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dc.contributor.authorAli, Men_US
dc.contributor.authorMacIsaac, Ren_US
dc.contributor.authorQuinn, TJen_US
dc.contributor.authorBath, PMen_US
dc.contributor.authorVeenstra, DLen_US
dc.contributor.authorXu, Yen_US
dc.contributor.authorBrady, MCen_US
dc.contributor.authorPatel, Aen_US
dc.contributor.authorLees, KRen_US
dc.date.accessioned2016-12-16T09:53:00Z
dc.date.available2016-11-18en_US
dc.date.issued2017-03en_US
dc.date.submitted2016-11-25T11:24:33.582Z
dc.identifier.urihttp://qmro.qmul.ac.uk/xmlui/handle/123456789/18302
dc.description.abstractIntroduction: Health utilities (HU) assign preference weights to specific health states and are required for cost-effectiveness analyses. Existing HU for stroke inadequately reflect the spectrum of post-stroke disability. Using international stroke trial data, we calculated HU stratified by disability to improve precision in future cost-effectiveness analyses. Materials and methods: We used European Quality of Life Score (EQ-5D-3L) data from the Virtual International Stroke Trials Archive (VISTA) to calculate HU, stratified by modified Rankin Scale scores (mRS) at 3 months. We applied published value sets to generate HU, and validated these using ordinary least squares regression, adjusting for age and baseline National Institutes of Health Stroke Scale (NIHSS) scores. Results: We included 3858 patients with acute ischemic stroke in our analysis (mean age: 67.5 ± 12.5, baseline NIHSS: 12 ± 5). We derived HU using value sets from 13 countries and observed significant international variation in HU distributions (Wilcoxon signed-rank test p < 0.0001, compared with UK values). For mRS = 0, mean HU ranged from 0.88 to 0.95; for mRS = 5, mean HU ranged from -0.48 to 0.22. OLS regression generated comparable HU (for mRS = 0, HU ranged from 0.9 to 0.95; for mRS = 5, HU ranged from -0.33 to 0.15). Patients' mRS scores at 3 months accounted for 65-71% of variation in the generated HU. Conclusion: We have generated HU stratified by dependency level, using a common trial endpoint, and describing expected variability when applying diverse value sets to an international population. These will improve future cost-effectiveness analyses. However, care should be taken to select appropriate value sets.en_US
dc.description.sponsorshipThis study was supported by a grant from Genentech. MB and the NMAHP Research Unit are funded by the Chief Scientist Office, (CSO) Scottish Government’s Health and Social Care Directorate, Scotland.en_US
dc.format.extent70 - 76en_US
dc.languageengen_US
dc.language.isoenen_US
dc.relation.ispartofEur Stroke Jen_US
dc.subjectEQ-5Den_US
dc.subjectStrokeen_US
dc.subjectcost effectivenessen_US
dc.subjecthealth utilityen_US
dc.subjectmodified Rankin Scaleen_US
dc.subjectquality of lifeen_US
dc.subjecttrialen_US
dc.titleDependency and health utilities in stroke: Data to inform cost-effectiveness analyses.en_US
dc.typeArticle
dc.rights.holder(c) 2016 The Authors.
dc.identifier.doi10.1177/2396987316683780en_US
pubs.author-urlhttps://www.ncbi.nlm.nih.gov/pubmed/30009266en_US
pubs.issue1en_US
pubs.notesNot knownen_US
pubs.publication-statusPublisheden_US
pubs.volume2en_US
dcterms.dateAccepted2016-11-18en_US


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