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Objectives: The objective of this research was to generate psychometric evidence supporting the myasthenia gravis (MG) symptoms patient-reported outcome (PRO) scales as a fit-for-purpose measure of severity of core symptoms of MG and provide information allowing their meaningful interpretation using data from a phase 3 study in MG. Methods: Data from the MycarinG study, a phase 3 study of rozanolixizumab in patients with generalized MG who experience moderate to severe symptoms (ClinicalTrials.gov Identifier: NCT03971422) were analyzed with both classical test theory (CTT) and Rasch measurement theory (RMT). Meaningful within-individual change and group-level meaningful change were estimated for three MG Symptoms PRO scales using anchor- and distribution-based methods. Anchor-based methods used patient global impression of severity (PGIS) and change (PGIC) in MG symptoms as anchors. Results: Good measurement properties of the MG Symptoms PRO scales were shown in the sample of 200 participants: good to excellent reliability (test-retest and internal consistency reliability) and validity (associations between items and scores within the MG Symptoms PRO scales and between the MG Symptoms PRO scores and other clinical outcomes-MG ADL, QMG score, MGC score, and MGFA classes-were as expected); and the items showed good coverage of the continuum and fit to the Rasch model. Triangulation of the anchor- and distribution-based method results led to the definition of clinically meaningful within-patient improvement in scores for Muscle Weakness Fatigability (-16.67), Physical Fatigue (-20.00), and Bulbar Muscle Weakness (-20.00), with associated ranges. Benchmarks are also proposed for the interpretation of group-level results. Conclusion: The strong psychometric performance of the MG Symptoms PRO scales and the information generated to guide its interpretation supports its use in clinical trials for demonstrating the clinical benefits of new treatments targeting core symptoms of MG (muscle weakness fatigability, physical fatigue, bulbar muscle weakness, respiratory muscle weakness, and ocular muscle weakness).
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BACKGROUND: The patient-reported outcomes version of the Common Terminology Criteria for Adverse Events (PRO-CTCAE) is used to assess symptomatic adverse events in oncology trials. Currently, no standard for PRO-CTCAE analysis exists. METHODS: Key methods of descriptive analysis and longitudinal modeling using PRO-CTCAE data from an oncology clinical trial, DRiving Excellence in Approaches to Multiple Myeloma-2 (DREAMM-2), a phase II trial of belantamab mafodotin in multiple myeloma (NCT03525678), were explored. Descriptive methods included maximum postbaseline ratings, mean change over time, ratings above a predefined cutoff, line graphs, and stacked bar charts to illustrate patient-reported adverse events at one timepoint or dynamics over time. Analysis methods involving modeling over time included toxicity over time (ToxT) (repeated measurement model, time-to-event, area under the curve analyses), generalized estimating equations (GEE), and ordinal log-linear models (OLLMs). RESULTS: Visualizations of PRO-CTCAE data highlighted different aspects of the data. Selection of the appropriate visualization will depend on the audience and message to be conveyed. Consistent results were obtained by all modeling approaches; no difference was found between dose groups of the DREAMM-2 study in any PRO-CTCAE item by the ToxT approach or the more sophisticated GEE and OLLM methods. Interpretation of GEE results was the most challenging. OLLM supported the interval nature of the PRO-CTCAE response scale in the DREAMM-2 study. All modeling approaches account for multiple testing (driven by the number of items). CONCLUSIONS: Descriptive analyses and longitudinal modeling approaches are complementary approaches to presenting PRO-CTCAE data. In modeling, the ToxT approach may be a good compromise compared with more sophisticated analyses.