Incorrect identification of recent HIV infection in adults in the United States using a limiting-antigen avidity assay

Abstract

Objectives To evaluate factors associated with misclassification by the limiting-antigen avidity (LAg-avidity) assay among individuals with long-standing HIV infection. Design Samples were obtained from the Multicenter AIDS Cohort Study (MACS), and AIDS Linked to the IntraVenous Experience (ALIVE) cohort (1089 samples from 667 individuals, 595 samples collected 2–4 years and 494 samples collected 4–8 years after HIV seroconversion). Paired samples from both time points were available for 422 (63.3%) of the 667 individuals. Methods Samples were considered to be misclassified if the LAg-Avidity assay result was ≤1.5 normalized optical density (OD-n) units. Results Overall, 4.8% (52/1089) of the samples were misclassified, including 1.8% (16/884, 95% confidence intervals [CI]: 1.09%–3.06%) of samples from individuals with viral loads >400 copies/mL and 1.4% (10/705) of samples from individuals with viral loads >400 copies/mL and CD4 cell counts >200 cells/μl (95% CI: 0.68%–2.60%). Age, race, gender, and mode of HIV acquisition were not associated with misclassification. In an adjusted analysis, viral load <400 copies/mL (adjusted odds ratio [aOR]: 3.72, 95% CI: 1.61–8.57), CD4 cell count <50 cells/μl (aOR: 5.41, 95% CI: 1.86–15.74), and low LAg-Avidity result (≤1.5 OD-n) from the earlier time point (aOR: 5.60, 95% CI: 1.55–20.25) were significantly associated with misclassification. Conclusions The manufacturer of the LAg-Avidity assay recommends excluding individuals from incidence surveys who are receiving antiretroviral therapy, are elite suppressors, or have AIDS (CD4 cell count <200 cells/μl). The results of this study indicate that those exclusions do not remove all sources of assay misclassification among individuals with long-standing HIV infection.

Characteristics of Patients Recently Infected with HIV-1 Non-B Subtypes in France: a Nested Study within the Mandatory Notification System for New HIV Diagnoses

“…The recentness of infection was identified in each sample using the EIA-RI (IDE/V3) assay (20,24). Recent studies have shown that a combination of assays may improve the accuracy of the data (35)(36)(37)(38). Although we did not use a multiassay algorithm, our strategy which corrects the false recentness for any patient known to be at the AIDS stage, a major factor for misclassification, was shown to be relevant at a population level (20,23,24).…”

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

“…Using the same set of specimens from the ALIVE and MACS cohorts, the Bio-Rad Combo Avidity assay had a similar FRR to the LAg-Avidity assay, using a LAg-Avidity assay cutoff of 1.5 OD-n (FRR: 5.8% and 4.8%, respectively). 13 The same factors were associated with misclassification in multivariate analysis for these two assays: viral suppression (VL <400 copies/ml) and low CD4 cell count (<50 cells/mm 3 ). In another report, the third-generation Bio-Rad GS HIV-1/ HIV-2 Plus O EIA was modified for incidence testing using urea as the chaotropic agent, rather than DEA.…”

“…Low viral load (VL) (natural 10 or drug-induced 11 ), low CD4 cell count, 12,13 and HIV subtype D 14 are associated with misclassification by cross-sectional incidence assays. The performance of incidence assays can be characterized by two variables: the mean duration of recent infection (MDRI, the average amount of time individuals are considered recently infected for a given assay or algorithm), and the false recent rate (FRR, the frequency that individuals with long-term infection are misclassified as recently infected).…”

Cross-Sectional HIV Incidence Surveillance: A Benchmarking of Approaches for Estimating the ‘Mean Duration of Recent Infection’

“…Under a general framework for incidence estimation, two parameters are required (Kassanjee, McWalter & Barnighausen 2012): The Mean Duration of Recent Infection (MDRI) -the average time subjects spend 'recently' infected within some time post infection; and the FalseRecent Rate (FRR) -the probability that a subject who is infected for longer than will return a 'recent' result. While the FRR should ideally be zero, it is non-negligible for many currently available TRIs and is understood to vary by time and place (Busch, Pilcher & Mastro 2010;Hallett, Ghys & Barnighausen 2009;Kassanjee, Pilcher & Keating 2014;Le Vu, Pillonel & Semaille 2008;Longosz, Mehta & Kirk 2014;Mastro, Kim & Hallett 2010;Murphy & Parry 2008). The MDRI, typically required to be at least half a year for a TRI to begin to show promise (Incidence Assay Critical Path Working Group 2011), should ideally remain constant so that a once-calibrated TRI would be useful when transferred to other contexts.…”