AEGiS-14IAC: HIV antibody avidity index: a new tool for estimating HIV incidence.

14th International AIDS Conference

Barcelona, Spain - July 7-12, 2002

HIV antibody avidity index: a new tool for estimating HIV incidence.

Int Conf AIDS 2002 Jul 7-12; 14:(abstract no. MoOrC1041)

Suligoi B, Massi M, Sciandra M, Sora FD, Galli C, Pezzotti P, Rezza G
Istituto Superiore di Sanita, Rome, Italy

BACKGROUND: To assess changes in the HIV epidemic, incidence estimates are essential, yet they are best obtained through longitudinal studies, which are complicated and time-consuming. We evaluated a new procedure for identifying recent infections based on an automated enzyme immunoassay.

METHODS: We conducted a longitudinal retrospective study using serum samples from 47 HIV-positive persons for whom the seroconversion date could be accurately estimated. Each sample was divided into two aliquots: one diluted with phosphate-buffered saline (PBS) and the other with 1M guanidine (G). We assayed the aliquots with the automated AxSYM HIV1/2gO test (Abbott) without modifying the manufacturer's protocol. We then calculated the ratio of the sample/cutoff (S/CO) value for the G aliquot to that of the PBS aliquot, which provided the avidity index (AI). The rationale behind the use of the AI is that early antibodies are less likely to link with antigens when G is present, giving an AI of <1 in the initial period after seroconversion.

RESULTS: We analysed 216 serum samples, collected from 4 days to 10.3 years after seroconversion; 34 samples were collected within 6 months of seroconversion (recent seroconversions), 30 samples within 7-12 months, and 152 later than 12 months. The median AI values, by time from seroconversion, were: 0.66 (within 6 months); 0.98 (7-12 months); and 1.02 (more than 12 months). For an AI of <0.9, the sensitivity and specificity of the test to identify recent seroconversions were 88% and 76.4%, respectively. An AI of <0.6 gave a positive predictive value of 82% and a negative predictive value of 88% for samples collected within 6 months of seroconversion.

CONCLUSIONS: The low AI observed in the first 6 months after seroconversion shows that this test, which is automated and easy to perform, can identify recent HIV infections with a high positive predictive value and may be useful for estimating HIV incidence.

Keywords: AEGIS, Incidence, HIV Infections, HIV Seropositivity, Antibody Affinity, Immunoenzyme Techniques, Sensitivity and Specificity, Retrospective Studies, Longitudinal Studies, Greece, epidemiology, immunology

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MoOrC1041