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Mapping analysis to predict SF-6D utilities from health outcomes in people with focal epilepsy

Author

Listed:
  • India Flint

    (PHMR Limited)

  • Jasmina Medjedovic

    (Arvelle Therapeutics GmbH)

  • Ewa Drogon O’Flaherty

    (Arvelle Therapeutics GmbH)

  • Elena Alvarez-Baron

    (Arvelle Therapeutics GmbH)

  • Karthinathan Thangavelu

    (Arvelle Therapeutics GmbH)

  • Natasa Savic

    (Arvelle Therapeutics GmbH)

  • Aurelie Meunier

    (PHMR Limited)

  • Louise Longworth

    (PHMR Limited)

Abstract

Background Focal-onset seizures (FOS) are commonly experienced by people with epilepsy and have a significant impact on quality of life (QoL). This study aimed to develop a mapping algorithm to predict SF-6D values in adults with FOS for use in economic evaluations of a new treatment, cenobamate. Methods An online survey, including questions on disease history, SF-36, and an epilepsy-specific measure (QOLIE-31-P) was administered to people with FOS in the UK, France, Italy, Germany, and Spain. A range of regression models were fitted to SF-6D scores including direct and response mapping approaches. Results 361 individuals were included in the analysis. In the previous 28 days, the mean number of FOS experienced was 3, (range 0–43) and the mean longest period of consecutive days without experiencing a seizure was 14 days (range 1–28 days or more). Mean responses on all SF-36 dimensions were lower than general population norms. Mean SF-6D and QOLIE-31-P scores were 0.584 and 45.72, respectively. The best performing model was the ordinary least squares (OLS), with root mean squared error and mean absolute error values of 0.0977 and 0.0742, respectively. Explanatory variables which best predicted SF-6D included seizure frequency, severity, freedom, and age. Conclusion People with uncontrolled FOS have poor QoL. The mapping algorithm enables the prediction of SF-6D values from clinical outcomes in people with FOS. It can be applied to outcome data from clinical trials to facilitate cost-utility analysis.

Suggested Citation

  • 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.
  • Handle: RePEc:spr:eujhec:v:24:y:2023:i:7:d:10.1007_s10198-022-01519-w
    DOI: 10.1007/s10198-022-01519-w
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    References listed on IDEAS

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    More about this item

    Keywords

    Health-related utility; Mapping; SF-6D; SF-36; Epilepsy; Quality of life; Cenobamate;
    All these keywords.

    JEL classification:

    • B40 - Schools of Economic Thought and Methodology - - Economic Methodology - - - General
    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
    • C19 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Other
    • C30 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - General
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • C55 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Large Data Sets: Modeling and Analysis
    • C83 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Survey Methods; Sampling Methods
    • C87 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Econometric Software

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