Patient-Centered Identification of Meaningful Regulatory Endpoints for Medical Devices to Treat Parkinson’s Disease (PCOR Project Aim 1 Paper)

Jul 2, 2021Clinical, Discovery & Ideation, Invention & Prototyping, Patient Centered Outcomes Research (PCOR), Pre-Clinical, Regulatory Decision

Patient Introduction

A growing body of literature has developed identifying outcomes that matter to patients. The study that these published articles (Aims 1, 2 & 3 of MDIC’s PCOR project) are based on demonstrates an approach to identifying outcomes of medical devices for Parkinson’s disease that are meaningful to patients and regulators. This approach is of interest to patients who seek to provide input to the design of medical device clinical trials to ensure that what matters to patients is incorporated into study endpoints. Although Parkinson’s disease was the disease focused on for this study, the approach can be used to study patient perspectives about other disease or treatment areas. This paper summarizes Aim 1 of the project, describing the process that was used to identify nine specific aspects of potential treatments for Parkinson’s disease that should be measured in a clinical trial for a medical device for these patients.

Summary

Parkinson’s disease (PD) is a neurodegenerative condition, causing motor, cognitive, psychological, somatic, and autonomic symptoms. This article, published in the journal MDM Policy & Practice describes Aim 1 of the MDIC Parkinson’s disease PCOR project, in which nine meaningful patient-centric attributes were identified for use in clinical trial design and quantitative patient preference studies. These nine attributes were benefits and risks related to therapeutics for Parkinson’s disease as well as time until a medical device is available for patient use and number of oral medicines taken each day to treat Parkinson’s disease and their side effects. This prospective approach identified meaningful and relevant benefits, risks, and other considerations that may be used for clinical trial design and quantitative patient preference studies.