title: Using probit regression to disclose the analytical performance of qualitative and semi-quantitative tests.
abstract: BACKGROUND
  The analytical performance of qualitative and semi-quantitative tests is usually studied by calculating the fraction of positive results after replicate testing of a few specimens with known concentrations of the analyte. We propose using probit regression to model the probability of positive results as a function of the analyte concentration, based on testing many specimens once with a qualitative and a quantitative test.
  
  
  METHODS
  We collected laboratory data where urine specimens had been analyzed by both a urine albumin ('protein') dipstick test (Combur-Test strips) and a quantitative test (BN ProSpec System). For each dipstick cut-off level probit regression was used to estimate the probability of positive results as a function of urine albumin concentration. We also used probit regression to estimate the standard deviation of the continuous measurement signal that lies behind the binary test response. Finally, we used probit regression to estimate the probability of reading a specific semi-quantitative dipstick result as a function of urine albumin concentration.
  
  
  RESULTS
  Based on analyses of 3259 specimens, the concentration of urine albumin with a 0.5 (50%) probability of positive result was 57 mg/L at the lowest possible cut-off limit, and 246 and 750 mg/L at the next (higher) levels. The corresponding standard deviations were 29, 83, and 217 mg/L, respectively. Semi-quantitatively, the maximum probability of these three readings occurred at a u-albumin of 117, 420, and 1200 mg/L, respectively.
  
  
  CONCLUSIONS
  Probit regression is a useful tool to study the analytical performance of qualitative and semi-quantitative tests.
authors.affiliation: a Department of Clinical Chemistry , Trondheim University Hospital , Trondheim , Norway.
authors.forename: Arne
authors.initials: A
authors.lastname: Åsberg
authors.affiliation: b Department of Nuclear Medicine , Trondheim University Hospital , Trondheim , Norway.
authors.forename: Harald
authors.initials: H
authors.lastname: Johnsen
authors.affiliation: a Department of Clinical Chemistry , Trondheim University Hospital , Trondheim , Norway.
authors.forename: Gustav
authors.initials: G
authors.lastname: Mikkelsen
authors.affiliation: a Department of Clinical Chemistry , Trondheim University Hospital , Trondheim , Norway.
authors.forename: Gunhild Garmo
authors.initials: GG
authors.lastname: Hov
mesh_terms: D000419:Albuminuria / Q000652:urine*; D001681:Biological Assay / Q000592:standards*; D006801:Humans; D011933:Reagent Kits, Diagnostic / Q000706:statistics & numerical data*; D011934:Reagent Strips; D012044:Regression Analysis; D012680:Sensitivity and Specificity; D016482:Urinalysis / Q000379:methods / Q000706:statistics & numerical data*
chemical_list: D011933:Reagent Kits, Diagnostic; D011934:Reagent Strips
keywords: Diagnostic equipment; diagnostic reagents and test kits; regression analysis; regression diagnostics; urinalysis