The development of these minimum measurement standards is intended to promote the appropriate use of PRO measures to inform PCOR and CER, which in turn can improve the effectiveness and efficiency of healthcare delivery. A next step is to expand these minimum standards to identify best practices for selecting decision-relevant PRO measures.

factor analysis, higher-order factor models, hierarchical factor models, bi-factor solutions, general factor, model equivalence,

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.