model.
Participants were followed from the time of HI for the composite end point of an AIDS-defining illness or death from any cause through 18 months after the last study visit. For those without an event, data were censored 18 months after the last study visit.
The 4 groups, defined by baseline HB status, were summarized with descriptive statistics. All continuous covariates were tested for normality using Shapiro–Wilks; covariates with a P value <0.05 were considered not normally distributed. All covariates were nonnormal, so medians were compared using Kruskal–Wallis test for continuous data. Categorical data were evaluated with either Fisher exact test when the cell contained small counts or the χ2 test.
Logistic regression was used to estimate the adjusted odds ratios for ever achieving VS within 6 months and 1 year of HI. Subjects were excluded from analyses if no VL assays within either 6 months or 1 year of HI or any model covariates were missing. Sensitivity analyses were performed on all models to assess the effect of missing data on outcomes using multiple imputation with predictive mean matching for missing data.32 Backwards selection methods, based on significance levels in the full mode (P < 0.1) and other clinically relevant covariates, were later added. The final adjusted models (within 6 and 12 months of HI) were adjusted for age at HI, gender, race, era of HI, HCV status, VL and CD4 cell count at HI, ART use before HI, and number of VL assays during 6 or 12 months of HI. Odds ratios (ORs) are given with 95% confidence intervals (CIs). A Cox proportional hazard model was used to estimate the adjusted hazard rate of VF. Only those who ever achieved VS were included. Time to VF was defined as the number of years from the first suppressed VL after HI to the first VF after HI. Backward stepwise selection was used to choose statistically significant covariates then other clinically relevant covariates were added to the model. Multiple imputations were used as a sensitivity analysis to assess the effect of missing data on parameter estimation. The final adjusted model was adjusted for age at HI, race, gender, HCV status at HI, year of HI, HIV VL at HI, CD4 count at HI, ART before HI, AIDS before HI, and years from HI to VS. Hazard ratios (HRs) are given with 95% CIs.
To quantify the effect of covariates at HI on the rate of increase in CD4 cell count, analysis of immunologic outcomes was evaluated using linear spline mixed models to account for within-subject repeated CD4 measures and to assess the effect of HB status and other factors on CD4 trajectories. Knots for the linear spline model were selected by inspection of locally weighted scatter plot smoothing (LOWESS) curves. Backwards selection methods were used to select covariates. Mean rates of increase in CD4 were allowed to differ by CD4 at HI, HB status at HI, and the era of HI. P values <0.05 were considered statistically significant. Given the Q-Q plot comparing the standardized residuals to theoretical normal quantiles showed a lack of fit in the tails, a regression technique using the multivariate t distribution and bootstrapping was used as a sensitivity analysis with respect to normality and outlier to improve model fit and compare parameters with the standard mixed model approach. R programming 2.13.2 was used for all other analyses.33
The number of events, person-years (PY) at risk, and unadjusted rates per 100 PY were calculated for the 4 baseline groups; proportional HRs were estimated using Cox regression models.
Of 5403 HIV-positive participants enrolled in the NHS with a documented HIV-positive date, 2797 were ever on HAART (after 1996), 2536 (81%) had HBV testing results available to determine HB status in the HIW and were included in these analyses. Individuals whose HB status were not classified differed from those who were in that they were older at HAART start, had a greater percentage of HCV seropositivity, had a longer duration of HIV before HI, were more often diagnosed in the pre-HAART era and had lower CD4 nadirs (data not shown). HB status at HI was classified as HB negative (n = 1505; 66%), resolved HB (n = 518; 23%), isolated HBcAb (n = 139; 6%), or chronic HB (n = 131; 6%). Characteristics at the time of HI by HB status are shown in Table 1. Age at HIV diagnosis and HI [overall median, 29 years; interquartile range (IQR), 24–35 and 33 years; IQR, 28–39, respectively] were significantly different among the 4 HB groups, with HB-negative individuals diagnosed with HIV in the later calendar years, initiating HAART at the youngest age, having the lowest number of individuals with previous AIDS, having the least number with previous ART use, and having the highest median CD4 count at HI. Isolated core subjects had the highest proportion of HCV (15%). The chronic HB group had the lowest median CD4 at HI (median, 278; IQR, 146–410), and highest alanine aminotransferase values (median, 59 IU/L; IQR, 33–102). HIV RNA levels at the time of HI were available for 2005 (87%) participants and were similar among the groups (median, 4.5 log10 copies/mL; IQR, 3.8–5). Median follow-up was 9.2 years; IQR, 4.4–16. Of all subjects, 93% received HBV-active HAART regimens at HI. Of individuals initiating HAART between 1996 and 1999, the majority were on unboosted PIs (78%); however, from 2000 to 2012, 68% were on an NNRTI regimen (data not shown).
