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Activity Number: 198 - Innovations in Patient-Focused Clinical Trials
Type: Contributed
Date/Time: Monday, August 8, 2022 : 2:00 PM to 3:50 PM
Sponsor: Biopharmaceutical Section
Abstract #323076
Title: Approaches for Understanding Treatment Effects with Health Measures: The Meaningfulness of Expected Scores Versus Expected Differences in Scores
Author(s): Laura Lee Johnson* and Fraser Bocell and Monica Morell and Kevin Weinfurt
Companies: U.S. Food and Drug Administration and US FDA/CDRH and U.S. Food and Drug Administration and Duke University
Keywords: clinical outcome assessments (COA); patient reported outcomes (PRO); clinical trials; meaningful difference

Clinical trials often compare randomized groups on endpoints based on clinical outcome assessments (COAs) such as a patient-reported outcome measures. Treatment effects defined in terms of COA scores may be difficult to interpret when a COA’s metric is unfamiliar. Two approaches can help translate treatment effects into the language of patients’ experiences. The Meaningful Differences approach identifies the difference (D) between COA scores corresponding to a difference between any two expected experiences patients regard as meaningful. D is then used to evaluate the meaningfulness of a treatment effect. The Meaningful Scores approach attempts to translate COA scores into patient experiences. For example, scores may be translated into activities patients with each score could do without any difficulty. Next, for any given patient (including the average patient) the COA scores expected under treatment and control conditions are translated into corresponding patient experiences, which can help patients and other stakeholders appreciate the magnitude of the expected treatment effect. Each method has strengths and limitations that may depend on the type of COA and the score metric.

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

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