Mercieca-Bebber, R., King, M. T., Calvert, M. J., et al. (2018). The importance of patient-reported outcomes in clinical trials and strategies for future optimization. Patient Relat Outcome Meas, 9, 353–367. https://doi.org/10.2147/PROM.S156279
Article PubMed PubMed Central Google Scholar
Coens, C., Pe, M., Dueck, A. C., et al. (2020). International standards for the analysis of quality-of-life and patient-reported outcome endpoints in cancer randomised controlled trials: Recommendations of the SISAQOL Consortium. The Lancet Oncology, 21, e83–e96. https://doi.org/10.1016/S1470-2045(19)30790-9
Collister, D., Bangdiwala, S., Walsh, M., et al. (2021). Patient reported outcome measures in clinical trials should be initially analyzed as continuous outcomes for statistical significance and responder analyses should be reserved as secondary analyses. Journal of Clinical Epidemiology, 134, 95–102. https://doi.org/10.1016/j.jclinepi.2021.01.026
Qian, Y., Walters, S. J., Jacques, R., & Flight, L. (2021). Comprehensive review of statistical methods for analysing patient-reported outcomes (PROs) used as primary outcomes in randomised controlled trials (RCTs) published by the UK’s Health Technology Assessment (HTA) journal (1997–2020). British Medical Journal Open, 11, e051673. https://doi.org/10.1136/bmjopen-2021-051673
Abugov, R., Clark, J., Higginbotham, L., et al. (2023). Should responder analyses be conducted on continuous outcomes? Pharmaceutical Statistics, 22, 312–327. https://doi.org/10.1002/pst.2273
Senn, S. (2003). Disappointing dichotomies. Pharmaceutical Statistics, 2, 239–240. https://doi.org/10.1002/pst.90
Terwee, C. B., Peipert, J. D., Chapman, R., et al. (2021). Minimal important change (MIC): A conceptual clarification and systematic review of MIC estimates of PROMIS measures. Quality of Life Research, 30, 2729–2754. https://doi.org/10.1007/s11136-021-02925-y
Article PubMed PubMed Central Google Scholar
Trigg, A., Lenderking, W. R., & Boehnke, J. R. (2023). Introduction to the special section: Methodologies and considerations for meaningful change. Quality of Life Research, 32, 1223–1230. https://doi.org/10.1007/s11136-023-03413-1
Coon, C. D., & Cook, K. F. (2018). Moving from significance to real-world meaning: Methods for interpreting change in clinical outcome assessment scores. Quality of Life Research, 27, 33–40. https://doi.org/10.1007/s11136-017-1616-3
FDA. (2009). Guidance for industry patient-reported outcome measures: Use in medical product development to support labeling claims.
Vanier, A., Leroy, M., & Hardouin, J-B. (2022). Toward a rigorous assessment of the statistical performances of methods to estimate the minimal important difference of patient-reported outcomes: A protocol for a large-scale simulation study. Methods, 204, 396–409. https://doi.org/10.1016/j.ymeth.2022.02.006
Article CAS PubMed Google Scholar
Bjorner, J. B., Terluin, B., Trigg, A., et al. (2022). Establishing thresholds for meaningful within-individual change using longitudinal item response theory. Quality of Life Research. https://doi.org/10.1007/s11136-022-03172-5
Article PubMed PubMed Central Google Scholar
Vanier, A., Sébille, V., Blanchin, M., & Hardouin, J.-B. (2021). The minimal perceived change: A formal model of the responder definition according to the patient’s meaning of change for patient-reported outcome data analysis and interpretation. BMC Medical Research Methodology, 21, 128. https://doi.org/10.1186/s12874-021-01307-9
Article PubMed PubMed Central Google Scholar
Staunton, H., Willgoss, T., Nelsen, L., et al. (2019). An overview of using qualitative techniques to explore and define estimates of clinically important change on clinical outcome assessments. Journal of Patient-Reported Outcomes, 3, 16. https://doi.org/10.1186/s41687-019-0100-y
