Absence of Hepatitis Delta Infection in a Large Rural HIV Cohort in Tanzania

OBJECTIVES The epidemiological and clinical determinants of hepatitis delta virus (HDV) infection in sub-Saharan Africa are ill-defined. We determined the prevalence of HDV infection in HIV/hepatitis B virus (HBV)-co-infected individuals in rural Tanzania. DESIGN AND METHODS We screened all hepatitis B virus (HBV)-infected adults under active follow-up in the Kilombero and Ulanga Antiretroviral Cohort (KIULARCO) for anti-HDV antibodies. In positive samples, we performed a second serological test and nucleic acid amplification. Demographic and clinical characteristics at initiation of antiretroviral therapy (ART) were compared between anti-HDV-negative and positive patients. RESULTS Among 222 HIV/HBV-coinfected patients on ART, 219 (98.6%) had a stored serum sample available and were included. Median age was 37 years, 55% were female, 46% had WHO stage III/IV HIV disease and median CD4 count was 179 cells/μL. The prevalence of anti-HDV positivity was 5.0% (95% confidence interval 2.8%-8.9%). There was no significant predictor of anti-HDV positivity. HDV could not be amplified in any of the anti-HDV-positive patients and the second serological test was negative in all of them. CONCLUSIONS We found no confirmed case of HDV infection among over 200 HIV/HBV-co-infected patients in Tanzania. As false-positive serology results are common, screening results should be confirmed with a second test.

Risk charts to guide targeted HIV-1 viral load monitoring of ART: development and validation in patients from resource-limited settings.

BACKGROUND HIV-1 RNA viral load (VL) testing is recommended to monitor antiretroviral therapy (ART) but not available in many resource-limited settings. We developed and validated CD4-based risk charts to guide targeted VL testing. METHODS We modeled the probability of virologic failure up to 5 years of ART based on current and baseline CD4 counts, developed decision rules for targeted VL testing of 10%, 20% or 40% of patients in seven cohorts of patients starting ART in South Africa, and plotted cut-offs for VL testing on colour-coded risk charts. We assessed the accuracy of risk chart-guided VL testing to detect virologic failure in validation cohorts from South Africa, Zambia and the Asia-Pacific. FINDINGS 31,450 adult patients were included in the derivation and 25,294 patients in the validation cohorts. Positive predictive values increased with the percentage of patients tested: from 79% (10% tested) to 98% (40% tested) in the South African, from 64% to 93% in the Zambian and from 73% to 96% in the Asia-Pacific cohorts. Corresponding increases in sensitivity were from 35% to 68% in South Africa, from 55% to 82% in Zambia and from 37% to 71% in Asia-Pacific. The area under the receiver-operating curve increased from 0.75 to 0.91 in South Africa, from 0.76 to 0.91 in Zambia and from 0.77 to 0.92 in Asia Pacific. INTERPRETATION CD4-based risk charts with optimal cut-offs for targeted VL testing may be useful to monitor ART in settings where VL capacity is limited.

Implementation and Operational Research: Risk Charts to Guide Targeted HIV-1 Viral Load Monitoring of ART: Development and Validation in Patients From Resource-Limited Settings.

BACKGROUND HIV-1 RNA viral load (VL) testing is recommended to monitor antiretroviral therapy (ART) but not available in many resource-limited settings. We developed and validated CD4-based risk charts to guide targeted VL testing. METHODS We modeled the probability of virologic failure up to 5 years of ART based on current and baseline CD4 counts, developed decision rules for targeted VL testing of 10%, 20%, or 40% of patients in 7 cohorts of patients starting ART in South Africa, and plotted cutoffs for VL testing on colour-coded risk charts. We assessed the accuracy of risk chart-guided VL testing to detect virologic failure in validation cohorts from South Africa, Zambia, and the Asia-Pacific. RESULTS In total, 31,450 adult patients were included in the derivation and 25,294 patients in the validation cohorts. Positive predictive values increased with the percentage of patients tested: from 79% (10% tested) to 98% (40% tested) in the South African cohort, from 64% to 93% in the Zambian cohort, and from 73% to 96% in the Asia-Pacific cohort. Corresponding increases in sensitivity were from 35% to 68% in South Africa, from 55% to 82% in Zambia, and from 37% to 71% in Asia-Pacific. The area under the receiver operating curve increased from 0.75 to 0.91 in South Africa, from 0.76 to 0.91 in Zambia, and from 0.77 to 0.92 in Asia-Pacific. CONCLUSIONS CD4-based risk charts with optimal cutoffs for targeted VL testing maybe useful to monitor ART in settings where VL capacity is limited.