A Systematic Approach For Quantifying Heterogeneity Within Clinical Trial Populations

Heterogeneity in clinical trial populations can contribute to variability in observed treatment effect. According to the Cochrane Handbook, sources can be either clinical or methodological diversity. Assessing the impact of heterogeneity in observed intervention effects is an important part of interpreting trial results, whether determining the presence of unanticipated clinical subgroups in a given trial or designing pooled analyses of trial results, even for those with ostensibly similar methodologies. Two proven quantitative approaches to addressing heterogeneity include use of clustering algorithms and of propensity score modeling techniques.

We propose here a quantitative, systematic, scalable approach to assessing clinical trial population heterogeneity, leveraging both approaches, to estimate the likely presence and impact of heterogeneity on observed trial results, and guide future analysis.