What works for whom in pediatric OCD: description of causally interpretable meta-analysis methods and report on trial data harmonization.

Background: Improving patient outcomes will be enhanced by understanding "what works, for whom?" enabling better matching of patients to available treatments. However, answering this "what works, for whom?" question requires sample sizes that exceed those of most individual trials. Conventional methods for combining data across trials, including aggregate-data meta-analysis, suffer from key limitations including difficulty accounting for differences across trials (e.g., comparing "apples to oranges"). Causally interpretable meta-analysis (CI-MA) addresses these limitations by pairing individual-participant-data (IPD) across trials using advancements in transportability methods to extend causal inferences to clinical "target" populations of interest. Combining IPD across trials also requires careful acquisition and harmonization of data, a challenging process for which practical guidance is not well-described in the literature.

Methods: We describe methods and work to date for a large harmonization project in pediatric obsessive-compulsive disorder (OCD) that employs CI-MA.

Results: We review the data acquisition, harmonization, meta-data coding, and IPD analysis processes for Project Harmony, a study that (1) harmonizes 28 randomized controlled trials, along with target data from a clinical sample of treatment-seeking youth ages 4-20 with OCD, and (2) applies CI-MA to examine "what works, for whom?" We also detail dissemination strategies and partner involvement planned throughout the project to enhance the future clinical utility of CI-MA findings. Data harmonization took approximately 125 hours per trial (3,000 hours total), which was considerably higher than preliminary projections.

Conclusions: Applying CI-MA to harmonize data has the potential to answer "what works for whom?" in pediatric OCD.