Evaluation of the Performance of Three Biomarker Assays for Recent HIV Infection Using a Well-Characterized HIV-1 Subtype C Incidence Cohort.


Journal

AIDS research and human retroviruses
ISSN: 1931-8405
Titre abrégé: AIDS Res Hum Retroviruses
Pays: United States
ID NLM: 8709376

Informations de publication

Date de publication:
07 2019
Historique:
pubmed: 3 4 2019
medline: 7 7 2020
entrez: 3 4 2019
Statut: ppublish

Résumé

Biomarkers for detecting early HIV infection and estimating HIV incidence should minimize false-recent rates (FRRs) while maximizing mean duration of recent infection (MDRI). We compared HIV subtypes B, E and D (BED) capture enzyme immunoassay (BED), Sedia limiting antigen (LAg) avidity enzyme immunoassay, and Bio-Rad avidity incidence (BRAI) assays using samples from Zimbabwean postpartum women infected with clade C HIV. We calculated MDRIs using 590 samples from 351 seroconverting postpartum women, and FRRs using samples from 2,825 women known to be HIV positive for >12 months. Antibody kinetics were more predictable with LAg and had higher precision compared with BED or BRAI. BRAI also exhibited more variability, and avidity reversal in some cases. For BED, LAg, and BRAI, used alone or with viral load, MDRI values in days were: BED-188 and 170 at normalized optical density (ODn) 0.8; LAg-104 and 100 at ODn cutoff 1.5; BRAI-135 and 134 at avidity index cutoff 30%. Corresponding FRRs were: BRAI 1.1% and 1.0% and LAg 0.57% and 0.35%: these were 3.8-10.9 times lower than BED values of 4.8% and 3.8%. BRAI and LAg have significantly lower FRRs and MDRIs than in published studies, and much lower than BED and could be used to estimate incidence in perinatal women and to measure population-level HIV incidence in HIV control operations in Africa.

Identifiants

pubmed: 30938164
doi: 10.1089/AID.2019.0033
doi:

Substances chimiques

Biomarkers 0
HIV Antibodies 0

Types de publication

Comparative Study Evaluation Study Journal Article Research Support, U.S. Gov't, Non-P.H.S. Research Support, U.S. Gov't, P.H.S.

Langues

eng

Sous-ensembles de citation

IM

Pagination

615-627

Subventions

Organisme : PEPFAR
Pays : United States

Auteurs

Elizabeth Gonese (E)

1 Division of Global HIV and TB, Centers for Disease Control and Prevention, Harare, Zimbabwe.
2 DST-NRF Center of Excellence in Epidemiological Modeling and Analysis (SACEMA), Faculty of Science, Stellenbosch University, Stellenbosch, South Africa.

Peter H Kilmarx (PH)

1 Division of Global HIV and TB, Centers for Disease Control and Prevention, Harare, Zimbabwe.
3 Division of Global HIV and TB, Centers for Disease Control and Prevention, Atlanta, Georgia.

Cari van Schalkwyk (C)

2 DST-NRF Center of Excellence in Epidemiological Modeling and Analysis (SACEMA), Faculty of Science, Stellenbosch University, Stellenbosch, South Africa.

Eduard Grebe (E)

2 DST-NRF Center of Excellence in Epidemiological Modeling and Analysis (SACEMA), Faculty of Science, Stellenbosch University, Stellenbosch, South Africa.

Kuda Mutasa (K)

4 Department of Laboratory Services, Zvitambo Institute for Maternal and Child Health Research, Harare, Zimbabwe.

Robert Ntozini (R)

4 Department of Laboratory Services, Zvitambo Institute for Maternal and Child Health Research, Harare, Zimbabwe.

Bharat Parekh (B)

3 Division of Global HIV and TB, Centers for Disease Control and Prevention, Atlanta, Georgia.

Trudy Dobbs (T)

3 Division of Global HIV and TB, Centers for Disease Control and Prevention, Atlanta, Georgia.

Yen Duong Pottinger (Y)

3 Division of Global HIV and TB, Centers for Disease Control and Prevention, Atlanta, Georgia.
5 Department of Laboratory Services, ICAP at University of Columbia, Mailman Public Health, Baltimore, Maryland.

Silvina Masciotra (S)

6 Department of Laboratory Services, Centers for Disease Control and Prevention, Atlanta, Georgia.

Michele Owen (M)

6 Department of Laboratory Services, Centers for Disease Control and Prevention, Atlanta, Georgia.

Jean B Nachega (JB)

7 Departments of Epidemiology, Infectious Diseases and Microbiology, University of Pittsburgh Graduate School of Public Health, Pittsburgh, Pennsylvania.
8 Department of Medicine and Center for Infectious Diseases, Faculty of Medicine and Health Sciences, Stellenbosch University, Cape Town, South Africa.
9 Departments of Epidemiology and International Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland.

Gert van Zyl (G)

10 Division of Medical Virology, Faculty of Medicine and Health Sciences, Stellenbosch University and National Health Laboratory Service, Cape Town, South Africa.

John W Hargrove (JW)

2 DST-NRF Center of Excellence in Epidemiological Modeling and Analysis (SACEMA), Faculty of Science, Stellenbosch University, Stellenbosch, South Africa.

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Classifications MeSH