Comparison of the PROMIS Preference Score (PROPr) and EQ-5D-5L Index Value in General Population Samples in the United Kingdom,France, and Germany |
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| Institution: | 1. Department of Psychosomatic Medicine, Center for Internal Medicine and Dermatology, Charité – Universitätsmedizin Berlin, Berlin, Germany;2. Department of Symptom Research, MD Anderson Cancer Center, University of Houston, TX, USA;3. Health Services & Policy Research Group, University of Exeter, Exeter, England, UK;4. NIHR Peninsula Collaboration for Leadership in Applied Health Research and Care, Exeter, England, UK;5. Department of Quantitative Health Sciences, University of Massachusetts Medical School, Worcester, MA, USA;1. School of Population Health, Curtin University, Perth, Australia;2. Department of Community Medicine, University of Tromsø, Tromsø, Norway;3. Division of Health Services, Norwegian Institute of Public Health, Oslo, Norway;1. Department of Social and Preventative Medicine, Université Laval, Québec City, Québec, Canada;2. Population Health and Optimal Health Practices Research Unit, Trauma – Emergency – Critical Care Medicine, Centre de Recherche du CHU de Québec (Hôpital de l’Enfant-Jésus), Université Laval, Québec City, Québec, Canada;3. Department of Family Medicine and Emergency Medicine, Université Laval, Québec City, Québec, Canada;4. VITAM-Centre de recherche en santé durable, Université Laval, Québec City, Québec, Canada;5. Centre intégré de santé et de services sociaux de Chaudière-Appalaches, Université Laval, Québec City, Québec, Canada;6. Division of Critical Care Medicine, Department of Anesthesiology and Critical Care Medicine, Université Laval, Québec City, Québec, Canada;7. Department of Critical Care Medicine, Medicine and Community Health Sciences, O’Brien Institute for Public Health, University of Calgary, Calgary, Alberta, Canada;8. Department of Medicine, Université de Montréal, Québec City, Québec, Canada;9. Division of Health Policy and Management, Department of Public Health Sciences, University of California, Davis, Davis, CA, USA;10. School of Public Health and Preventive Medicine at Monash University, Melbourne, Victoria, Australia;11. Uniformed Services University of the Health Sciences Annapolis, Bethesda, MD, USA;12. School of Health and Related Research, Sheffield, England, UK;1. Catalan Health Service (CatSalut), Barcelona, Spain;2. Digitalization for the Sustainability of the Healthcare System (DS3), Sistema de Salut de Catalunya, Barcelona, Spain;3. Catalan Institute of Oncology, L’Hospitalet de Llobregat, Barcelona, Spain;4. Blood and Tissue Bank (BST), Barcelona, Spain;1. Services in Health Economics SHE, Brussels, Belgium;2. Section Medical Psychology and Psychotherapy, Department of Psychiatry, Erasmus MC, Rotterdam, The Netherlands;3. Acaster Lloyd Consulting Ltd, London, England, UK;4. Science Policy and Research Programme, National Institute for Health and Care Excellence, London, England, UK;1. Maths in Health, Rotterdam, the Netherlands;2. Department of Health Economics and Health Care Management, School of Public Health, Bielefeld University, Bielefeld, Germany;3. National Perinatal Epidemiology Unit, Nuffield Department of Population Health, University of Oxford, Oxford, England, UK;1. Nestle Health Science, Bridgewater, NJ, USA;2. Rush University, Chicago, IL, USA;3. Instituto Nacional de Câncer, Petrópolis, Brazil;4. Duke Center for Applied Genomics & Precision Medicine, Department of Medicine, Duke University School of Medicine, Durham, NC;5. Durham VA Health Care System, Durham, NC, USA;6. ISPOR, Lawrenceville, NJ, USA;7. University of Macau, Taipa, Macau;8. Abbott, Columbus, OH, USA;9. University of New Mexico, Albuquerque, NM, USA;10. Istanbul Technical University, Istanbul, Turkey;11. Texas A&M University, College Station, TX, USA;12. York Health Economics Consortium, York, England, UK;13. Changi General Hospital, Singapore;14. Erasmus University Rotterdam, Rotterdam, The Netherlands |
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| Abstract: | ObjectivesThe Patient-Reported Outcome Measurement Information System (PROMIS) Preference score (PROPr) can be used to assess health state utility (HSU) and estimate quality-adjusted life-years in cost-effectiveness analyses. It is based on item response theory and promises to overcome limitations of existing HSU scores such as ceiling effects. The PROPr contains 7 PROMIS domains: cognitive abilities, depression, fatigue, pain, physical function, sleep disturbance, and ability to participate in social roles and activities. We aimed to compare the PROPr with the 5-level EQ-5D (EQ-5D-5L) in terms of psychometric properties using data from 3 countries.MethodsWe collected PROMIS-29 profile and EQ-5D-5L data from 3 general population samples (United Kingdom = 1509, France = 1501, Germany = 1502). Given that cognition is not assessed by the PROMIS-29, it was predicted by the recommended linear regression model. We compared the convergent validity, known-groups construct validity, and ceiling and floor effects of the PROPr and EQ-5D-5L.ResultsThe mean PROPr (0.48, 0.53, 0.48; P<.01) and EQ-5D-5L scores (0.82, 0.85, 0.83; P<.01) showed significant differences of similar magnitudes (d = 0.34; d = 0.32; d = 0.35; P<.01) across all samples. The differences were invariant to sex, income, occupation, education, and most conditions but not for age. The Pearson correlation coefficients between both scores were r = 0.74, r = 0.69, and r = 0.72. PROPr’s ceiling and floor effects both were minor to moderate. The EQ-5D-5L’s ceiling (floor) effects were major (negligible).ConclusionsBoth the EQ-5D-5L and the PROPr assessed by the PROMIS-29 show high validity. The PROPr yields considerably lower HSU values than the EQ-5D-5L. Consequences for quality-adjusted life-year measurements should be investigated in future research. |
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| Keywords: | EQ-5D health-related quality of life incremental cost-effectiveness ratio outcome measures patient-reported outcomes Patient-Reported Outcome Measurement Information System Preference score quality-adjusted life-year |
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