IDEAS home Printed from https://ideas.repec.org/a/spr/eujhec/v20y2019i9d10.1007_s10198-019-01092-9.html
   My bibliography  Save this article

Health state utility values (QALY weights) for Huntington’s disease: an analysis of data from the European Huntington’s Disease Network (EHDN)

Author

Listed:
  • Annie Hawton

    (University of Exeter)

  • Colin Green

    (University of Exeter)

  • Elizabeth Goodwin

    (University of Exeter)

  • Timothy Harrower

    (Neurology, Royal Devon and Exeter NHS Foundation Trust)

Abstract

Background Huntington’s Disease (HD) is a hereditary neurodegenerative disorder which affects individuals’ ability to walk, talk, think, and reason. Onset is usually in the forties, there are no therapies currently available that alter disease course, and life expectancy is 10–20 years from diagnosis. The gene causing HD is fully penetrant, with a 50% probability of passing the disease to offspring. Although the impacts of HD are substantial, there has been little report of the quality of life of people with the condition in a manner that can be used in economic evaluations of treatments for HD. Health state utility values (HSUVs), used to calculate quality-adjusted life-years (QALYs), are the metric commonly used to inform such healthcare policy decision-making. Objectives The aim was to report HSUVs for HD, with specific objectives to use European data to: (i) describe HSUVs by demographic and clinical characteristics; (ii) compare HSUVs of people with HD in the UK with population norms; (iii) identify the relative strength of demographic and clinical characteristics in predicting HSUVs. Methods European Huntington’s Disease Network REGISTRY study data were used for analysis. This is a multi-centre, multi-national, observational, longitudinal study, which collects six-monthly demographic, clinical, and patient-reported outcome measures, including the SF-36. SF-36 scores were converted to SF-6D HSUVs and described by demographic and clinical characteristics. HSUVs from people with HD in the UK were compared with population norms. Regression analysis was used to estimate the relative strength of age, gender, time since diagnosis, and disease severity (according to the Total Function Capacity (TFC) score, and the UHDRS’s Motor score, Behavioural score, and Cognition score) in predicting HSUVs. Results 11,328 questionnaires were completed by 5560 respondents with HD in 12 European countries. Women generally had lower HSUVs than men, and HSUVs were consistently lower than population norms for those with HD in the UK, and dropped with increasing disease severity. The regression model significantly accounted for the variance in SF-6D scores (n = 1939; F [7,1931] = 120.05; p

Suggested Citation

  • Annie Hawton & Colin Green & Elizabeth Goodwin & Timothy Harrower, 2019. "Health state utility values (QALY weights) for Huntington’s disease: an analysis of data from the European Huntington’s Disease Network (EHDN)," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 20(9), pages 1335-1347, December.
  • Handle: RePEc:spr:eujhec:v:20:y:2019:i:9:d:10.1007_s10198-019-01092-9
    DOI: 10.1007/s10198-019-01092-9
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s10198-019-01092-9
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.

