On the use of meaningful score regions to interpret treatment effects on continuous clinical outcome assessments
TL;DR
It is concluded that using the maximum MSR width as a benchmark may fail to detect meaningful treatment effects in practice, and suggests alternative approaches to evaluate treatment effects against MSRs, describing the expected outcome within each arm in terms of the probabilities of MSR membership.
Abstract
Clinical outcome assessments (COAs), such as patient-reported outcomes (PROs), are faced with an interpretability issue due to a variety of score metrics being employed. Therefore, evidence linking COA scores to interpretable patient experiences is necessary to judge the extent to which the results of COA-based clinical trial endpoints are meaningful. The fourth Patient-Focused Drug Development guidance, published in draft form by the FDA in 2023, proposes the use of meaningful score regions (MSRs) to divide COA scores into more easily interpretable categories (e.g. severity-based MSRs of'none','mild','moderate'and'severe'). A recommendation is to compare the magnitude of estimated treatment effects for continuous COA scores (e.g. the difference in mean change from baseline between two treatment groups) to the maximum MSR width. In this article we explore this recommendation further, through historical evidence and simulations, and conclude that using the maximum MSR width as a benchmark may fail to detect meaningful treatment effects in practice. We suggest alternative approaches to evaluate treatment effects against MSRs, describing the expected outcome within each arm in terms of the probabilities of MSR membership.