HIV Virologic Suppression
In unadjusted analyses by HB status, HB status was associated with HIV VS in the first 6 months and 1 year (data not shown). Within 6 months, VS rates for 1015 subjects were 53% overall, with HB negative, chronic HB, isolate core, and resolved HB achieving rates of 58%, 35%, 44%, and 45%, respectively, P < 0.001. Within 1 year, VS rates for 1250 subjects were 59% overall, with HB negative, chronic HB, isolate core, and resolved HB achieving rates of 65%, 40%, 53%, and 47%, respectively, P < 0.001. Table 2 presents the adjusted OR for achieving HIV VS within 6 months and 1 year of HI for the 4 HB groups. The number of subjects included in models 1 (6 months) and 2 (12 months) were 1922 and 2130 subjects, respectively. The adjusted OR for achieving VS was not significantly different by HB status, whereas age, year of HI, VL at HI, previous ART, and HIV VL assay count were significantly associated with the OR for achieving VS within 6 months and 12 months of HI, and African American race was significantly associated with achieving VS within 12 months of HI. HB status at HI, gender, HCV status at HI, CD4 count at HI, and AIDS before HI were not predictive of VS.
In an unadjusted model, over 5533 years of follow-up, there were 863 events of VF. The rate of VF was 15.6 events/100 PY; 95% CI: 14.6 to 16.7 overall. VF by HBV status was higher in the chronic HB status group (23.5 events/100 PY; 95% CI: 17.9 to 30.3) over the years of follow-up as compared with the isolated, resolved, and HB-negative status groups (18.8 events per 100 PY; 95% CI: 14.4 to 24, 18.5 events per 100 PY; 95% CI: 16.3 to 21, and 13.7 events per 100 PY; 95% CI: 12.6 to 15, respectively) (data not shown). Predictors of VF in adjusted analyses, however, did not show a significant difference by HB status, suggesting the association was confounded by other factors (Table 3). Younger age, African American race, HI in the period 1996–1999, and previous ART were significantly associated with an increased risk of VF. Higher VL at HI showed a trend toward increased risk of VF (HR = 1.09; 95% CI: 1.00 to 1.18).
Unadjusted trends in CD4 reconstitution by HBV status are shown in Figure 1. CD4 slope did not significantly differ by HB status during the first 6 months after HI (chronic: P = 0.838; isolated core: P = 0.270; resolved HB: P = 0.239) (Table 4). The rate increase in CD4 cell count in chronic HB compared with HB negatives during the period between 6 months and 4 years after HI was also not significantly different (chronic: P = 0.069; isolated core: P= 0.289; resolved HB: P = 0.099). A significantly greater rate increase in CD4 cell count in chronic HB compared with HB negative, however, was seen during the period from 4 to 12 years after HI (chronic: P < 0.001; isolated core: P= 0.841; resolved HB: P = 0.071), after adjustment for age at HI, gender, race, HCV status at HI, AIDS before HI, CD4 cell count at HI, HIV VL at HI, ART before HI, and year of HI.
