NIH National Heart, Lung, and Blood Institute (NHLBI)
Dr. Michele Jonsson-Funk, Epidemiology
Project Run Dates
5/1/2014 to 4/30/2018
Cardiovascular disease (CVD) remains the leading cause of morbidity and mortality in the United States. Recent evidence suggests women, in comparison to men, experience greater CVD related mortality, may have inferior responses to treatment, and are at greater risk of adverse drug events. However, from drug development to safety, tolerability and efficacy testing, insufficient attention has been given to sex differences in patient responses to pharmacologic agents. Moreover, randomized controlled trials, even large multicenter studies, are generally underpowered to detect heterogeneity in efficacy or safety, including any existing sex differences. Our preliminary results further suggest that standard analytic approaches for assessing sex differences in non-experimental research may lead to estimated sex-specific treatment effects that are biased. Therefore, our overall objectives are to develop, test, implement, and disseminate reliable and innovative methods for evaluating sex differences in the comparative effectiveness and safety of CVD pharmacotherapy. Our specific aims are to: 1) identify conditions under which common analytic methods are likely to produce biased estimates of treatment effects in men and/or women; 2) develop innovative alternative analytic methods that validly and reliably evaluate sex differences; 3) test the performance of these innovative methods and the standard analytic approaches in a large scale Monte Carlo simulation study; and 4) apply and validate methods for quantifying sex differences in the safety and effectiveness of pharmacotherapy. We will use national administrative claims data supplemented by survey and laboratory data enabling us to deliver timely answers to these urgent clinical questions with immediate implications for clinical practice. Moreover, the innovative and novel analytic methods we will develop and implement in this proposal will be applicable broadly to the study of other important patient subgroups (such as those defined by race, ethnicity and age), and will be equally relevant across the full spectrum of health conditions and their clinical management.