title: Validation of the Bayesian Alcoholism Test compared to single biomarkers in detecting harmful drinking.
abstract: OBJECTIVE
  Conventional tests for alcohol dependence often fail to detect hazardous and harmful alcohol use (HHAU) accurately. We previously validated the Bayesian Alcoholism Test (BAT) for the detection of HHAU among males. This uses 15 biochemical and clinical variables, including questionnaire data to calculate the probability of harmful (>80 g alcohol/day), hazardous (40-80 g/day) and 'moderate' (<40 g/day) drinking. Here we investigate the BAT's diagnostic performance when more limited clinical data are available.
  
  
  METHODS
  The WHO/ISBRA Collaborative Project recruited subjects from the general community and alcohol dependence treatment services. We analysed data from male drinkers: 318 alcohol dependent, 220 heavy and 712 moderate drinkers. Drinking was assessed using the Alcohol-Use Disorders and Associated Disabilities Interview Schedule. Eight of 15 markers used in the original BAT could be extracted from the WHO/ISBRA dataset.
  
  
  RESULTS
  Comparing harmful to moderate drinkers, the area under the ROC curve for BAT (0.90) was significantly higher than that for CDT (0.82), GGT (0.77) and AST (0.76). Comparing hazardous to moderate drinkers, the area under the ROC curve for BAT (0.78) was significantly higher than that for AST (0.65) but not significantly higher than that for CDT (0.71) and GGT (0.70). For all 1250 subjects, the amount consumed correlated significantly better with BAT (0.65) than with CDT (0.52), GGT (0.44) or AST (0.40) alone.
  
  
  CONCLUSIONS
  The BAT is more accurate than commonly used single biological markers in detecting harmful alcohol use, even when only half the input requirements are available. Computerized record keeping increases the practicality of use of algorithms in the detection of harmful drinking.
authors.affiliation: Sint Lucas Andreas Ziekenhuis, Post Box 9423, 1006 AE Amsterdam, The Netherlands. skorzec@science.uva.nl
authors.forename: Sanne
authors.initials: S
authors.lastname: Korzec
authors.forename: Alex
authors.initials: A
authors.lastname: Korzec
authors.forename: Katherine
authors.initials: K
authors.lastname: Conigrave
authors.forename: Janneke
authors.initials: J
authors.lastname: Gisolf
authors.forename: Boris
authors.initials: B
authors.lastname: Tabakoff
mesh_terms: D000328:Adult; D000368:Aged; D000437:Alcoholism / Q000175:diagnosis*; D001499:Bayes Theorem; D015415:Biomarkers / Q000097:blood*; D005260:Female; D006801:Humans; D016013:Likelihood Functions; D008297:Male; D008875:Middle Aged; D012372:ROC Curve; D015203:Reproducibility of Results; D011795:Surveys and Questionnaires; D014168:Transferrin / Q000031:analogs & derivatives / Q000378:metabolism; D005723:gamma-Glutamyltransferase / Q000097:blood
chemical_list: D015415:Biomarkers; D014168:Transferrin; C056759:carbohydrate-deficient transferrin; D005723:gamma-Glutamyltransferase