Interpopulation variation in HIV testing promptness may introduce bias in HIV incidence estimates using the serologic testing algorithm for recent HIV seroconversion
- 1Yale University, School of Public Health, Center for Interdisciplinary Research on AIDS, New Haven, Connecticut, USA
- 2Department of Epidemiology, University of Washington, Seattle, Washington, USA
- 3Department of Anthropology, University of Washington, Seattle, Washington, USA
- 4Department of Biostatistics, University of Washington, Seattle, Washington, USA
- Correspondence to Dr Edward White, Yale University School of Public Health, Center for Interdisciplinary Research on AIDS, 60 College Street, PO Box 208034, New Haven, CT 065520-8034, USA; e.white{at}yale.edu
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Contributors EW was the analyst and writer for this manuscript and used it as a major part of his dissertation in epidemiology at the University of Washington. GG was the principal investigator of the project from which the data for this analysis were obtained and provided assistance with the manuscript. SG provided guidance in biostatistical methods. TL also provided guidance in biostatistical methods. SH provided assistance with the manuscript.
- Accepted 22 January 2010
- Published Online First 24 June 2010
Abstract
Objectives The serologic testing algorithm for recent HIV seroconversion (STARHS) calculates incidence using the proportion of testers who produce a level of HIV antibody high enough to be detected by ELISA but low enough to suggest recent infection. The validity of STARHS relies on independence between dates of HIV infection and dates of antibody testing. When subjects choose the time of their own test, testing may be motivated by risky behaviour or symptoms of infection and the criterion may not be met. This analysis was conducted to ascertain whether estimates of incidence derived using STARHS were consistent with estimates derived using a method more robust against motivated testing.
Methods A cohort-based incidence estimator and two STARHS methods were applied to identical populations (n=3821) tested for HIV antibody at publicly funded sites in Seattle. Overall seroincidence estimates, demographically stratified estimates and incidence rate ratios were compared across methods. The proportion of low-antibody testers among HIV-infected individuals was compared with the proportion expected given their testing histories.
Results STARHS estimates generally exceeded cohort-based estimates. Incidence ratios derived using STARHS between demographic strata were not consistent across methods. The proportion of HIV-infected individuals with lower antibody levels exceeded that which would be expected under independence between infection and testing.
Conclusions Incidence estimates and incidence rate ratios derived using methods that rely on the changing antibody level over the course of HIV infection may be vulnerable to bias when applied to populations who choose the time of their own testing.
- bias
- clinical populations
- epidemiology
- HIV
- HIV incidence
- laboratory diagnosis
- recency of infection
- STARHS
- surveillance
Footnotes
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Funding The parent study providing the data used in this analysis was conducted with support of the Centers for Disease Control and Prevention, grant number U62/CCU006260. This analysis was conducted with the support of the University of Washington, Department of Epidemiology and by grant number T32 MH020031 from the National Institute of Mental Health. Content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institute of Mental Health or the National Institutes of Health.
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Competing interests None.
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Ethics approval The University of Washington Human Subjects Division approved this analysis. The Washington State Human Research Review Section and the CDC Human Research Protection Office approved the parent study.
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Provenance and peer review Not commissioned; not externally peer reviewed.