Deaths and AIDS-Defining Illnesses
During 14,458 PY of follow-up (range, January 1996 to February 2010), 269 participants experienced an AIDS event or death after HI. AIDS events occurred at a rate of 1.86 per 100 PY; 95% CI: 1.64 to 2.10. In multivariate analysis, chronic HB status and resolved HB status were significantly associated with an increased risk of AIDS or death (chronic HB; HR = 1.68; 95% CI: 1.05 to 2.68, isolated HB; HR = 1.51; 95% CI: 0.93 to 2.44, resolved HB; HR = 1.61; 95% CI: 1.15 to 2.25). The HR comparing individuals with isolated HBcAb to those who were HB negative was not significant (data not shown). Other covariates that were associated with a significantly increased risk of an AIDS or death included subjects with a positive HCV status (HR = 1.99; 95% CI: 11.26 to 3.16), CD4 cell count at HI <200 (HR 3.70; 95% CI: 2.49 to 5.50) and 200–350 (HR = 1.35; 95% CI: 0.85 to 2.05), as compared with a CD4 cell count ≥350, and previous ART (HR = 2.06; 95% CI: 1.39 to 3.07). All models were stratified by AIDS before HI. The interaction between HBV and HCV was not significant.
We evaluated HIV outcomes in HBV-coinfected HAART recipients and found that in agreement with other studies, HB status did not have a significant impact on HIV virologic outcomes. To adjust for the disparity in ART between HBV-infected and HBV-negative groups, we used era of HI in all models and ran sensitivity analyses (data not shown) to adjust for regimen potency (unboosted PI vs. boosted PI, 3 NRTI, and NNRTI-based regimens, excluding PI + NNRTI + NRTI). Expectedly, regimen potency was significant, whereas P values and ORs for HBV status did not greatly change, indicating that while disparity in ART regimen between HBV groups affect virologic and immunologic outcomes, it is accurately adjusted for in our analysis. Older age, HI in the era 2000–2010, lower HIV RNA, and the absence of ART use before HI were associated with improved odds of achieving VS in our study in agreement with findings observed from other studies.14,18 Of interest, our cohort demonstrated 53% of subjects achieving HIV VS at 6 months and 59% at 12 months, which is lower than a recent study evaluating patients in the Swiss HIV Cohort Study (85.3%–90.1% at 12 months), as well as previously published results from NHS participants starting HAART after 2000 (81% VS at 12 months).28,34 This likely reflects differences in ARV potency and treatment practices and previous mono- and dual-NRTI exposure. Although HB status was not significantly associated with VS, VL at HI was significantly associated with the odds of achieving VS within 6 months and 12 months of HI. We also found no difference in time to VF by HB status at HI.
Previous studies evaluating T-cell recovery in HBV infection have been mixed, with several showing no difference or early lower median CD4 cell count gains in HIV-HBV coinfection with no differences by 48 weeks.14,16,23,24 The Swiss HIV Cohort Study, however, which evaluated CD4 count recovery over a 36-month period, showed impaired CD4 recovery in patients with both HBsAg and anti-HBc alone suggesting direct impairment of immunologic recovery in HBV-coinfected patients.28 Results from our study show that HB status may be associated with CD4 cell count reconstitution post-HI, as seen with a trend for slower CD4 cell count trajectories in individuals with chronic HB and resolved HB between 6 months and 4 years after HI. However, any trend in impaired immunologic recovery was not sustained as we observed a significantly greater rate increase in CD4 cell count in chronic HB compared with HB-negative patients during the period from 4 to 12 years after HI (P < 0.001). Our study, with long median times of patient observation, is the first to demonstrate significantly greater long-term CD4 cell count gains in chronic HB individuals. The explanation for this difference is not clear, but one possibility is a positive impact on CD4 regenerative capacity in individuals with chronic HB when placed on HAART as compared with ART regimens that were not as robust as HAART. We also reviewed ART regimen changes over follow-up. Initially, only 11% (Table 1) of the CHB group was on dual HBV-active therapy; however, we found that 47% of the CHB initially on non–dual HBV-active ART, were switched to dual HBV-active ART at a median of 7.2 years after HI (data not shown). This may account for the significant CD4 cell count increase in the CHB group to similar levels as the other groups. Despite individuals with CHB having lower CD4 cell counts and older age at HI, which would negatively impact CD4 cell count rise, long-term increases were observed. Similar to other studies, we show that individuals initiating HAART in the later years have greater CD4 slope changes in CD4 cell count as compared with individuals who started HAART in the early years of HAART availability, with VL not affecting CD4 trajectory.35 Factors associated with poorer immunologic outcomes in our study, such as AIDS before HI, previous ART, lower CD4 count at HI are well-established determinants of HIV disease progression and risk of death.36
Similar to other studies, we not only found an increase in AIDS events or death in patients with chronic HB but also found an increased risk in resolved HB compared with HB-negative individuals, which has not been previously described. These findings in individuals with resolved HB were not expected, given there were no significant differences in virologic and immunologic responses to ART over time between individuals with resolved HB as compared with individuals who were HB negative.
