Using Patient Preference Information in the Design of Clinical Trials Framework
Patient Introduction
The Using Patient Preference Information in the Design of Clinical Trials (PPI-CT) Framework is focused on providing medical device clinical trial sponsors and the broader clinical trial community an actionable set of learnings and compendium of best practice information on approaches for integrating patient preference information (PPI) into clinical trial design. Patient-centered medical device clinical trials facilitate development of innovative medical products that can make a direct and meaningful impact on the lives of patients. A patient-centered approach to clinical trial design has many important benefits, including the potential to improve patient experience in clinical trials, accelerate enrollment, improve retention and long-term follow-up, improve data quality, assure trials are focused on outcomes that matter most to patients, support regulatory decision-making activities, assist in payer evaluations of value of new medical devices, and help ensure new technological innovation is focused on bringing the most benefit to patients. Patients may be interested in this information to better understand the opportunities and recommendations for sponsors to integrate patient preferences into the design of their clinical trials.
Summary
This PPI-CT Framework provides detailed information for sponsors to consider when seeking to engage the appropriate expertise and stakeholders (especially patient advocacy organizations) as they plan and execute patient preference studies to inform clinical trial design. The recommendations in this framework are derived from the input of an array of multi-stakeholder experts and a detailed review of five recent projects that have been distilled into case examples, including one in Parkinson’s disease, two in heart failure, one in mitral valve disease, and one in obesity.
One approach discussed in this report to incorporate PPI in the development of patient-centered significance level thresholds is use of a Bayesian decision analysis (BDA) framework. The BDA framework provides a systematic, quantitative, and transparent approach to setting the statistical significance threshold for a clinical trial.
The PPI-CT Framework provides a body of information and case examples to help move the device field forward toward more patient-centered clinical trials. As the body of evidence supporting the feasibility of these approaches grows, MDIC envisions that all stakeholders will develop additional confidence and comfort with using PPI to design the most streamlined and efficient clinical trials possible in the development of medical devices, yielding outcomes that systematically include the benefit-risk preferences of patients.