Moving from significance to real-world meaning: methods for interpreting change in clinical outcome assessment scores

Clinical outcome assessments (COAs) require evidence not only of reliability, validity, and ability to detect change, but also a definition of what constitutes a meaningful change on the instrument. The responder definition specifies the amount of change on the COA that may be interpreted as a treatment benefit and is critical for interpreting what constitutes a meaningful change on the COA scores. However, the literature that describes methods for developing and applying responder definitions can be difficult to navigate. Clear and concise guidelines regarding which methods to apply under what circumstances and how to interpret the results are lacking. This article provides a guide to the variety of available methods and issues that should be considered when establishing responder definitions for interpreting meaningful changes in COA scores. An overview is provided for selecting anchors, developing study designs, planning psychometric analyses, using psychometric results to set responder thresholds, and applying responder thresholds in demonstrating treatment efficacy. There are a variety of anchor-based methods for consideration, but they all rely on a preference for strongly related and easily interpretable anchors. The benefits of applying multiple anchors and multiple analytic methods are discussed. The process of triangulation can synthesize results across multiple sources to gain confidence in a proposed responder definition. Though a link to meaningfulness from the patient's perspective is absent, distribution-based methods provide lower bound estimates of score precision and have a role in triangulation. Responder definitions are typically required within regulatory review, but their application may differ across clinical trial programs. By careful planning of anchor selection, study design, and psychometric methods, COA researchers can establish defensible responder thresholds that ultimately aid patients and clinicians in making informed treatment decisions.