Andrew Trigg1, Philip Griffiths2. 1. Adelphi Values, Adelphi Mill, Bollington, Cheshire, SK10 5JB, UK. andrew.trigg@adelphivalues.com. 2. IQVIA, Reading, Berkshire, UK.
Abstract
PURPOSE: The notion of what constitutes meaningful differences or changes in patient-reported outcome scores is represented by meaningful change thresholds (MCTs). Applying multiple methods to estimate MCTs inevitably results in a range of estimates; however, a single estimate or small range is sought in practice to enable consistent interpretation of scores. While current recommendations for triangulation are appropriate in principle, the vital step of moving from all estimates to a value or small range lacks clarity and is subjective in nature. This article aims to review current triangulation approaches and provide more robust recommendations than what is currently available. METHODS: Current approaches to perform triangulation are described and discussed. Anchor-based estimates are focussed upon due to their recognition as the most valid and developed approach. Recommendations for triangulation are provided. RESULTS: A correlation-weighted average of MCT estimates is recommended to triangulate multiple MCT estimates derived from a single study into a single value, where increased weighting is given to stronger anchor measures. The choice of method to triangulate estimates from several published studies is highly dependent on the availability of information within the publications. MCTs designed for between-group differences, within-group changes, and within-individual changes should be considered separately. CONCLUSION: The recommendations within this article provide a reliable and transparent approach to triangulation when a single value is sought, based on meta-analytic approaches. This approach is preferable to a simple mean of estimates where all are weighted equally, or through 'eyeballing' plotted estimates which is unreliable. We encourage researchers to adopt these methods, but to remain aware of the limitations within each method and further nuances in study design that result in heterogeneity. Sensitivity analyses with a range of plausible values are encouraged; however, the recommendations provide a suitable starting value for inferences. Unresolved issues in triangulation, requiring further exploration, are highlighted.
PURPOSE: The notion of what constitutes meaningful differences or changes in patient-reported outcome scores is represented by meaningful change thresholds (MCTs). Applying multiple methods to estimate MCTs inevitably results in a range of estimates; however, a single estimate or small range is sought in practice to enable consistent interpretation of scores. While current recommendations for triangulation are appropriate in principle, the vital step of moving from all estimates to a value or small range lacks clarity and is subjective in nature. This article aims to review current triangulation approaches and provide more robust recommendations than what is currently available. METHODS: Current approaches to perform triangulation are described and discussed. Anchor-based estimates are focussed upon due to their recognition as the most valid and developed approach. Recommendations for triangulation are provided. RESULTS: A correlation-weighted average of MCT estimates is recommended to triangulate multiple MCT estimates derived from a single study into a single value, where increased weighting is given to stronger anchor measures. The choice of method to triangulate estimates from several published studies is highly dependent on the availability of information within the publications. MCTs designed for between-group differences, within-group changes, and within-individual changes should be considered separately. CONCLUSION: The recommendations within this article provide a reliable and transparent approach to triangulation when a single value is sought, based on meta-analytic approaches. This approach is preferable to a simple mean of estimates where all are weighted equally, or through 'eyeballing' plotted estimates which is unreliable. We encourage researchers to adopt these methods, but to remain aware of the limitations within each method and further nuances in study design that result in heterogeneity. Sensitivity analyses with a range of plausible values are encouraged; however, the recommendations provide a suitable starting value for inferences. Unresolved issues in triangulation, requiring further exploration, are highlighted.
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