DCRI Think Tank Paper Looks to Future of Pragmatic Clinical Trials

Attendees to a January 2019 DCRI Think Tank outlined recommendations for optimizing pragmatic clinical trials and weighing risks and benefits of innovative trial designs.

While using real-world data to conduct pragmatic clinical trials has the potential to make research more efficient with more generalizable results, these benefits must be weighed against potential difficulties of ensuring data integrity and completeness, write the authors of a paper recently published in Therapeutic Innovation & Regulatory Science.

The paper shares takeaways from a 2019 DCRI Think Tank, “Monitoring and Analyzing Data from Pragmatic Streamlined Randomized Clinical Trials.” The meeting, which was held in Washington, D.C., convened a group of stakeholders from academia, industry, professional organizations, regulatory bodies, government agencies, and patient advocates to discuss best practices and a path forward for pragmatic clinical trials. The DCRI Think Tank was chaired by DCRI’s Lesley Curtis, PhD, and Susan Ellenberg, PhD, of the University of Pennsylvania, with a significant contribution from DCRI’s Frank Rockhold, PhD.

The paper, which was led by the DCRI Think Tank fellow Trevor Lentz, PT, PhD, MPH—who is now a DCRI faculty member—outlined the group’s discussions on many topics surrounding pragmatic clinical trials, including study design, reducing bias, and selecting data sources.

Attendees to the DCRI Think Tank also identified opportunities to ensure the quality, safety, and viability of pragmatic clinical trials so that they can continue to be implemented and conducted to improve patient health. These recommendations are as follows:

  • Ask precise questions and select the level of pragmatism that is appropriate to answer the question.
  • Optimize data quality by keeping quality at top of mind during the design phase of the trial.
  • Focus on the primary endpoints during data capture to maximize the trial’s chances of success and minimize operational costs.
  • Innovate on data capture mechanisms to improve data quality and completeness and to improve on patient-centeredness.
  • Promote adherence to study protocol, which is not inconsistent with the goals of a pragmatic trial.
  • Provide training to trial operations staff so they can evolve to focus on data science and informatics.

Each of these recommendations requires collaboration among investigators, sponsors, health care systems, and regulators. By collaborating and sharing learnings, improvements can be made earlier in the planning and design of future pragmatic clinical trials.

Additional DCRI contributors to this paper include Adrian Hernandez, MD, MHS, and Myles Wolf, MD, MMSc.