Leveraging meta-regression to test if medication effects on cue-induced craving are associated with clinical efficacy

Steven J Nieto; Han Du; Lindsay R Meredith; Suzanna Donato; Molly Magill; Lara A Ray

doi:10.1007/s00213-024-06589-7

Leveraging meta-regression to test if medication effects on cue-induced craving are associated with clinical efficacy

Psychopharmacology (Berl). 2024 Apr 13. doi: 10.1007/s00213-024-06589-7. Online ahead of print.

Authors

Steven J Nieto¹, Han Du², Lindsay R Meredith², Suzanna Donato², Molly Magill³, Lara A Ray^{2

4}

Affiliations

¹ Department of Psychology, University of California at Los Angeles, 1285 Franz Hall, Box 951563, Los Angeles, CA, 90095-1563, USA. snieto@psych.ucla.edu.
² Department of Psychology, University of California at Los Angeles, 1285 Franz Hall, Box 951563, Los Angeles, CA, 90095-1563, USA.
³ Center for Alcohol and Addiction Studies, Brown University School of Public Health, Providence, Rhode Island, USA.
⁴ Department of Psychiatry and Biobehavioral Sciences, University of California at Los Angeles, Los Angeles, CA, USA.

PMID: 38613685
DOI: 10.1007/s00213-024-06589-7

Abstract

Rationale: The alcohol cue exposure paradigm is a common method for evaluating new treatments for alcohol use disorder (AUD); however, it is unclear if medication-related reductions in cue-induced craving in the human laboratory can predict the clinical success of those medications in reducing alcohol consumption during clinical trials.

Objectives: To use a novel meta-analytic approach to test whether medication effect sizes on cue-induced alcohol craving are associated with clinical efficacy in clinical trials.

Method: We searched the literature for medications tested for AUD treatment using both the alcohol cue-reactivity paradigm and randomized clinical trials (RCTs). For alcohol cue-reactivity studies, we computed medication effect sizes for cue-induced alcohol craving (k = 36 studies, 15 medications). For RCTs, we calculated medication effect sizes for heavy drinking and abstinence (k = 139 studies, 19 medications). Using medication as the unit of analysis, we applied the Williamson-York bivariate weighted least squares estimation to account for errors in both independent and dependent variables. We also conducted leave-one-out cross validation simulations to examine the predictive utility of cue-craving medication effect sizes on RCT heavy drinking and abstinence endpoints.

Results: There was no significant relationship between medication effects on cue-induced alcohol craving in the human laboratory and medication effects on heavy drinking ( $\hat{β}$ = 0.253, SE = 0.189, p = 0.090) and abstinence ( $\hat{β}$ = 0.829, SE = 0.747, p = 0.133) in RCTs.

Conclusions: The preliminary results of the current study challenge the assumption that alcohol cue-reactivity alone can be used as an early efficacy indicator for AUD pharmacotherapy development. These findings suggest that a wider range of early efficacy indicators and experimental paradigms be considered for Phase II testing of novel compounds.

Keywords: Alcohol cue-reactivity; Alcohol use disorder; Cue-induced craving; Human laboratory; Medication development; Randomized clinical trials.

Abstract

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