Dependency and health utilities in stroke

Data to inform cost-effectiveness analyses

on behalf of the VISTA Collaborators

Research output: Contribution to journalArticle

7 Citations (Scopus)

Abstract

Introduction: 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.

Original languageEnglish (US)
Pages (from-to)70-76
Number of pages7
JournalEuropean Stroke Journal
Volume2
Issue number1
DOIs
StatePublished - Mar 1 2017

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Cost-Benefit Analysis
Stroke
Health
National Institutes of Health (U.S.)
Nonparametric Statistics
Least-Squares Analysis
Quality of Life

All Science Journal Classification (ASJC) codes

  • Clinical Neurology
  • Cardiology and Cardiovascular Medicine

Cite this

Dependency and health utilities in stroke : Data to inform cost-effectiveness analyses. / on behalf of the VISTA Collaborators.

In: European Stroke Journal, Vol. 2, No. 1, 01.03.2017, p. 70-76.

Research output: Contribution to journalArticle

on behalf of the VISTA Collaborators. / Dependency and health utilities in stroke : Data to inform cost-effectiveness analyses. In: European Stroke Journal. 2017 ; Vol. 2, No. 1. pp. 70-76.
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abstract = "Introduction: 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.",
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AU - on behalf of the VISTA Collaborators

AU - Ali, Myzoon

AU - MacIsaac, Rachael

AU - Quinn, Terence J.

AU - Bath, Philip M.

AU - Veenstra, David L.

AU - Xu, Yaping

AU - Brady, Marian C.

AU - Patel, Anita

AU - Lees, Kennedy R.

AU - Lees, K. R.

AU - Alexandrov, A.

AU - Bath, P. M.

AU - Bluhmki, E.

AU - Bornstein, N.

AU - Chen, C.

AU - Claesson, L.

AU - Davis, S. M.

AU - Alexandrov, Andrei

AU - Diener, H. C.

AU - Fisher, M.

AU - Ginsberg, M.

AU - Gregson, B.

AU - Grotta, J.

AU - Hacke, W.

AU - Hennerici, M. G.

AU - Hommel, M.

AU - Kaste, M.

AU - Lyden, P.

AU - Marler, J.

AU - Muir, K.

AU - Venketasubramanian, N.

AU - Sacco, R.

AU - Shuaib, A.

AU - Teal, P.

AU - Wahlgren, N. G.

AU - Warach, S.

AU - Weimar, C.

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N2 - Introduction: 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.

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