Patient-Centered Clinical Trial Design Tool for Heart Failure Devices Methods Report
Clinical trials are designed based on a statistical approach to gain confidence that a product is safe and effective. These statistical considerations, however, traditionally have not considered patients’ willingness to accept risk. For example, some patients may be willing to accept a greater risk that a device will not work for them, in exchange for the opportunity that they might benefit. Patients may also have a broader set of characteristics in mind for what would be a meaningful benefit than what has traditionally been measured in clinical trials. This report helps to advance the discussion among experts about how to best incorporate those patient preferences, using a technical model for thinking differently when designing a trial. Patients may be interested in this report to better understand how statistical methods can reflect what matters to patients in the context of medical device clinical trial design.
MDIC engaged QLS Advisors (statistical modeling and clinical trial design experts) to analyze data from the MDIC Heart Failure Patient Preference Study (PPI) to determine optimal statistical significance thresholds in a future medical device clinical trial. This report describes the use of a Bayesian decision analysis (BDA) Framework to demonstrate how quantified information about the maximum level of risk patients living with heart failure would be willing to accept to achieve different potential therapeutic benefits can impact the statistical significance threshold in a clinical trial.