Estimating risk of alcohol dependence using alcohol screening scores☆☆☆
Received 7 March 2009; received in revised form 26 August 2009; accepted 7 November 2009.
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.
aNorthwest Health Services Research and Development Center of Excellence, VA Puget Sound Health Care System, Seattle, WA 98101, USA
bDepartment of Health Services, University of Washington, Seattle, WA 91895, USA
cDepartment of Psychiatry and Behavioral Sciences, University of Washington, Seattle, WA 91895, USA
dDepartment of Medicine, University of Washington, Seattle, WA 91895, USA
eDepartment of General Internal Medicine, Ambulatory Treatment & Emergency Care, The University of Texas M.D. Anderson Cancer Center, Houston, TX 77230, USA
Corresponding author at: Northwest HSR&D Center of Excellence, VA Puget Sound Health Care System, 1100 Olive Way, Suite 1400, Seattle, WA 98101, USA. Tel.: +1 206 277 4156; fax: +1 206 768 5343.
☆ Supplementary information on the data analytic approach used in this study is available with the online version of this paper at doi:xxx/j.drugalcdep.xxx.
☆☆Disclaimer: The views expressed in this article are those of the authors and do not necessarily reflect the position or policy of the Department of Veterans Affairs, University of Washington, Baylor College of Medicine, The University of Texas or National Institute on Alcohol Abuse and Alcoholism.