title: Estimating risk of alcohol dependence using alcohol screening scores.
abstract: Brief alcohol counseling interventions can reduce alcohol consumption and related morbidity among non-dependent risky drinkers, but more intensive alcohol treatment is recommended for persons with alcohol dependence. This study evaluated whether scores on common alcohol screening tests could identify patients likely to have current alcohol dependence so that more appropriate follow-up assessment and/or intervention could be offered. This cross-sectional study used secondary data from 392 male and 927 female adult family medicine outpatients (1993-1994). Likelihood ratios were used to empirically identify and evaluate ranges of scores of the AUDIT, the AUDIT-C, two single-item questions about frequency of binge drinking, and the CAGE questionnaire for detecting DSM-IV past-year alcohol dependence. Based on the prevalence of past-year alcohol dependence in this sample (men: 12.2%; women: 5.8%), zones of the AUDIT and AUDIT-C identified wide variability in the post-screening risk of alcohol dependence in men and women, even among those who screened positive for alcohol misuse. Among men, AUDIT zones 5-10, 11-14 and 15-40 were associated with post-screening probabilities of past-year alcohol dependence ranging from 18 to 87%, and AUDIT-C zones 5-6, 7-9 and 10-12 were associated with probabilities ranging from 22 to 75%. Among women, AUDIT zones 3-4, 5-8, 9-12 and 13-40 were associated with post-screening probabilities of past-year alcohol dependence ranging from 6 to 94%, and AUDIT-C zones 3, 4-6, 7-9 and 10-12 were associated with probabilities ranging from 9 to 88%. AUDIT or AUDIT-C scores could be used to estimate the probability of past-year alcohol dependence among patients who screen positive for alcohol misuse and inform clinical decision-making.
authors.affiliation: Northwest Health Services Research and Development Center of Excellence, VA Puget Sound Health Care System, Seattle, WA 98101, USA. Anna.Rubinsky@va.gov
authors.forename: Anna D
authors.initials: AD
authors.lastname: Rubinsky
authors.forename: Daniel R
authors.initials: DR
authors.lastname: Kivlahan
authors.forename: Robert J
authors.initials: RJ
authors.lastname: Volk
authors.forename: Charles
authors.initials: C
authors.lastname: Maynard
authors.forename: Katharine A
authors.initials: KA
authors.lastname: Bradley
mesh_terms: D000293:Adolescent; D000328:Adult; D000367:Age Factors; D000368:Aged; D000437:Alcoholism / Q000175:diagnosis* / Q000453:epidemiology*; D003430:Cross-Sectional Studies; D004493:Education; D005006:Ethnicity; D005260:Female; D006801:Humans; D007182:Income; D016013:Likelihood Functions; D008297:Male; D017533:Marital Status; D008875:Middle Aged; D011446:Prospective Studies; D011594:Psychometrics / Q000295:instrumentation*; D015203:Reproducibility of Results; D018570:Risk Assessment; D011795:Surveys and Questionnaires; D055815:Young Adult