Determination of HIV status and identification of incident HIV infections in a large, community-randomized trial: HPTN 071 (PopART)

Susan H Eshleman, Estelle Piwowar-Manning, Ethan A Wilson, Denni Lennon, Jessica M Fogel, Yaw Agyei, Philip A Sullivan, Lei Weng, Ayana Moore, Oliver Laeyendecker, Barry Kosloff, Justin Bwalya, Gerald Maarman, Anneen van Deventer, Sian Floyd, Peter Bock, Helen Ayles, Sarah Fidler, Richard Hayes, Deborah Donnell, HPTN 071 (PopART) Study Team, Susan H Eshleman, Estelle Piwowar-Manning, Ethan A Wilson, Denni Lennon, Jessica M Fogel, Yaw Agyei, Philip A Sullivan, Lei Weng, Ayana Moore, Oliver Laeyendecker, Barry Kosloff, Justin Bwalya, Gerald Maarman, Anneen van Deventer, Sian Floyd, Peter Bock, Helen Ayles, Sarah Fidler, Richard Hayes, Deborah Donnell, HPTN 071 (PopART) Study Team

Abstract

Introduction: The HPTN 071 (PopART) trial evaluated the impact of an HIV combination prevention package that included "universal testing and treatment" on HIV incidence in 21 communities in Zambia and South Africa during 2013-2018. The primary study endpoint was based on the results of laboratory-based HIV testing for> 48,000 participants who were followed for up to three years. This report evaluated the performance of HIV assays and algorithms used to determine HIV status and identify incident HIV infections in HPTN 071, and assessed the impact of errors on HIV incidence estimates.

Methods: HIV status was determined using a streamlined, algorithmic approach. A single HIV screening test was performed at centralized laboratories in Zambia and South Africa (all participants, all visits). Additional testing was performed at the HPTN Laboratory Center using antigen/antibody screening tests, a discriminatory test and an HIV RNA test. This testing was performed to investigate cases with discordant test results and confirm incident HIV infections.

Results: HIV testing identified 978 seroconverter cases. This included 28 cases where the participant had acute HIV infection at the first HIV-positive visit. Investigations of cases with discordant test results identified cases where there was a participant or sample error (mixups). Seroreverter cases (errors where status changed from HIV infected to HIV uninfected, 0.4% of all cases) were excluded from the primary endpoint analysis. Statistical analysis demonstrated that exclusion of those cases improved the accuracy of HIV incidence estimates.

Conclusions: This report demonstrates that the streamlined, algorithmic approach effectively identified HIV infections in this large cluster-randomized trial. Longitudinal HIV testing (all participants, all visits) and quality control testing provided useful data on the frequency of errors and provided more accurate data for HIV incidence estimates.

Trial registration: ClinicalTrials.gov NCT01900977.

Keywords: HIV incidence; HIV testing; South Africa; Zambia; community-randomized; seroconverters.

© 2020 The Authors. Journal of the International AIDS Society published by John Wiley & Sons Ltd on behalf of the International AIDS Society.

Figures

Figure 1
Figure 1
Determination of within‐visit HIV status. Within‐visit HIV status was classified as NEG (HIV uninfected), POS (HIV infectesssd), or INC (inconclusive; HIV status not determined). Results of in‐country testing and quality control (QC) testing at the HPTN Laboratory Center (LC) were compared to identify samples with discordant test results (reactive/non‐reactive). (A) shows the QC testing algorithm and (B) shows the testing algorithm for samples with discordant site/LC test results. HIV assays: ARCHITECT HIV Ag/Ab COMBO Test (Architect test), GS HIV Combo Ag/Ab EIA (BioRad test), BioPlex 2200 HIV Ag‐Ab Assay (BioPlex test), Geenius HIV‐1/2 Supplemental Assay (Geenius test), and Abbott RealTime HIV‐1 Viral Load Assay (HIV RNA test).
Figure 2
Figure 2
Confirmation of seroconverter and seroreverter cases. The figure shows the testing strategy used to confirm seroconverter and seroreverter cases. NEG, negative; POS, positive.

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Source: PubMed

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