    File URL: https://libkey.io/10.1007/s10198-019-01092-9?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Brazier, John & Ratcliffe, Julie & Salomon, Joshua & Tsuchiya, Aki, 2016. "Measuring and Valuing Health Benefits for Economic Evaluation," OUP Catalogue, Oxford University Press, edition 2, number 9780198725923.
    2. Brazier, John & Roberts, Jennifer & Deverill, Mark, 2002. "The estimation of a preference-based measure of health from the SF-36," Journal of Health Economics, Elsevier, vol. 21(2), pages 271-292, March.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Stevens, K, 2010. "Valuation of the Child Health Utility Index 9D (CHU9D)," MPRA Paper 29938, University Library of Munich, Germany.
    2. Brazier, JE & Yang, Y & Tsuchiya, A, 2008. "A review of studies mapping (or cross walking) from non-preference based measures of health to generic preference-based measures," MPRA Paper 29808, University Library of Munich, Germany.
    3. Ian M. McCarthy, 2015. "Putting the Patient in Patient Reported Outcomes: A Robust Methodology for Health Outcomes Assessment," Health Economics, John Wiley & Sons, Ltd., vol. 24(12), pages 1588-1603, December.
    4. Brazier, John & Rowen, Donna & Tsuchiya, Aki & Yang, Yaling & Young, Tracy A., 2011. "The impact of adding an extra dimension to a preference-based measure," Social Science & Medicine, Elsevier, vol. 73(2), pages 245-253, July.
    5. Katherine Stevens, 2012. "Valuation of the Child Health Utility 9D Index," PharmacoEconomics, Springer, vol. 30(8), pages 729-747, August.
    6. Hareth Al-Janabi & Terry Flynn & Joanna Coast, 2011. "QALYs and Carers," PharmacoEconomics, Springer, vol. 29(12), pages 1015-1023, December.
    7. Young, Tracey A. & Yang, Y & Brazier, J & Tsuchiya, A, 2007. "The use of Rasch analysis as a tool in the construction of a preference based measure: the case of AQLQ," MPRA Paper 29802, University Library of Munich, Germany.
    8. Samer Kharroubi, 2015. "A Comparison of Japan and UK SF-6D Health-State Valuations Using a Non-Parametric Bayesian Method," Applied Health Economics and Health Policy, Springer, vol. 13(4), pages 409-420, August.
    9. Matthijs M. Versteegh & Annemieke Leunis & Jolanda J. Luime & Mike Boggild & Carin A. Uyl-de Groot & Elly A. Stolk, 2012. "Mapping QLQ-C30, HAQ, and MSIS-29 on EQ-5D," Medical Decision Making, , vol. 32(4), pages 554-568, July.
    10. Samer A. Kharroubi & Donna Rowen, 2019. "Valuation of preference-based measures: can existing preference data be used to select a smaller sample of health states?," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 20(2), pages 245-255, March.
    11. Elizabeth Goodwin & Colin Green, 2016. "A Systematic Review of the Literature on the Development of Condition-Specific Preference-Based Measures of Health," Applied Health Economics and Health Policy, Springer, vol. 14(2), pages 161-183, April.
    12. Ratcliffe, Julie & Huynh, Elisabeth & Chen, Gang & Stevens, Katherine & Swait, Joffre & Brazier, John & Sawyer, Michael & Roberts, Rachel & Flynn, Terry, 2016. "Valuing the Child Health Utility 9D: Using profile case best worst scaling methods to develop a new adolescent specific scoring algorithm," Social Science & Medicine, Elsevier, vol. 157(C), pages 48-59.
    13. Makai, Peter & Brouwer, Werner B.F. & Koopmanschap, Marc A. & Stolk, Elly A. & Nieboer, Anna P., 2014. "Quality of life instruments for economic evaluations in health and social care for older people: A systematic review," Social Science & Medicine, Elsevier, vol. 102(C), pages 83-93.
    14. Rowen, D & Brazier, J & Tsuchiya, A & Hernández, M & Ibbotson, R, 2009. "The simultaneous valuation of states from multiple instruments using ranking and VAS data: methods and preliminary results," MPRA Paper 29841, University Library of Munich, Germany.
    15. Ifigeneia Mavranezouli, 2010. "A Review and Critique of Studies Reporting Utility Values for Schizophrenia-Related Health States," PharmacoEconomics, Springer, vol. 28(12), pages 1109-1121, December.
    16. Peasgood, T & Ward, S & Brazier, J, 2010. "A review and meta-analysis of health state utility values in breast cancer," MPRA Paper 29950, University Library of Munich, Germany.
    17. Christopher McCabe & Richard Edlin & David Meads & Chantelle Brown & Samer Kharroubi, 2013. "Constructing Indirect Utility Models: Some Observations on the Principles and Practice of Mapping to Obtain Health State Utilities," PharmacoEconomics, Springer, vol. 31(8), pages 635-641, August.
    18. Nan Luo & Pei Wang & Julian Thumboo & Yee-Wei Lim & Hubertus Vrijhoef, 2014. "Valuation of EQ-5D-3L Health States in Singapore: Modeling of Time Trade-Off Values for 80 Empirically Observed Health States," PharmacoEconomics, Springer, vol. 32(5), pages 495-507, May.
    19. Jing Chen & Carlos K H Wong & Sarah M McGhee & Polly K P Pang & Wai-Cho Yu, 2014. "A Comparison between the EQ-5D and the SF-6D in Patients with Chronic Obstructive Pulmonary Disease (COPD)," PLOS ONE, Public Library of Science, vol. 9(11), pages 1-9, November.
    20. Joseph Kwon & Sung Wook Kim & Wendy J. Ungar & Kate Tsiplova & Jason Madan & Stavros Petrou, 2018. "A Systematic Review and Meta-analysis of Childhood Health Utilities," Medical Decision Making, , vol. 38(3), pages 277-305, April.

    More about this item

    Keywords

    Huntington’s disease; Health state utility values; Quality-adjusted life-years; Cost-effectiveness analysis;
    All these keywords.

    JEL classification:

    • I19 - Health, Education, and Welfare - - Health - - - Other

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:eujhec:v:20:y:2019:i:9:d:10.1007_s10198-019-01092-9. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.