Study limitations include the relatively small number of individuals with chronic HB and isolated HB in this cohort in comparison with individuals with resolved and HB-negative status. The population whose HB status was not classified differed from those who were classified in that they were more often diagnosed in the pre-HAART era, had lower CD4 nadirs, were older at HAART start, had a greater percentage of HCV seropositivity, and had a longer duration of HIV diagnosis before HI. This difference would likely contribute to worse outcomes in individuals not HB classified, therefore, HB-unclassified individuals were excluded from analyses. Whether the CD4 cell count recovery findings observed in our study reflect survivor bias in individuals with chronic HB is possible, however, our cohort had significantly longer follow-up for the chronic HB compared with other groups. The interpretation of data regarding HCV status is limited as confirmatory HCV RNA results were unavailable for the majority of those who were anti-HCV positive. The quantification of the contribution of liver-related causes to death is not possible in our cohort. Findings from this study may be relevant to groups similar to our cohort and may not be applicable to groups with high rates of IDU, women, or those with limited access to care.
The NHS cohort provides a unique opportunity to understand the impact of HBV coinfection on HIV outcomes in HAART recipients. The low use of injection drugs in this cohort, as well as open access to medical care, vaccinations, and medications in the military health system also help reduce potential confounding. Additionally, the long median ART duration and PY of observation in our cohort allow for the observation of potential associations otherwise not seen in other studies. However, some of the cohort's features may limit external generalizability. In addition, given the limited number of women in our cohort, study findings may not be generalizable to women. Therefore, in our cohort, and likely for other HIV-infected persons with similar characteristics, HB status does not seem to be associated with worse immunologic or virologic HIV outcomes.
In conclusion, our study adds further insight into the understanding of the complex interactions between HBV and HIV infection, and demonstrates the possible association between HB status at the time of HI and subsequent HIV immunologic and clinical outcomes. Further evaluation of the impact of HBV on cellular immunity and clinical outcomes should be prioritized. Findings from this study add further support to the recommendations to expand HBV screening to potentially minimize the morbidity and mortality associated with HIV/HBV coinfection.
The investigators thank their patients for their enormous contributions over the years. In addition to the authors listed above, the IDCRP HIV Working Group includes Susan Banks, RN, Nancy Crum-Cianflone, MD, MPH, Cathy Decker, MD, Conner Eggleston, LTC Tomas Ferguson, MD, COL Susan Fraser, MD, MAJ Joshua Hartzell, MD, MAJ Joshua Hawley, MD, LTC Gunther Hsue, MD, Arthur Johnson, MD, COL Mark Kortepeter, MD, MPH, Tahaniyat Lalani, MD, Robbin Lockhart, MS, Scott Merritt, LTC Robert O'Connell, MD, Maj Jason Okulicz, MD, Michael Polis, MD, John Powers, MD, MAJ Roseanne Ressner, MD, COL (ret) Edmund Tramont, MD, LT Tyler Warkentien, MD, CDR Timothy Whitman, MD, and COL Michael Zapor, MD.
