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Activity Number: 57 - Nonparametric Modeling I
Type: Contributed
Date/Time: Sunday, August 8, 2021 : 3:30 PM to 5:20 PM
Sponsor: Section on Nonparametric Statistics
Abstract #317704
Title: Nonparametric Analysis of Patient-Reported Outcomes Using Compartmentalization Method
Author(s): Saryet Kucukemiroglu* and Manasi Sheth
Companies: FDA and FDA
Keywords: patient reported outcomes; non-parametric; compartmentalization; categorical data
Abstract:

In a public health regulatory setting, it is important for patients to have access to high-quality, safe, and effective medical devices. It is necessary to partner with patients by incorporating the patient perspective as evidence in the decision-making process, including both patient preference information (PPI) and patient-reported outcomes (PROs). PROs are often relevant in assessing diagnostic evaluations and can be used to capture a patient's everyday experience with a medical device, including experience outside of the clinician's office and the effects of treatment on a patient's activities of daily living. Furthermore, in some cases, PRO measures enable us to measure important health status information that cannot yet be detected by other measures, such as pain. To be useful to patients, researchers, and decision makers, PROs must undergo a validation process to support the accuracy and reliability of measurements from a device. Here, we present a novel two-stage non-parametric approach for analyzing PROs using compartmentalization method. We use two examples of diagnostic medical devices to test this approach.


Authors who are presenting talks have a * after their name.

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