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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.

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Presentation on theme: "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."— Presentation transcript:

1 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 High Risk of Liver Fibrosis and Cirrhosis Among HIV/HBV Co-Infected Persons in Rakai, Uganda (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

2 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

3 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

4 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).

5 Results: Demographics HIV/HBV Co-infected HBV Mono-infected Male Gender27 (44)24 (47) †Median Age (IQR)37 (32-57)30 (25-46) Use Liquor12 (20)5 (10) On HAART33 (54)- Median HAART Duration, months (IQR) 21 (11-48)- Median CD4 count (cells/mm 3 )406 (179-1152)- Nadir CD4 <20022(36)- Data represent N (%) or median (interquartile range [IQR]) † p<0.05 HIV/HBV co-infected v. HBV mono-infected

6 HIV/HBV Co-infected HBV Mono-infected Median ALT (IU/L)25 (12-71)24(13-37) ACTG ALT Hepatotoxicity Criteria (%) Grade 0 (0-1.25X ULN) 54 (89)50 (98) Grade1 (1.25-2.5 X ULN) 5 (8)1 (2) Grade 2 (2.5 -5X ULN) 1 (2)- Grade 3 (5-10X ULN) 1 (2)- Grade 4 (>=10X ULN) -- HBV DNA<100 IU/ml (below detection) 35 (57)‡26 (51) ‡ HBV DNA <100 in 60% of co-infected on HAART vs. 20% in those not yet on HAART (p=0.002) Results: ALT & HBV DNA Levels

7 Prevalence of Liver Disease HBV Mono-infected HIV/HBV Co-infected

8 Predictors of Significant Fibrosis in Overall Study Population Gender, age, liquor use, and HIV/HBV co-infection Univariate PRRPMultivariate PRR p Male Gender1.2 (0.6-2.4)0.6221.0 (0.4-2.3)0.995 Age (per year)1.0 (1.0-1.0)0.4481.0 (0.9-1.0)0.095 Use liquor1.9 (0.9-4.0)0.1131.9 (0.7-1.9)0.202 HIV /HBV vs. HBV only2.0 (0.9-4.5)0.0832.3 (1.0-5.0)0.041

9 Predictors of Significant Fibrosis in Overall Study Population HAART and nadir CD4 in HIV/HBV co-infected compared to HBV mono-infected Multivariate ‡ PRR p HBV mono-infected1 (ref)- HIV/HBV, No HAART nadir CD4>=200 2.7 (1.2-6.5)0.022 HIV/HBV, No HAART nadir CD4< 200 5.0 (1.8-13.9)0.002 HIV/HBV, On HAART nadir CD4>=200 1.3 (0.3-5.2)0.746 HIV/HBV, On HAART nadir CD< 200 1.8 (0.6-5.6)0.299 ‡ adjusted for age, gender and liquor use

10 Predictors of Significant Fibrosis in Overall Study Population HBV DNA accounting for HIV/HAART status Multivariate PRR‡ p †HBV DNA >100 IU/ml2.6 (1.0-6.5)0.040 HIV positive, No HAART2.4 (1.0-5.3)0.039 HIV positive on HAART1.8 (0.7-4.7)0.257 † 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

11 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

12 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

13 NIH/LIR & the NIH Uganda ICER –Tom Quinn –Steven J. Reynolds –Oliver Laeyendecker –Andrew Redd –Aaron Tobian –Kevin Newell (SAIC, INC) 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 –Ponsiano Ocama –Kenneth Opio –Emmanuel Seremba –Godfrey Gemagaine Johns Hopkins University –Gregory D. Kirk –Dave Thomas –Chloe Thio


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