1. Gilson RJC, Hawkins AE, Beecham MR, et al.. Interactions between HIV and hepatitis B virus in homosexual men: effects on the natural history of infection. AIDS. 1997;11:597–606.
2. Kellerman SE, Hanson DL, McNaghten AD, et al.. Prevalence of chronic hepatitis B and incidence of acute hepatitis B infection in human immunodeficiency virus-infected subjects. J Infect Dis. 2003;188:571–577.
3. Weber R, Sabin CA, Friis-Moller N, et al.. Liver-related deaths in persons infected with the human immunodeficiency virus: the D:A:D study. Arch Intern Med. 2006;166:1632–1641.
4. Mathews G, Bhagani S. The epidemiology and natural history of HIV/HBV and HCV co-infections. J HIV Ther. 2003;8:77–84.
5. Thio CL, Seaberg EC, Skolasky R Jr, et al.. HIV-1, hepatitis B virus, and risk of liver-related mortality in the Multicenter Cohort Study (MACS). Lancet. 2002;360:1921–1926.
6. Thio CL. Hepatitis B and human immunodeficiency virus coinfection. Hepatology. 2009;49(5 suppl):S138–S145.
7. Eskild A, Magnus P, Petersen G, et al.. Hepatitis B antibodies in HIV-infected homosexual men are associated with more rapid progression to AIDS. AIDS. 1992;6:571–574.
8. Scharschmidt BF, Held MJ, Hollander HH, et al.. Hepatitis B in patients with HIV infection: relationship to AIDS and patient survival. Ann Intern Med. 1992;117:837–838.
9. Sinicco A, Raiteri R, Sciandra M, et al.. Coinfection and superinfection of hepatitis B virus in patients infected with human immunodeficiency virus: no evidence of faster progression to AIDS. Scand J Infect Dis. 1997;29:111–115.
10. Solomon RE, Van Raden M, Kaslow RA, et al.. Association of hepatitis B surface antigen and core antibody with acquisition and manifestations of human immunodeficiency virus type 1 HIV-1infection. Am J Public Health. 1990;80:1475–1478.
11. Greenspan D, Greenspan JS, Overby G, et al.. Risk factors for rapid progression from hairy leukoplakia to AIDS: a nested case-control study. J Acquir Immune Defic Syndr. 1991;4:652–658.
12. Ockenga J, Tillmann HL, Trautwein C, et al.. Hepatitis B and C in HIV-infected patients. Prevalence and prognostic value. J Hepatol. 1997;27:18–24.
13. Chun HM, Fieberg AM, Hullsiek KH, et al.. The epidemiology of hepatitis B virus infection in a U.S. cohort of HIV-infected individuals during the last 20 years. Clin Infect Dis. 2010;50:426–436.
14. de Luca A, Bugarinin R, Lepri AC, et al.. Coinfection with hepatitis viruses and outcome of initial antiretroviral regimens in previously naïve HIV-infected subjects. Arch Intern Med. 2002;162:2125–2132.
15. Omland N, Skinhøj P, Laursen A, et al.. Impact of hepatitis B virus co-infection on response to highly active antiretroviral treatment and outcome in HIV-infected individuals: a nationwide cohort study. HIV Med. 2008;9:300–306.
16. Konopnicki D, Mocroft A, De WS, et al.. Hepatitis B and HIV: prevalence, AIDS progression, response to highly active antiretroviral therapy and increased mortality in the EuroSIDA cohort. AIDS. 2005;19:593–601.
17. Hoffmann CJ, Seaberg EC, Young S, et al.. Hepatitis B and long-term HIV outcomes in coinfected HAART recipients. AIDS. 2009;23:1881–1889.
18. Lincoln D, Petoumenos K, Dore GJ. HIV/HBV and HIV/HCV coinfection, and outcomes following highly active antiretroviral therapy. HIV Med. 2003;4:241–249.
