# Optimal Endpoints in Clinical Trials of Cognitive Behavioral Interventions for AOD: An Aggregate and Individual Patient Data Meta-Analysis

> **NIH NIH R01** · BROWN UNIVERSITY · 2024 · $572,808

## Abstract

Project Abstract
The purpose of this study is to conduct a comprehensive and state-of-the-art meta-analysis of Cognitive
Behavioral Therapy, Relapse Prevention, and other Cognitive-Behavioral Intervention (CBIs) efficacy,
moderated efficacy, and mediating processes. Building upon our prior work (R21 AA026006; PI: Magill, Co-Is:
Kiluk & Ray; Consultants: Carroll & Tonigan), this R01 project will extract additional functional endpoints from
the prior meta-analytic sample (i.e., K~100 primary studies), will conduct an updated search to yield all recent
trials, and will incorporate advanced methodologies such as Network Meta-Analysis (NMA) and Individual
Participant Data Meta-Analysis (IPD). In our prior work, consumption frequency and heavy frequency at one
early and one late follow-up time point were the a priori indicators of interest. However, the dialogue on what
constitutes an optimal endpoint in randomized clinical trials has grown in recent years (e.g., ACTIVE Initiative),
arguing that a range of functional endpoints beyond abstinence or heavy consumption should be of greater
emphasis in treatment development and clinical outcome research. Alternative endpoints such as related
problems, coping behaviors, and mental and general health are certainly of interest to patients, families, and
clinical providers. These indicators have additionally become key constructs in the what defines recovery.
Preliminary analyses of the sample of trials reviewed in R21 AA026006 show that data for 4 to 50 possible
endpoints are available per study, and that approximately 79% of the available data have yet to be
collected, analyzed, or reported. In addition, using the methods of R21 AA023662 (PI: Magill), direct data
requests for a selection of alcohol use disorder (AUD) studies will be conducted, and a number of relevant PIs
have already agreed to meet such requests. In this case, a two-stage IPD will be used to conduct an aggregate
path analysis of CBI process, considering putative mechanisms of CBI efficacy. Although R01-level meta-analytic
projects have been conducted on a) alcohol pharmacotherapies, b) DUI interventions, c) brief interventions for
adolescents/young adults, and d) combined AUD and trauma-related therapies, no such project has been
undertaken on CBIs, and this is despite their longevity and centrality in direct patient care for alcohol and other
drug use disorders. The proposed project, extracting all available endpoints from the published reports,
conducting data requests for AUD trials specifically, and conducting NMA to account for variability in type of
contrast condition will inform clinical and methodological recommendations on: 1) CBI implementation and
delivery, 2) optimal endpoints for measuring CBI effect, and 3) defining and understanding recovery in the context
of evidence-based treatment.

## Key facts

- **NIH application ID:** 10907536
- **Project number:** 5R01AA029703-03
- **Recipient organization:** BROWN UNIVERSITY
- **Principal Investigator:** Molly Magill
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $572,808
- **Award type:** 5
- **Project period:** 2022-09-01 → 2026-08-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10907536

## Citation

> US National Institutes of Health, RePORTER application 10907536, Optimal Endpoints in Clinical Trials of Cognitive Behavioral Interventions for AOD: An Aggregate and Individual Patient Data Meta-Analysis (5R01AA029703-03). Retrieved via AI Analytics 2026-05-25 from https://api.ai-analytics.org/grant/nih/10907536. Licensed CC0.

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