Interpopulation variation in HIV testing promptness may introduce bias in HIV incidence estimates using the serologic testing algorithm for recent HIV seroconversion
ObjectivesThe 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 betw...
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| Abstract | ObjectivesThe 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.MethodsA 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.ResultsSTARHS 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.ConclusionsIncidence 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. |
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| AbstractList | 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. 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. 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. 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. 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. ObjectivesThe 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.MethodsA 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.ResultsSTARHS 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.ConclusionsIncidence 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. 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.OBJECTIVESThe 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.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.METHODSA 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.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.RESULTSSTARHS 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.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.CONCLUSIONSIncidence 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. |
| Author | White, Edward Hawes, Stephen E Goodreau, Steven Goldbaum, Gary Lumley, Thomas |
| AuthorAffiliation | 1 Yale University, School of Public Health, Center for Interdisciplinary Research on AIDS, New Haven, Connecticut, USA 3 Department of Anthropology, University of Washington, Seattle, Washington, USA 2 Department of Epidemiology, University of Washington, Seattle, Washington, USA 4 Department of Biostatistics, University of Washington, Seattle, Washington, USA |
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| Author_xml | – sequence: 1 givenname: Edward surname: White fullname: White, Edward email: e.white@yale.edu organization: Yale University, School of Public Health, Center for Interdisciplinary Research on AIDS, New Haven, Connecticut, USA – sequence: 2 givenname: Gary surname: Goldbaum fullname: Goldbaum, Gary email: e.white@yale.edu organization: Department of Epidemiology, University of Washington, Seattle, Washington, USA – sequence: 3 givenname: Steven surname: Goodreau fullname: Goodreau, Steven email: e.white@yale.edu organization: Department of Anthropology, University of Washington, Seattle, Washington, USA – sequence: 4 givenname: Thomas surname: Lumley fullname: Lumley, Thomas email: e.white@yale.edu organization: Department of Biostatistics, University of Washington, Seattle, Washington, USA – sequence: 5 givenname: Stephen E surname: Hawes fullname: Hawes, Stephen E email: e.white@yale.edu organization: Department of Epidemiology, University of Washington, Seattle, Washington, USA |
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| Snippet | ObjectivesThe serologic testing algorithm for recent HIV seroconversion (STARHS) calculates incidence using the proportion of testers who produce a level of... Objectives The serologic testing algorithm for recent HIV seroconversion (STARHS) calculates incidence using the proportion of testers who produce a level of... The serologic testing algorithm for recent HIV seroconversion (STARHS) calculates incidence using the proportion of testers who produce a level of HIV antibody... |
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| SubjectTerms | Adult Algorithms Bias Biological and medical sciences clinical populations Enzyme-Linked Immunosorbent Assay epidemiology Epidemiology. Vaccinations Estimates Ethnicity General aspects HIV HIV Antibodies - blood HIV incidence HIV Infections - epidemiology HIV Infections - immunology HIV Seropositivity - diagnosis Human immunodeficiency virus Human infectious diseases. Experimental studies and models Human viral diseases Humans Incidence Infections Infectious diseases laboratory diagnosis Medical laboratories Medical sciences Medical tests Methods Middle Aged recency of infection STARHS surveillance Viral diseases Viral diseases of the lymphoid tissue and the blood. Aids Washington - epidemiology Young Adult |
| Title | Interpopulation variation in HIV testing promptness may introduce bias in HIV incidence estimates using the serologic testing algorithm for recent HIV seroconversion |
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