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Mapping EQ-5D Utility Scores from the PedsQL™ Generic Core Scales

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  • Kamran Khan
  • Stavros Petrou
  • Oliver Rivero-Arias
  • Stephen Walters
  • Spencer Boyle

Abstract

Our mapping algorithms provide an empirical basis for estimating health utilities in childhood when EQ-5D data are not available; they can be used to inform future economic evaluations of paediatric interventions. They are likely to be robust for populations comparable to our own (children aged 11–15 years in attendance at secondary school). The performance of these algorithms in childhood populations, which differ according to age or clinical characteristics to our own, remains to be evaluated. Copyright Springer International Publishing Switzerland 2014

Suggested Citation

  • Kamran Khan & Stavros Petrou & Oliver Rivero-Arias & Stephen Walters & Spencer Boyle, 2014. "Mapping EQ-5D Utility Scores from the PedsQL™ Generic Core Scales," PharmacoEconomics, Springer, vol. 32(7), pages 693-706, July.
    • Handle: RePEc:spr:pharme:v:32:y:2014:i:7:p:693-706
    DOI: 10.1007/s40273-014-0153-y
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    References listed on IDEAS

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    1. Tsuchiya, A & Brazier, J & McColl, E & Parkin, D, 2002. "Deriving preference-based single indices from non-preference based condition-specific instruments: converting AQLQ into EQ5D indices," MPRA Paper 29740, University Library of Munich, Germany.
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    3. Anthony J. Culyer, 2005. "The Dictionary of Health Economics," Books, Edward Elgar Publishing, number 2934.
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    5. Stevens, K, 2010. "Valuation of the Child Health Utility Index 9D (CHU9D)," MPRA Paper 29938, University Library of Munich, Germany.
    6. J. Tilford & Nalin Payakachat & Erica Kovacs & Jeffrey Pyne & Werner Brouwer & Todd Nick & Jayne Bellando & Karen Kuhlthau, 2012. "Preference-Based Health-Related Quality-of-Life Outcomes in Children with Autism Spectrum Disorders," PharmacoEconomics, Springer, vol. 30(8), pages 661-679, August.
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    Cited by:

    1. Joanna F. Dipnall & Frederick P. Rivara & Ronan A. Lyons & Shanthi Ameratunga & Mariana Brussoni & Fiona E. Lecky & Clare Bradley & Ben Beck & Jane Lyons & Amy Schneeberg & James E. Harrison & Belinda, 2021. "Health-Related Quality of Life (HRQoL) Outcomes Following Injury in Childhood and Adolescence Using EuroQol (EQ-5D) Responses with Pooled Longitudinal Data," IJERPH, MDPI, vol. 18(19), pages 1-19, September.
    2. Chris Sampson;Martina Garau, 2019. "How Should We Measure Quality of Life Impact in Rare Disease? Recent Learnings in Spinal Muscular Atrophy," Briefing 002146, Office of Health Economics.
    3. Ben F. M. Wijnen & Iris Mosweu & Marian H. J. M. Majoie & Leone Ridsdale & Reina J. A. Kinderen & Silvia M. A. A. Evers & Paul McCrone, 2018. "A comparison of the responsiveness of EQ-5D-5L and the QOLIE-31P and mapping of QOLIE-31P to EQ-5D-5L in epilepsy," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 19(6), pages 861-870, July.
    4. Asrul Akmal Shafie & Irwinder Kaur Chhabra & Jacqueline Hui Yi Wong & Noor Syahireen Mohammed, 2021. "Mapping PedsQL™ Generic Core Scales to EQ-5D-3L utility scores in transfusion-dependent thalassemia patients," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 22(5), pages 735-747, July.

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