Examining the Impact of Trial Length on Detecting Medication Effects for Alcohol Use Disorder: A Meta-Regression...

Area of Science:

• Pharmacology
• Clinical Trials
• Addiction Medicine

Background:

• The U.S. Food and Drug Administration (FDA) recommends a minimum 6-month duration for pharmacotherapy trials in alcohol use disorder (AUD).
• The impact of randomized controlled trial (RCT) length on observed treatment effects in AUD is not well understood.
• This study investigates the association between trial duration and medication effect sizes in AUD clinical trials.

Purpose of the Study:

• To examine the relationship between randomized controlled trial (RCT) length and medication effect sizes for alcohol use disorder (AUD).
• To compare effect sizes in shorter (<12 weeks) and longer (>12 weeks) AUD trials against a 12-week reference duration.
• To inform optimal design strategies for future AUD clinical trials.

Main Methods:

• Meta-regression analyses were performed on data from 139 pharmacotherapy RCTs for AUD (1985-2023).
• Effect sizes for abstinence and drinking-based endpoints were compared across trials of different lengths (<12 weeks, >12 weeks, and 12 weeks).
• Publication bias was assessed and adjusted for using a weight-function model.

Main Results:

• No significant differences in medication effect sizes were observed between shorter (<12 weeks), longer (>12 weeks), and 12-week trials for either abstinence or drinking endpoints.
• These findings remained non-significant after adjusting for publication bias.
• Sensitivity analyses revealed that trials >12 weeks had smaller effect sizes compared to trials ≤12 weeks, specifically among those with statistically significant results.

Conclusions:

• Trial duration did not significantly alter observed medication effect sizes for AUD pharmacotherapy across abstinence and drinking endpoints.
• An advantage for shorter trials (≤12 weeks) emerged in analyses restricted to statistically significant effect sizes.
• Findings suggest that trial length may influence perceived treatment efficacy, particularly in significant findings, impacting AUD RCT design optimization.