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A comparison of the responsiveness of EQ-5D-5L and the QOLIE-31P and mapping of QOLIE-31P to EQ-5D-5L in epilepsy

Author

Listed:
  • Ben F. M. Wijnen

    (Maastricht University
    Epilepsy Centre Kempenhaeghe)

  • Iris Mosweu

    (Institute of Psychiatry, Psychology and Neuroscience at King’s College London)

  • Marian H. J. M. Majoie

    (Epilepsy Centre Kempenhaeghe
    Epilepsy Centre Kempenhaeghe and Maastricht University Medical Centre
    Maastricht University Medical Center
    Maastricht University)

  • Leone Ridsdale

    (Institute of Psychiatry, Psychology and Neuroscience at King’s College London)

  • Reina J. A. Kinderen

    (Maastricht University
    Netherlands Institute of Mental Health and Addiction)

  • Silvia M. A. A. Evers

    (Maastricht University
    Netherlands Institute of Mental Health and Addiction)

  • Paul McCrone

    (Institute of Psychiatry, Psychology and Neuroscience at King’s College London)

Abstract

Objective To investigate the responsiveness of and correlation between the EQ-5D-5L and the QOLIE-31P in patients with epilepsy, and develop a mapping function to predict EQ-5D-5L values based on the QOLIE-31P for use in economic evaluations. Methods The dataset was derived from two clinical trials, the ZMILE study in the Netherlands and the SMILE study in the UK. In both studies, patients’ quality of life using the EQ-5D-5L and QOLIE-31P was measured at baseline and 12 months follow-up. Spearman’s correlations, effect sizes (EF) and standardized response means (SRM) were calculated for both the EQ-5D-5L and QOLIE-31P domains and sub scores. Mapping functions were derived using ordinary least square (OLS) and censored least absolute deviations models. Results A total of 509 patients were included in this study. Low to moderately strong significant correlations were found between both instruments. The EQ-5D-5L showed high ceiling effects and small EFs and SRMs, whereas the QOLIE-31P did not show ceiling effects and also showed small to moderate EFs and SRMs. Results of the different mapping functions indicate that the highest adjusted R 2 we were able to regress was 0.265 using an OLS model with squared terms, leading to a mean absolute error of 0.103. Conclusions Results presented in this study emphasize the shortcomings of the EQ-5D-5L in epilepsy and the importance of the development of condition-specific preference-based instruments which can be used within the QALY framework. In addition, the usefulness of the constructed mapping function in economic evaluations is questionable.

Suggested Citation

  • 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.
    • Handle: RePEc:spr:eujhec:v:19:y:2018:i:6:d:10.1007_s10198-017-0928-0
    DOI: 10.1007/s10198-017-0928-0
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    References listed on IDEAS

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    Cited by:

    1. India Flint & Jasmina Medjedovic & Ewa Drogon O’Flaherty & Elena Alvarez-Baron & Karthinathan Thangavelu & Natasa Savic & Aurelie Meunier & Louise Longworth, 2023. "Mapping analysis to predict SF-6D utilities from health outcomes in people with focal epilepsy," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 24(7), pages 1061-1072, September.
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    More about this item

    Keywords

    Mapping; Responsiveness; Quality of life; Epilepsy;
    All these keywords.

    JEL classification:

    • D61 - Microeconomics - - Welfare Economics - - - Allocative Efficiency; Cost-Benefit Analysis

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