Online Program

Empirical Limits in Synthesizing Findings from Individual Data Across Similar and Diverse Randomized Trials

Ahnalee Brinks, University of Miami 
*C Hendricks Brown, Northwestern University 
Getachew Dagne, University of South Florida 
George Howe, George Washington University 
Hilda M Pantin, University of Miami Miller School of Medicine 
Tatiana Perrino, University of Miami Miller School of Medicine 
Juned Siddique, Northwestern University 

Keywords: integrative data analyses (IDA), synthesis of individual-level data, moderation, mediation

In standard meta-analysis, summary statistics from similar randomized trials are combined by standardizing outcomes, most often on effect size or odds ratio scales, and then adjusted for trial level covariates in meta-regression. Typically meta-analyses are limited to main effect. With syntheses that are built around individual level data across multiple trials, there is more opportunity to conduct more refined analyses, including rare subgroup analyses, moderation analyses, and mediation analyses. The challenge, however, with combining such data is that the trials may differ along three major dimensions, including population characteristics, trial level characteristics (including which measures and which times are used for assessments), and intervention characteristics. Using an ongoing synthesis study of up to 40 randomized trials focusing on adolescent depression, we discuss the limits of findings that can come from such synthesis studies. One example uses three similar trials of the Familias Unidas intervention, which focuses on preventing drug abuse, HIV risk behaviors, and depression in Hispanic adolescents. At the other extreme we discuss the synthesis of a broad set of related preventive interventions that differ on measures assessed, intervention, and population characteristics.