Background: Recent infection testing algorithms (RITAs) are used in public health surveillance to estimate the incidence of recently acquired HIV-1 infection.
Objectives: Our aims were (i) to evaluate the precision of the VITROS® Anti-HIV 1+2 automated antibody avidity assay for qualitative detection of antibodies to HIV 1+2 virus; (ii) to validate the accuracy of an automated guanidine-based antibody avidity assay to discriminate between recent and long standing infections using the VITROS 3600 platform; (iii) to compare this method with BED-CEIA assay; and (iv) to evaluate the occurrence of false recent misclassifications by the VITROS antibody avidity assay in patients with a CD4 count <200 cells/μL and in patients on combination antiretroviral therapy (cART).
Results: The VITROS® antibody avidity assay is highly reproducible. The ROC curve analysis of the accuracy of this assay, optimized for sensitivity and specificity, had an AI cut off of ≤0.51, with sensitivity and specificity values of 86.67% (95% CI: 72.51-94.46) and 86.24% (95% CI: 78.00-91.84), respectively. The agreement between VITROS antibody avidity and BED-CEIA assays was good. Misclassifications of long standing infections as recent infection occurred in 8.2% of patients with CD4 <200 cell/μL and 8.7% in patients on combination antiretroviral therapy.
Conclusions: The VITROS antibody avidity assay is a reliable serological method to detect recent HIV-1 infections and it could be incorporated into a RITA to estimate HIV incidence.
Keywords: Avidity index; False recent rate; Human immunodeficiency virus; Incidence; Incidencia; Infección reciente; Recent infection; Tasa de falsos recientes; Virus de la inmunodeficiencia humana; índice de avidez.
Copyright © 2014 Elsevier España, S.L.U. y Sociedad Española de Enfermedades Infecciosas y Microbiología Clínica. All rights reserved.