Mining clinical data for novel medications to treat alcohol use disorder

Abstract

BackgroundAlcohol use disorder (AUD) is a highly prevalent and often debilitating condition associated with high morbidity and mortality. Current AUD medications have limited efficacy and uptake. Alternative pharmacological options are needed. MethodsWe constructed a mechanistic tree of all US Food and Drug Administration approved medications and used a tree-based scan statistic, TreeScan, to identify medications associated with greater than expected improvements in alcohol consumption. Our cohort included all United States (US) Department of Veterans Affairs (VA) patients with a diagnosis of AUD between 10/1/1999 and 9/30/2019 with multiple Alcohol Use Disorders Identification Test-Consumption Module scores within the VA electronic health record data. ResultsMedications statistically associated with decreased alcohol consumption had, at large, minor effect sizes. Medications used in the treatment of chronic or life-threatening conditions like diabetes, chronic kidney disease, hepatitis C virus, or cancer produced larger effect sizes. Asenapine, an atypical antipsychotic, had a large effect with an observed to expected ratio of 1.78 (p = 0.003). Our findings were replicated in a propensity score matched population. ConclusionMost medications significantly associated with decreased alcohol consumption in our analysis were either contraindicated with alcohol or likely attributable to patients abstaining from alcohol due to severe illness. However, the large effect of asenapine is notable, and a worthwhile candidate for more careful analysis.