Performance of a limiting-antigen avidity enzyme immunoassay for cross-sectional estimation of HIV incidence in the United States

Abstract

Background: A limiting antigen avidity enzyme immunoassay (HIV-1 LAg-Avidity assay) was recently developed for cross-sectional HIV incidence estimation. We evaluated the performance of the LAg-Avidity assay alone and in multi-assay algorithms (MAAs) that included other biomarkers.

Methods and findings: Performance of testing algorithms was evaluated using 2,282 samples from individuals in the United States collected 1 month to >8 years after HIV seroconversion. The capacity of selected testing algorithms to accurately estimate incidence was evaluated in three longitudinal cohorts. When used in a single-assay format, the LAg-Avidity assay classified some individuals infected >5 years as assay positive and failed to provide reliable incidence estimates in cohorts that included individuals with long-term infections. We evaluated >500,000 testing algorithms, that included the LAg-Avidity assay alone and MAAs with other biomarkers (BED capture immunoassay [BED-CEIA], BioRad-Avidity assay, HIV viral load, CD4 cell count), varying the assays and assay cutoffs. We identified an optimized 2-assay MAA that included the LAg-Avidity and BioRad-Avidity assays, and an optimized 4-assay MAA that included those assays, as well as HIV viral load and CD4 cell count. The two optimized MAAs classified all 845 samples from individuals infected >5 years as MAA negative and estimated incidence within a year of sample collection. These two MAAs produced incidence estimates that were consistent with those from longitudinal follow-up of cohorts. A comparison of the laboratory assay costs of the MAAs was also performed, and we found that the costs associated with the optimal two assay MAA were substantially less than with the four assay MAA.

Conclusions: The LAg-Avidity assay did not perform well in a single-assay format, regardless of the assay cutoff. MAAs that include the LAg-Avidity and BioRad-Avidity assays, with or without viral load and CD4 cell count, provide accurate incidence estimates.

Figure 1. Proportion of samples classified as assay positive using the LAg-Avidity assay alone or with HIV viral load, as a function of the duration of HIV infection.

Probability curves were generated by analyzing samples from three cohort studies (see Methods). (A) Probability curves generated using the LAg-Avidity assay with four different assay cutoffs (0.5, 1.0, 1.5, and 3.0 normalized optical density units [OD-n]). Samples were classified as assay positive if the LAg-Avidity assay result was below the assay cutoff. (B) Probability curves generated using the MAAs shown in Figure 2. Samples were classified as MAA positive if results from each of the component assays met the requirements of the MAA.

Figure 2. Optimized multi-assay algorithms (MAAs).

The figure shows two optimized MAAs that include the LAg-Avidity assay. The assays, assay cutoffs, window periods, and shadows are shown for each MAA. The 95% confidence intervals for the window periods and shadows are shown in parentheses. Abbreviations: LAg-Avidity: limiting antigen (LAg) avidity assay; BioRad-Avidity: BioRad-Avidity assay; OD-n: normalized optical density. The following units are used for the component assays: LAg-Avidity assay: OD-n; BioRad-Avidity assay: percentage (avidity index); CD4 cell count: cells/mm³; viral load: copies/mL.