title: Assessment of BED HIV-1 incidence assay in seroconverter cohorts: effect of individuals with long-term infection and importance of stable incidence.
abstract: BACKGROUND
  Performance of the BED assay in estimating HIV-1 incidence has previously been evaluated by using longitudinal specimens from persons with incident HIV infections, but questions remain about its accuracy. We sought to assess its performance in three longitudinal cohorts from Thailand where HIV-1 CRF01_AE and subtype B' dominate the epidemic.
  
  
  METHODS
  BED testing was conducted in two longitudinal cohorts with only incident infections (a military conscript cohort and an injection drug user cohort) and in one longitudinal cohort (an HIV-1 vaccine efficacy trial cohort) that also included long-term infections.
  
  
  METHODS
  Incidence estimates were generated conventionally (based on the number of annual serocoversions) and by using BED test results in the three cohorts. Adjusted incidence was calculated where appropriate.
  
  
  RESULTS
  For each longitudinal cohort the BED incidence estimates and the conventional incidence estimates were similar when only newly infected persons were tested, whether infected with CRF01_AE or subtype B'. When the analysis included persons with long-term infections (to mimic a true cross-sectional cohort), BED incidence estimates were higher, although not significantly, than the conventional incidence estimates. After adjustment, the BED incidence estimates were closer to the conventional incidence estimates. When the conventional incidence varied over time, as in the early phase of the injection drug user cohort, the difference between the two estimates increased, but not significantly.
  
  
  CONCLUSIONS
  Evaluation of the performance of incidence assays requires the inclusion of a substantial number of cohort-derived specimens from individuals with long-term HIV infection and, ideally, the use of cohorts in which incidence remained stable. Appropriate adjustments of the BED incidence estimates generate estimates similar to those generated conventionally.
authors.affiliation: Division of HIV/AIDS Prevention, Centers for Disease Control and Prevention, Atlanta, Georgia, United States of America. jkm7@cdc.gov
authors.forename: Janet M
authors.initials: JM
authors.lastname: McNicholl
authors.forename: J Steven
authors.initials: JS
authors.lastname: McDougal
authors.forename: Punneeporn
authors.initials: P
authors.lastname: Wasinrapee
authors.forename: Bernard M
authors.initials: BM
authors.lastname: Branson
authors.forename: Michael
authors.initials: M
authors.lastname: Martin
authors.forename: Jordan W
authors.initials: JW
authors.lastname: Tappero
authors.forename: Philip A
authors.initials: PA
authors.lastname: Mock
authors.forename: Timothy A
authors.initials: TA
authors.lastname: Green
authors.forename: Dale J
authors.initials: DJ
authors.lastname: Hu
authors.forename: Bharat
authors.initials: B
authors.lastname: Parekh
mesh_terms: D015331:Cohort Studies; D006679:HIV Seropositivity / Q000453:epidemiology* / Q000276:immunology* / Q000821:virology; D015497:HIV-1 / Q000276:immunology*; D006801:Humans; D007118:Immunoassay / Q000379:methods*; D015994:Incidence; D008297:Male; D013785:Thailand / Q000453:epidemiology; D013997:Time Factors