In recent years, the US FDA has become more critical of instruments used to measure patient-reported outcomes (PROs) in clinical trials. To facilitate decisions related to the approval of drugs, labels and promotional claims based on PROs, the FDA created the Study Endpoints and Label Development (SEALD) group. SEALD has developed a PRO guidance related to the use of PRO measures used to support drug approvals and label claims, including recommendations for establishing thresholds for meaningful change at the individual level (i.e., defining a responder). This article examines in detail the FDA-recommended methodology for defining a responder and analyzing responder-based PRO measure results. We also present other responder analysis approaches for consideration in furthering the precision and interpretation of this methodology.

Selection of a psychometric approach depends on many factors. Researchers should justify their evaluation method and consider the intended audience. If the instrument is being developed for descriptive purposes and on a restricted budget, a cursory examination of the CTT-based psychometric properties may be all that is possible. In a high-stakes situation, such as the development of a patient-reported outcome instrument for consideration in pharmaceutical labeling, however, a thorough psychometric evaluation including IRT or RMT should be considered, with final item-level decisions made on the basis of both quantitative and qualitative results.

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.

In patients with advanced melanoma in the CheckMate 066 study, baseline health-related quality of life (HRQoL) with nivolumab was maintained over time, with statistically significant and clinically meaningful improvements in some exploratory analyses, and no HRQoL improvements with dacarbazine. Added to the survival benefit of nivolumab, the benefit-to-risk ratio favors nivolumab over dacarbazine.

Interpreting change in scores on patient-reported outcome instruments is a key aspect of instrument development. Without interpretation guidelines, the clinical meaning of significant improvements observed within a treatment group cannot be ascertained. While the field has contemplated this topic for several decades, there remains inconsistency in terminology, methods, and application. Careful selection of methods can result in determining when change is meaningful, but researchers must keep an open mind to the methods that best fit their study and instrument. In many cases, anchor-based methods are appropriate, but the statistical model that evaluates them should be defensible (eg, linear regression, repeated-measures modeling, logistic regression). Sometimes, researchers must entertain the use of novel methods that may be more appropriate for their planned studies and instrument (eg, standard setting, exit interviews, conjoint analysis). The selection of the method is best supported by clear, transparent communication with the regulatory agency to ensure that the method can support its goals.