Applying propensity scores estimated in a full cohort to adjust for confounding in subgroup analyses

Jeremy A. Rassen, Robert J. Glynn, Kenneth J. Rothman, Soko Setoguchi Iwata, Sebastian Schneeweiss

Publication Date: 07/01/2012

Background: A correctly specified propensity score (PS) estimated in a cohort (“cohort PS”) should, in expectation, remain valid in a subgroup population. Objective: We sought to determine whether using a cohort PS can be validly applied to subgroup analyses and, thus, add efficiency to studies with many subgroups or restricted data. Methods: In each of three cohort studies, we estimated a cohort PS, defined five subgroups, and then estimated subgroup-specific PSs. We compared difference in treatment effect estimates for subgroup analyses adjusted by cohort PSs versus subgroup-specific PSs. Then, over 10 million times, we simulated a population with known characteristics of confounding, subgroup size, treatment interactions, and treatment effect and again assessed difference in point estimates. Results: We observed that point estimates in most subgroups were substantially similar with the two methods of adjustment. In simulations, the effect estimates differed by a median of 3.4% (interquartile (IQ) range 1.3-10.0%). The IQ range exceeded 10% only in cases where the subgroup had <1000 patients or few outcome events. Conclusions: Our empirical and simulation results indicated that using a cohort PS in subgroup analyses was a feasible approach, particularly in larger subgroups.