title: High specificity of line-immunoassay based algorithms for recent HIV-1 infection independent of viral subtype and stage of disease.
abstract: BACKGROUND
  Serologic testing algorithms for recent HIV seroconversion (STARHS) provide important information for HIV surveillance. We have shown that a patient's antibody reaction in a confirmatory line immunoassay (INNO-LIA HIV I/II Score, Innogenetics) provides information on the duration of infection. Here, we sought to further investigate the diagnostic specificity of various Inno-Lia algorithms and to identify factors affecting it.
  
  
  METHODS
  Plasma samples of 714 selected patients of the Swiss HIV Cohort Study infected for longer than 12 months and representing all viral clades and stages of chronic HIV-1 infection were tested blindly by Inno-Lia and classified as either incident (up to 12 m) or older infection by 24 different algorithms. Of the total, 524 patients received HAART, 308 had HIV-1 RNA below 50 copies/mL, and 620 were infected by a HIV-1 non-B clade. Using logistic regression analysis we evaluated factors that might affect the specificity of these algorithms.
  
  
  RESULTS
  HIV-1 RNA < 50 copies/mL was associated with significantly lower reactivity to all five HIV-1 antigens of the Inno-Lia and impaired specificity of most algorithms. Among 412 patients either untreated or with HIV-1 RNA ≥ 50 copies/mL despite HAART, the median specificity of the algorithms was 96.5% (range 92.0-100%). The only factor that significantly promoted false-incident results in this group was age, with false-incident results increasing by a few percent per additional year. HIV-1 clade, HIV-1 RNA, CD4 percentage, sex, disease stage, and testing modalities exhibited no significance. Results were similar among 190 untreated patients.
  
  
  CONCLUSIONS
  The specificity of most Inno-Lia algorithms was high and not affected by HIV-1 variability, advanced disease and other factors promoting false-recent results in other STARHS. Specificity should be good in any group of untreated HIV-1 patients.
authors.affiliation: University of Zurich, Institute of Medical Virology, Swiss National Center for Retroviruses, Zurich, Switzerland. schupbach.jorg@virology.uzh.ch
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mesh_terms: D000328:Adult; D000465:Algorithms; D019411:Clinical Laboratory Techniques / Q000379:methods*; D005260:Female; D015658:HIV Infections / Q000175:diagnosis*; D015497:HIV-1 / Q000145:classification / Q000235:genetics / Q000276:immunology; D006801:Humans; D007118:Immunoassay; D008297:Male; D012367:RNA, Viral / Q000097:blood; D012680:Sensitivity and Specificity; D014773:Virology / Q000379:methods*
chemical_list: D012367:RNA, Viral