Using data from the United Kingdom General Practice Research Database (GPRD) randomized controlled trials (RCTs) were replicated to determine whether identifiable study characteristics and/or analytic methods influence the validity of observational studies.
This study reports GPRD replications of 2 RCTs that investigated whether angiotensin-converting enzyme inhibitors (ACEIs) improve cardiovascular outcomes in patients without congestive heart failure at high risk for cardiovascular disease (heart outcomes prevention evaluation (HOPE) and EUROPA). The GPRD studies replicated to the extent feasible all aspects of these RCTs except for randomization.
With adjustment for confounders using conventional biostatistical techniques, both GPRD studies exhibited results divergent from the RCTs. Myocardial infarction, stroke, congestive heart failure, and coronary revascularization were increased in the Exposed group of both GPRD studies; whereas these outcomes either were decreased or unchanged by ACEI therapy in both RCTs. The results also were analyzed with a new method that appears to adjust for both identified and unmeasured confounders. With this methodology that employs the ratio of event rates between the Exposed and Unexposed cohorts prior to study start time to adjust the study hazard ratio (HR), the GPRD results for myocardial infarction, stroke, and coronary revascularization were largely similar to those found in the two RCTs.
This study provides additional empiric evidence suggesting that this new analytic methodology, ‘prior events rate ratio (PERR)’ adjustment, is a promising solution for the vexing problem of ‘unmeasured confounding’ in observational studies. Additional statistical simulations are needed to fully appreciate the applicability and limitations of this method. Copyright © 2008 John Wiley & Sons, Ltd.