Clinical Trials Overview: From Explanatory to Pragmatic Clinical Trials

Clinical trials have been the bedrock of research to evaluate the safety and efficacy of new medical, surgical, or other interventions. Traditional explanatory clinical trials have aimed to explain a biological cause (new treatment) and effect (patient outcome) while controlling for many factors that might impact the evaluation, such as restricted eligibility criteria, frequent follow-up visits, and multiple clinical and laboratory measures. Despite the benefits of a well-controlled clinical trial, compromises have been made that can limit who might benefit from a new intervention, can increase complexity of the conduct of a trial, or that lead to excessively long durations of trials. An alternative approach to evaluate the effectiveness of an intervention is based on pragmatic clinical trials, which consider how an intervention affects a patient's condition in the real world, accounting for how to optimize an intervention within the operations of busy and diverse clinical practices. Although we describe explanatory and pragmatic trial designs as separate approaches, there is a continuum of approaches that intersect. Some key points are the need to maintain scientific rigor, increase efficiency of clinical trials operations, ensure that trial results can be generalized to a broad spectrum of patients, and balance the needs of real-world clinical care. Pragmatic trials can leverage technology and telecommunication strategies of decentralized trials to further reach underrepresented and underserved patients to close the health disparity gaps.& COPY; 2023 Mayo Foundation for Medical Education and Research. Published by Elsevier Inc. All rights reserved. & BULL; Mayo Clin Proc. 2023;98(8):1241-1253

Automated summary

Clinical trials are important for evaluating the safety and efficacy of new interventions. Traditional explanatory trials focus on exploring the biological causes and effects, while pragmatic trials consider real-world conditions and aim to optimize interventions in diverse clinical practices. It is essential to maintain scientific rigor, increase trial efficiency, ensure generalizability of results, and address health disparities through technology and decentralized approaches.