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Using Costs States in a Semi-Markov Model to Estimate Cost-Effectiveness with an Illustration for Metastatic HER2+ Breast Cancer in the Czech Republic

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  • Lenka Slegerova

    (Institute of Economic Studies, Faculty of Social Sciences, Charles University Opletalova 26, 110 00, Prague, Czech Republic)

Abstract

This paper proposes an original method for assessing costs of medical treatment. It defines states in a semi-Markov model associated with specific costs of the treatment, and not with patients' health statuses. Costs assigning to these "costs states" is more straightforward; moreover, it allows to estimate the periods separately when no treatment is administered. This method is applied to individuals' data drawn from the Czech clinical practice in the treatment of metastatic HER2+ breast cancer. The aim is to assess the cost-effectiveness of adding pertuzumab to the combination of trastuzumab+docetaxel within first-line therapy. The Kaplan-Meier estimates of survival functions were supplemented by the Cox proportional hazard model and the accelerated failure time model that both control for patients' characteristics. Based on the employed data, the addition of pertuzumab does not result in significantly longer patients' survival. Since the treatment is associated with higher costs, adding pertuzumab is not considered to be cost-effective; however, this could be due to relatively short patients' follow-up that is available at the moment.

Suggested Citation

  • Lenka Slegerova, 2020. "Using Costs States in a Semi-Markov Model to Estimate Cost-Effectiveness with an Illustration for Metastatic HER2+ Breast Cancer in the Czech Republic," Working Papers IES 2020/12, Charles University Prague, Faculty of Social Sciences, Institute of Economic Studies, revised May 2020.
    • Handle: RePEc:fau:wpaper:wp2020_12
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    File URL: https://ies.fsv.cuni.cz/en/veda-vyzkum/working-papers/6243
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    More about this item

    Keywords

    Cost-effectiveness; costs states in semi-Markov processes; Kaplan-Meier estimator; HER2+ metastatic breast cancer; pertuzumab; clinical data; Czech Republic;
    All these keywords.

    JEL classification:

    • C24 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Truncated and Censored Models; Switching Regression Models; Threshold Regression Models
    • C41 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Duration Analysis; Optimal Timing Strategies
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • D61 - Microeconomics - - Welfare Economics - - - Allocative Efficiency; Cost-Benefit Analysis
    • I13 - Health, Education, and Welfare - - Health - - - Health Insurance, Public and Private
    • I18 - Health, Education, and Welfare - - Health - - - Government Policy; Regulation; Public Health

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