19. Hoffmann CJ, Charalambous S, Martin DJ, et al.. Hepatitis B virus infection and response to antiretroviral therapy (ART) in a South African ART program. Clin Infect Dis. 2008;47:1479–1485.
20. lsa SE, Gwamzhi LN, Akolo C, et al.. A prospective cohort study of immunologic and virologic outcomes in patients with HIV/AIDS and hepatitis virus coinfection in Jos, Nigeria. Niger J Med. 2010;19:279–285.
21. Moore E, Beadsworth MB, Chaponda M, et al.. Favourable one-year ART outcomes in adult Malawians with hepatitis B and C co-infection. J Infect. 2010;61:155–163.
22. Idoko J, Meloni S, Muazu, et al.. Impact of hepatitis B virus infection on HIV response to antiretroviral therapy in Nigeria. Clin Infect Dis. 2009;49:1268–1273.
23. Law WP, Duncombe CJ, Mahanontharit A, et al.. Impact of viral hepatitis coinfection on response to antiretroviral therapy and HIV disease progression in the HIV-NAT cohort. AIDS. 2004;18:1169–1177.
24. Hawkins C, Christian B, Ye J, et al.. Prevalence of hepatitis B coinfection and response to antiretroviral therapy among HIV-infected patients in urban Tanzania. AIDS. 2013;27:919–927.
25. Sheng WH, Chen MY, Hsieh SM, et al.. Impact of chronic hepatitis B virus (HBV) infection on outcomes of patients infected with HIV in an area where HBV infection is hyperendemic. Clin Infect Dis. 2004;38:1471–1477.
26. Sheng WH, Kao JH, Chen PJ, et al.. Evaluation of hepatitis B serological markers in HIV-infected patients receiving highly active antiretroviral therapy. Clin Infect Dis. 2007;45:1221–1229.
27. Thio CL, Smeaton L, Saulynas M, et al.. Characterization of HIV-HBV coinfection in a multinational HIV-infected cohort. AIDS. 2013;27:191–201.
28. Wandeler G, Gsponer T, Bihl F, et al.. Hepatitis B virus infection is associated with impaired immunological recovery during antiretroviral therapy in the Swiss HIV cohort study. J Infect Dis. 2013;208:1454–1458.
29. Brodine SK, Starkey MJ, Shaffer RA, et al.. Diverse HIV-1 subtypes and clinical, laboratory and behavioral factors in a recently infected US military cohort. AIDS. 2003;17:2521–2527.
31. Centers for Disease Control and Prevention. 1993 revised classification system for HIV infection and expanded surveillance case definition for AIDS among adolescents and adults. MMWR. 1992;41:No-RR17. Available at: http://www.cdc.gov/mmwr/preview/mmwrhtml/00018871.htm
. Accessed January 4, 2008.
32. Harrell FE Jr. Regression Modeling Strategies with Applications to Linear Models, L2ogistic Regression, and Survival Analysis. New York: Springer; 2001.
33. R Development Core Team. R: A Language and Environment for Statistical Computing. Vienna, Austria: R Foundation for Statistical Computing; 2010. Available at: http://www.R-project.org
. Accessed November 1, 2011.
34. Marconi VC, Grandits GA, Weintrob AC, et al.. Outcomes of highly active antiretroviral therapy in the context of universal access to healthcare: the U.S. Military HIV Natural History Study. AIDS Res Ther. 2010;7:14.
35. Lifson AR, Krantz EM, Eberly LE, et al.. Long-term CD4+ lymphocyte response following HAART initiation in a U.S. Military prospective cohort. AIDS Res Ther. 2011;8:2.
36. SMART Study Group, El-Sadr WM, Grund B, et al.. Risk for opportunistic disease and death after reinitiating continuous antiretroviral therapy in patients with HIV previously receiving episodic therapy: a randomized trial. Ann Intern Med. 2008;149:289–299.
Keywords:© 2014 by Lippincott Williams & Wilkins
hepatitis B virus; chronic hepatitis B; HIV; highly active antiretroviral therapy