Article PubMed PubMed Central Google Scholar
Sabah, S. A., Alvand, A., Beard, D. J., & Price, A. J. (2022). Minimal important changes and differences were estimated for Oxford hip and knee scores following primary and revision arthroplasty. Journal of Clinical Epidemiology, 143, 159–168. https://doi.org/10.1016/j.jclinepi.2021.12.016
Bell, M. L., Dhillon, H. M., Bray, V. J., & Vardy, J. L. (2018). Important differences and meaningful changes for the Functional Assessment of Cancer Therapy-Cognitive function (FACT-Cog). Journal of Patient-Reported Outcomes, 2, 48. https://doi.org/10.1186/s41687-018-0071-4
Article PubMed Central Google Scholar
McLeod, L. D., Cappelleri, J. C., & Hays, R. D. (2016). Best (but oft-forgotten) practices: Expressing and interpreting associations and effect sizes in clinical outcome assessments1. The American Journal of Clinical Nutrition, 103, 685–693. https://doi.org/10.3945/ajcn.115.120378
Article CAS PubMed PubMed Central Google Scholar
Musoro, Z. J., Hamel, J-F., Ediebah, D. E., et al. (2018). Establishing anchor-based minimally important differences (MID) with the EORTC quality-of-life measures: A meta-analysis protocol. British Medical Journal Open, 8, e019117. https://doi.org/10.1136/bmjopen-2017-019117
Dworkin, R. H., Turk, D. C., McDermott, M. P., et al. (2009). Interpreting the clinical importance of group differences in chronic pain clinical trials: IMMPACT recommendations. Pain, 146, 238–244. https://doi.org/10.1016/j.pain.2009.08.019
Smith, S. M., Dworkin, R. H., Turk, D. C., et al. (2020). Interpretation of chronic pain clinical trial outcomes: IMMPACT recommended considerations. Pain, 161, 2446–2461. https://doi.org/10.1097/j.pain.0000000000001952
Article PubMed PubMed Central Google Scholar
Holland, P. W. (2002). Two measures of change in the gaps between the CDFs of test-score distributions. Journal of Educational and Behavioral Statistics, 27, 3–17. https://doi.org/10.3102/10769986027001003
R Core Team. (2023). R: A language and environment for statistical computing.
Bingham, C. O. III, Butanis, A. L., Orbai, A. M., et al. (2021). Patients and clinicians define symptom levels and meaningful change for PROMIS pain interference and fatigue in RA using bookmarking. Rheumatology, 60, 4306–4314. https://doi.org/10.1093/rheumatology/keab014
Article PubMed PubMed Central Google Scholar
Cocks, K., King, M. T., Velikova, G., et al. (2011). Evidence-based guidelines for determination of sample size and interpretation of the European Organisation for the Research and Treatment of Cancer Quality of Life Questionnaire Core 30. Journal of Clinical Oncology, 29, 89–96. https://doi.org/10.1200/JCO.2010.28.0107
Cook, J. A., Julious, S. A., Sones, W., et al. (2018). DELTA2 guidance on choosing the target difference and undertaking and reporting the sample size calculation for a randomised controlled trial. Trials, 19, 606. https://doi.org/10.1186/s13063-018-2884-0
Article PubMed PubMed Central Google Scholar
Ellis, L. M., Bernstein, D. S., Voest, E. E., et al. (2014). American Society of Clinical Oncology Perspective: Raising the bar for clinical trials by defining clinically meaningful outcomes. JCO, 32, 1277–1280. https://doi.org/10.1200/JCO.2013.53.8009
Cherny, N. I., Sullivan, R., Dafni, U., et al. (2015). A standardised, generic, validated approach to stratify the magnitude of clinical benefit that can be anticipated from anti-cancer therapies: The European Society for Medical Oncology Magnitude of Clinical Benefit Scale (ESMO-MCBS). Annals of Oncology, 26, 1547–1573. https://doi.org/10.1093/annonc/mdv249
留言 (0)