All Times EDT
Keywords: Real world data, real world evidence, randomized controlled clinical trials
Randomized controlled clinical trials (RCTs) are the gold standard for evaluating the safety and efficacy of medical products, but in many cases their costs, duration, limited generalizability, and ethical or technical feasibility have caused some to look for real-world (RW) studies as alternatives. Most recently, especially with the release of the FDA RWE Framework in Dec. 2018, we have seen increasing use of RW evidence from a variety of RW data sources in the context of preauthorization regulatory decision making to address key clinical questions. Examples of such use include the utility of external controls as a possible type of control arm for single-arm trials and analysis of existing RW data to support label expansions. However, RW studies and the use of external controls have some inherent limitations as compared to RCTs due to the lack of randomization and blinding.
The ASA BIOP Section chartered its RWE Scientific Working Group (SWG) in 2018 to facilitate using statistics to generate RWE designed to inform regulatory decisions of medical products. In its first phase, the SWG was divided into two workstreams and both reviewed biostatistical methods related to RWE generation for two different regulatory purposes: (I) to modify existing labels of medical products and (II) to inform better clinical study designs and analyses using external control. Both Workstreams have summarized their findings in three papers, which were submitted for publication. In this talk, we will discuss the output from SWG. The focus of the talk is to lay out some key considerations and methodologies in the design and analysis of RW studies, to minimize and mitigate biases and confounding. Challenges and opportunities will also be discussed, along with future work.