Identifying responders to gabapentin for the treatment of alcohol use disorder: an exploratory machine learning approach.

Journal: Alcohol and alcoholism (Oxford, Oxfordshire)
PMID: 40138385

Abstract

BACKGROUND: Gabapentin, an anticonvulsant medication, has been proposed as a treatment for alcohol use disorder (AUD). A multisite study tested gabapentin enacarbil extended-release (GE-XR; 600 mg/twice a day), a prodrug formulation, combined with a computerized behavioral intervention, for AUD. In this multisite trial, the gabapentin GE-XR group did not differ significantly from placebo on the primary outcome of percent of subjects with no heavy drinking days. Despite the null findings, there is considerable interest in using machine learning methods to identify responders to GE-XR. The present study applies interaction tree machine learning methods to identify positive and iatrogenic (i.e. individuals who responded better to placebo than to GE-XR) treatment responders in the trial.

Authors

  • Lara A Ray
    Department of Psychology, University of California Los Angeles, Los Angeles, California, USA.
  • Erica N Grodin
    Clinical NeuroImaging Research Core, National Institute of Alcohol Abuse and Alcoholism, National Institutes of Health, 10 Center Drive, Bethesda, MD 20814, MSC 1108, United States.
  • Wave-Ananda Baskerville
    Department of Psychology, University of California, Los Angeles, 1285 Franz Hall, Los Angeles, CA 90095, United States.
  • Suzanna Donato
    Department of Psychology, University of California, Los Angeles, 1285 Franz Hall, Los Angeles, CA 90095, United States.
  • Alondra Cruz
    Department of Psychology, University of California, Los Angeles, 1285 Franz Hall, Los Angeles, CA 90095, United States.
  • Amanda K Montoya
    Department of Psychology, University of California Los Angeles, Los Angeles, California, USA.

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