Illustrating Potential Effects of Alternate Control Populations on Real-World Evidence-based Statistical Analyses

Abstract

Case-control study designs are commonly used in retrospective analyses of Real-World Evidence (RWE). Due to the increasingly wide availability of RWE, it can be difficult to determine whether findings are robust or the result of testing multiple hypotheses. We investigate the potential effects of modifying cohort definitions in a case-control association study between depression and Type 2 Diabetes Mellitus (T2D). We found that small permutations to the criteria used to define the control population result in significant shifts in both the demographic structure of the identified cohort as well as the odds ratio of association. These differences remain present when testing against age and sex-matched controls. We believe this offers strong support for the need for robust guidelines, best practices and regulations around the use of observational RWE for clinical or regulatory decision making.