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PLoS One. 2013 Dec 27;8(12):e82772. doi: 10.1371/journal.pone.0082772. eCollection 2013.

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

Author information

1
Department of Biostatistics, School of Public Health, University of California Los Angeles, Los Angeles, California, United States of America.
2
National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, Maryland, United States of America.
3
Department of Pathology, Johns Hopkins University School of Medicine, Baltimore, Maryland, United States of America.
4
Departments. of Global Health and Medicine, University of Washington, Seattle, Washington, United States of America.
5
Bridge HIV, San Francisco Department of Health, San Francisco, California, United States of America.
6
Department of Epidemiology, Harvard School of Public Health, Boston, Massachusetts, United States of America.
7
Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, United States of America.
8
Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland, United States of America.
9
Department of Molecular Microbiology and Immunology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, United States of America.
10
Department of Epidemiology, School of Public Health, University of California Los Angeles, Los Angeles, California, United States of America.
11
Department of Global Health and Population Harvard School of Public Health, Boston, Massachusetts, United States of America.
12
New York Blood Center, New York, New York, United States of America.
13
Department of Epidemiology, Columbia University Mailman School of Public Health, New York, United States of America.
14
Department of Medicine, New Jersey Medical School, Newark, New Jersey, United States of America.
15
National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, Maryland, United States of America ; Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland, United States of America.

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.

PMID:
24386116
PMCID:
PMC3873916
DOI:
10.1371/journal.pone.0082772
[Indexed for MEDLINE]
Free PMC Article

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