Legislative and technological advancements over the past decade have given rise to the proliferation of healthcare data generated from routine clinical practice, often referred to as real-world data (RWD). These data have piqued the interest of healthcare stakeholders due to their potential utility in generating evidence to support clinical and regulatory decision making. In the oncology setting, studies leveraging RWD offer distinct advantages that are complementary to randomized controlled trials (RCTs). They also permit the conduct of investigations that may not be possible through prospective designs due to ethics or feasibility. Despite its promise, the use of RWD for the generation of clinical evidence remains controversial due to concerns of unmeasured confounding and other sources of bias that must be carefully addressed in the study design and analysis. To facilitate a better understanding of when RWD can provide reliable conclusions on drug effectiveness, we seek to conduct 10 RWD-based studies that emulate RCTs in oncology using a systematic, protocol-driven approach described herein. Results of this investigation will help inform clinical, scientific, and regulatory stakeholders on the applications of RWD in the context of product labeling expansion, drug safety, and comparative effectiveness in oncology.
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