Journal of Clinical and Translational Science (Jan 2023)

The evolving role of data & safety monitoring boards for real-world clinical trials

  • Bryan J. Bunning,
  • Haley Hedlin,
  • Jonathan H. Chen,
  • Jody D. Ciolino,
  • Johannes Opsahl Ferstad,
  • Emily Fox,
  • Ariadna Garcia,
  • Alan Go,
  • Ramesh Johari,
  • Justin Lee,
  • David M. Maahs,
  • Kenneth W. Mahaffey,
  • Krista Opsahl-Ong,
  • Marco Perez,
  • Kaylin Rochford,
  • David Scheinker,
  • Heidi Spratt,
  • Mintu P. Turakhia,
  • Manisha Desai

DOI
https://doi.org/10.1017/cts.2023.582
Journal volume & issue
Vol. 7

Abstract

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Abstract Introduction: Clinical trials provide the “gold standard” evidence for advancing the practice of medicine, even as they evolve to integrate real-world data sources. Modern clinical trials are increasingly incorporating real-world data sources – data not intended for research and often collected in free-living contexts. We refer to trials that incorporate real-world data sources as real-world trials. Such trials may have the potential to enhance the generalizability of findings, facilitate pragmatic study designs, and evaluate real-world effectiveness. However, key differences in the design, conduct, and implementation of real-world vs traditional trials have ramifications in data management that can threaten their desired rigor. Methods: Three examples of real-world trials that leverage different types of data sources – wearables, medical devices, and electronic health records are described. Key insights applicable to all three trials in their relationship to Data and Safety Monitoring Boards (DSMBs) are derived. Results: Insight and recommendations are given on four topic areas: A. Charge of the DSMB; B. Composition of the DSMB; C. Pre-launch Activities; and D. Post-launch Activities. We recommend stronger and additional focus on data integrity. Conclusions: Clinical trials can benefit from incorporating real-world data sources, potentially increasing the generalizability of findings and overall trial scale and efficiency. The data, however, present a level of informatic complexity that relies heavily on a robust data science infrastructure. The nature of monitoring the data and safety must evolve to adapt to new trial scenarios to protect the rigor of clinical trials.

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