Assessment of BED HIV-1 Incidence Assay in Seroconverter Cohorts: Effect of Individuals with Long-Term Infection and Importance of Stable Incidence

Janet M Mcnicholl,Punneeporn Wasinrapee,Bernard M Branson,Michael Martin,Jordan W Tappero,Dale J Hu,Philip A Mock,J Steven Mcdougal,Timothy A Green,Bharat Parekh,Landon Myer

doi:10.1371/journal.pone.0014748

Abstract

BackgroundPerformance of the BED assay in estimating HIV-1 incidence has previously been evaluated by using longitudinal specimens from persons with incident HIV infections, but questions remain about its accuracy. We sought to assess its performance in three longitudinal cohorts from Thailand where HIV-1 CRF01_AE and subtype B′ dominate the epidemic.DesignBED testing was conducted in two longitudinal cohorts with only incident infections (a military conscript cohort and an injection drug user cohort) and in one longitudinal cohort (an HIV-1 vaccine efficacy trial cohort) that also included long-term infections.MethodsIncidence estimates were generated conventionally (based on the number of annual serocoversions) and by using BED test results in the three cohorts. Adjusted incidence was calculated where appropriate.ResultsFor each longitudinal cohort the BED incidence estimates and the conventional incidence estimates were similar when only newly infected persons were tested, whether infected with CRF01_AE or subtype B′. When the analysis included persons with long-term infections (to mimic a true cross-sectional cohort), BED incidence estimates were higher, although not significantly, than the conventional incidence estimates. After adjustment, the BED incidence estimates were closer to the conventional incidence estimates. When the conventional incidence varied over time, as in the early phase of the injection drug user cohort, the difference between the two estimates increased, but not significantly.ConclusionsEvaluation of the performance of incidence assays requires the inclusion of a substantial number of cohort-derived specimens from individuals with long-term HIV infection and, ideally, the use of cohorts in which incidence remained stable. Appropriate adjustments of the BED incidence estimates generate estimates similar to those generated conventionally.

Highlights

The development of serologic assays to detect recent HIV-1 infection and to estimate HIV-1 incidence has generated widespread interest in applying this approach to monitor the HIV epidemic [1,2,3,4] and to identify appropriate populations for efficacy trials
Evaluation of the performance of incidence assays requires the inclusion of a substantial number of cohortderived specimens from individuals with long-term HIV infection and, ideally, the use of cohorts in which incidence remained stable
Incidence has previously been estimated from serial prevalence data and survival assumptions, backcalculation from AIDS case reporting, self-reported serologic history, or passive anonymous/linked surveys [5,6,7,9,10,11], the accurate estimation of incidence has traditionally relied on prospective HIV-1 testing and longitudinal follow-up of people at risk [12,13,14,15]

Summary

Introduction

The development of serologic assays to detect recent HIV-1 infection and to estimate HIV-1 incidence has generated widespread interest in applying this approach to monitor the HIV epidemic [1,2,3,4] and to identify appropriate populations for efficacy trials. Incidence has previously been estimated from serial prevalence data and survival assumptions, backcalculation from AIDS case reporting, self-reported serologic history, or passive anonymous/linked surveys [5,6,7,9,10,11], the accurate estimation of incidence has traditionally relied on prospective HIV-1 testing and longitudinal follow-up of people at risk [12,13,14,15] These cohort studies are time consuming, logistically difficult, expensive, and subject to biases related to enrollment, behavior change, preventive measures, interventions, loss to follow-up and other study effects. A number of assays have been described for the detection of recent HIV-1 infections (reviewed in [3,4]) These assays rely on features of early HIV-1 infection such as the presence of virus before antibody seroconversion (HIV-1 RNA or HIV-1 p24 antigenemia) or the characteristics of antibody titer, proportion, specificity, isotype, or avidity that differ between early and established infection. We sought to assess its performance in three longitudinal cohorts from Thailand where HIV-1 CRF01_AE and subtype B9 dominate the epidemic

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Results

Discussion

Conclusion