130 likes | 406 Views
High Risk of Liver Fibrosis and Cirrhosis Among HIV/HBV Co-Infected Persons in Rakai, Uganda. Lara Stabinski 1 , Gregory D. Kirk 2 , Steve J Reynolds 1 , Ponsiano Ocama 3 , Francis Bbosa 4 , Melissa Saulynas 2 , V. Kiggundu 4 , Dave Thomas 2 , Ron Gray 2 , Tom Quinn 1 & Chloe Thio 2.
E N D
High Risk of Liver Fibrosis and Cirrhosis Among HIV/HBV Co-Infected Persons in Rakai, Uganda Lara Stabinski1, Gregory D. Kirk2, Steve J Reynolds1, Ponsiano Ocama3, Francis Bbosa4, Melissa Saulynas2, V. Kiggundu4, Dave Thomas2, Ron Gray2, Tom Quinn1 & Chloe Thio2 (1) NIH/LIR Bethesda, Maryland, and the NIH ICER Rakai, Uganda (2) Johns Hopkins University, Baltimore, Maryland (3) Makerere University, Kampala, Uganda, (4) Rakai Health Sciences Program, Rakai, Uganda
Background • Liver disease is a leading cause of death among HIV-infected persons in western cohorts, especially among those co-infected with hepatitis B or C viruses (HBV, HCV) • Data regarding the effects of HIV, hepatitis B and HAART on liver disease in Africa remain extremely sparse • Estimates of hepatotoxicity among HIV-infected persons based on liver enzyme elevation are low in Africa • Evidence that liver enzyme elevation may have substantial limitations as a marker of liver disease in HIV + persons • Biopsy studies to ascertain liver disease are invasive and often difficult to conduct in resource-limited settings
Methods: A non-invasive, cross sectional study in Uganda • Transient elastography(TE) (FibroScan®) used to estimate fibrosis • Population prevalence of HIV/HBV co-infection 5% • Participants • 61 HBV/HIV co-infected Rakai Health Sciences Program (RHSP) ART program • 51HBV mono-infected RHSP population cohort • All included participants had valid TE scans, available HBV DNA
Methods • After consent, participants underwent a structured interview, collection of biological samples, and transient elastography to obtain liver stiffness measurements (LSM) for quantitation of liver fibrosis. • LSM cutoffs (in kilopascals, kPa) • Significant fibrosis (equivalent to Metavir F ≥2, LSM ≥9.3) • Cirrhosis (Metavir F>4, LSM ≥12.3). • Correlates of liver fibrosis were identified using modified Poisson regression to estimate prevalence rate ratios (PRR) with 95% confidence intervals (CI).
Results: Demographics Data represent N (%) or median (interquartile range [IQR]) †p<0.05 HIV/HBV co-infected v. HBV mono-infected
Results: ALT & HBV DNA Levels ‡HBV DNA <100 in 60% of co-infected on HAART vs. 20% in those not yet on HAART (p=0.002)
Prevalence of Liver Disease HIV/HBV Co-infected HBV Mono-infected
Predictors of Significant Fibrosis in Overall Study Population Gender, age, liquor use, and HIV/HBV co-infection
Predictors of Significant Fibrosis in Overall Study Population HAART and nadir CD4 in HIV/HBV co-infected compared to HBV mono-infected ‡ adjusted for age, gender and liquor use
Predictors of Significant Fibrosis in Overall Study Population HBV DNA accounting for HIV/HAART status † Numbers of participants were insufficient to further characterize risks with other categorizations of HBV DNA above 100 IU/ml ‡ adjusted for age, gender and liquor use
Notable Predictors of Liver Disease in HIV/HBV co-infected Population • HAART associated with a 60% reduction in fibrosis; PRR 0.4 (95% CI 0.1-1.0), adjusted for age, gender and nadir CD4 <200 cells/mm3 • Nadir CD4 <200 cells/mm3 not significantly associated with fibrosis; PR 1.7 (95% CI 0.7-4.2) • HBV DNA >100 IU/ml associated with an increased risk of fibrosis; PRR 3.0 (95% CI 1.0-9.3), controlled for age, gender, HAART and nadir CD4 <200
Conclusion • In HIV/HBV co-infected persons, the prevalence of significant fibrosis is double that of HBV mono-infected persons • HAART appears to provide protection against liver fibrosis among HIV-infected persons; early initiation of HAART may be useful in co-infection in resource limited settings • These data underscore the need for effective treatment for HBV in resource-limited settings as HAART is scaled up
Acknowledgements • Rakai Health Sciences Program • Maria Wawer • Ron Gray • Anthony Ndyanabo • Francis Bbosa • Victor Ssempijja • Denis Ssenyondwa • Gladys Namuyaba • Violet Nkalubo • Grace Kigozi • Valerian Kiggundu • Gertrude Nakigozi • Iga Boaz & the RHSP Lab team • Fred Nalugoda • Tom Lutalo • Godfrey Kigozi • Joseph Kagaayi • David Serwadda • Makerere University, Uganda • PonsianoOcama • Kenneth Opio • Emmanuel Seremba • Godfrey Gemagaine • Johns Hopkins University • Gregory D. Kirk • Dave Thomas • Chloe Thio • NIH/LIR & the NIH Uganda ICER • Tom Quinn • Steven J. Reynolds • Oliver Laeyendecker • Andrew Redd • Aaron Tobian • Kevin Newell (SAIC, INC)