In a study supported by the NIH Collaboratory, researchers developed and validated a new sample size formula for detecting heterogeneity of treatment effect in cluster randomized trials. The work was published this month in Statistics in Medicine.

Cluster randomization is frequently used in pragmatic clinical trials embedded in healthcare systems. Although cluster randomized trials are typically designed to evaluate the overall treatment effect in a study population, investigators are increasingly interested in studying differential treatment effects among subgroups.

The NIH Collaboratory investigators used extensive computer simulations to validate the new formula. They illustrate the procedure in a dataset from a large clinical trial.

In a previous study published last year, the same research team used computer simulation models validated by real-data simulations to reveal the influence of baseline covariate imbalance on treatment effect bias.

This work was supported within the NIH Collaboratory by the NIH Common Fund through a cooperative agreement from the Office of Strategic Coordination within the Office of the NIH Director, and by a research supplement from the NIH Common Fund to promote diversity in health-related research.