Development and Evaluation of a Modified Fourth-Generation Human Immunodeficiency Virus Enzyme Immunoassay for Cross-Sectional Incidence Estimation in Clade B Populations.

BACKGROUND: Accurate methods for cross-sectional incidence estimation are needed for HIV surveillance and prevention research. We developed an avidity assay based on the fourth-generation Genetic Systems HIV Combo Ag/Ab EIA (Bio-Rad Combo assay) and evaluated its performance.

MATERIALS AND METHODS: The Bio-Rad Combo assay was modified incubating samples with and without 0.025 M diethylamine (DEA). The avidity index (AI) was calculated as the ratio of the DEA-treated to untreated result for a specific sample. We analyzed 2,140 samples from 808 individuals from the United States with known duration of HIV infection. The mean duration of recent infection (MDRI) and the false-recent rate (FRR, fraction of samples from individuals known to be infected >2 years misclassified as recent) were calculated for AI cutoffs of 20%-90% for the avidity assay alone and in combination with a viral load assay (VL, limit of detection 400 copies/ml). Factors associated with misclassification of samples collected ≥2 years after infections were also evaluated.

RESULTS: The MDRI for the Bio-Rad Combo Avidity assay ranged from 50 days using an AI cutoff of 20% to 276 days using an AI cutoff of 90%; the FRR ranged from 0% to 9%. When samples with a VL <400 copies/ml were classified as nonrecent, the FRRs were reduced approximately twofold and the MDRI estimates were reduced by ∼20%. An AI cutoff of 50% provided an MDRI of 135 days with an FRR of 2.1%. All samples from elite suppressors had an AI >80%. In adjusted analysis, viral suppression and low CD4 cell count were significantly associated with misclassification among individuals infected >2 years.

CONCLUSIONS: This modified Bio-Rad Combo Avidity assay may be a useful tool for cross-sectional HIV incidence estimation. Further research is needed to evaluate use of this assay in combination with other assays to accurately estimate population-level HIV incidence.