Well-controlled and conducted randomized clinical trials (RCT) are viewed as the gold standard in the safety and effectiveness evaluation of medical products, including drugs, biological products and medical devices.  Observational (non-randomized) comparative studies also play an important role in medical product evaluation, due to ethical or practical reasons, in both pre-market and post-market regulatory settings. However, various biases could be introduced at every stage and into every aspect of the observational study, and adversely impact the interpretation of the study results. Among existing statistical techniques for addressing some of the challenging issues, propensity score methodology is one increasingly used in regulatory settings, due to its unique future of separating “study design” and “outcome analysis”.
 
This course will introduce the causal inference framework and propensity score methods (e.g. matching, stratification, and weighting), and highlight the principle and importance of prospective design of observational comparative studies to increase the integrity and the interpretability of outcome analysis results. Practical issues encountered in the application of the methodology in the regulatory settings will be presented, including but not limited to: study design process in regulatory submissions, specification of treatment effects of interest in treatment comparisons (average treatment effect (ATE) or average treatment effect on the treated (ATT), covariate identification and inclusion, control group selection/formation (a concurrent control, historical control or a control group extracted from national/international registry), sample size and power consideration. Some differences for implementing propensity score methodology will be delineated for studies with different purposes, for regulatory submissions or general comparative effectiveness research. For example, exclusion of treated patients with an investigational product should be discouraged in studies aimed at pre-market regulatory submissions.  These topics will be illustrated with examples based on regulatory review experience.

Instructors: 
Lilly Yue, PhD
Deputy Director, Division of Biostatistics, CDRH
FDA, United States

Diqiong Xie, PhD
Mathematical Statistician, Div. of Biometrics VII, Off. Biostatistics, OTS, CDER
FDA, United States

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