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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

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  • Wijnen, Ben F.M.
  • Mosweu, Iris
  • Majoie, Marian H.J.M.
  • Ridsdale, Leone
  • de Kinderen, Reina J.A.
  • Evers, Silvia M.A.A.
  • McCrone, Paul

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 R2 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

  • Wijnen, Ben F.M. & Mosweu, Iris & Majoie, Marian H.J.M. & Ridsdale, Leone & de Kinderen, Reina J.A. & Evers, Silvia M.A.A. & McCrone, Paul, 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," LSE Research Online Documents on Economics 106170, London School of Economics and Political Science, LSE Library.
  • Handle: RePEc:ehl:lserod:106170
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    References listed on IDEAS

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    1. Yan Feng & Nancy J. Devlin & Koonal K. Shah & Brendan Mulhern & Ben van Hout, 2018. "New methods for modelling EQ‐5D‐5L value sets: An application to English data," Health Economics, John Wiley & Sons, Ltd., vol. 27(1), pages 23-38, January.
    2. Greenberg, Edward & Parks, Robert P, 1997. "A Predictive Approach to Model Selection and Multicollinearity," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 12(1), pages 67-75, Jan.-Feb..
    3. 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.
    4. Donaldson, Cam & Atkinson, Ann & Bond, John & Wright, Ken, 1988. "Should QALYs be programme-specific?," Journal of Health Economics, Elsevier, vol. 7(3), pages 239-257, September.
    5. Ralph Crott & Andrew Briggs, 2010. "Mapping the QLQ-C30 quality of life cancer questionnaire to EQ-5D patient preferences," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 11(4), pages 427-434, August.
    6. John Brazier & Aki Tsuchiya, 2010. "Preference‐based condition‐specific measures of health: what happens to cross programme comparability?," Health Economics, John Wiley & Sons, Ltd., vol. 19(2), pages 125-129, February.
    7. Nancy J. Devlin & Koonal K. Shah & Yan Feng & Brendan Mulhern & Ben van Hout, 2018. "Valuing health‐related quality of life: An EQ‐5D‐5L value set for England," Health Economics, John Wiley & Sons, Ltd., vol. 27(1), pages 7-22, January.
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    More about this item

    Keywords

    epilepsy; mapping; quality of life; responsiveness; 09/165/01;
    All these keywords.

    JEL classification:

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

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