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Overview of Parametric Survival Analysis for Health-Economic Applications

Author

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  • K. Ishak
  • Noemi Kreif
  • Agnes Benedict
  • Noemi Muszbek

Abstract

Health economic models rely on data from trials to project the risk of events (e.g., death) over time beyond the span of the available data. Parametric survival analysis methods can be applied to identify an appropriate statistical model for the observed data, which can then be extrapolated to derive a complete time-to-event curve. This paper describes the properties of the most commonly used statistical distributions as a basis for these models and describes an objective process of identifying the most suitable parametric distribution in a given dataset. The approach can be applied with both individual-patient data as well as with survival probabilities derived from published Kaplan–Meier curves. Both are illustrated with analyses of overall survival from the Sorafenib Hepatocellular Carcinoma Assessment Randomised Protocol trial. Copyright Springer International Publishing Switzerland 2013

Suggested Citation

  • K. Ishak & Noemi Kreif & Agnes Benedict & Noemi Muszbek, 2013. "Overview of Parametric Survival Analysis for Health-Economic Applications," PharmacoEconomics, Springer, vol. 31(8), pages 663-675, August.
    • Handle: RePEc:spr:pharme:v:31:y:2013:i:8:p:663-675
    DOI: 10.1007/s40273-013-0064-3
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    Citations

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    Cited by:

    1. John W. Stevens, 2018. "Using Evidence from Randomised Controlled Trials in Economic Models: What Information is Relevant and is There a Minimum Amount of Sample Data Required to Make Decisions?," PharmacoEconomics, Springer, vol. 36(10), pages 1135-1141, October.
    2. Lisa Masucci & Jaclyn Beca & Mona Sabharwal & Jeffrey S. Hoch, 2017. "Methodological Issues in Economic Evaluations Submitted to the Pan-Canadian Oncology Drug Review (pCODR)," PharmacoEconomics - Open, Springer, vol. 1(4), pages 255-263, December.
    3. Kevin Marsh & Peng Xu & Panagiotis Orfanos & Agnes Benedict & Kamal Desai & Ingolf Griebsch, 2014. "Model-Based Cost-Effectiveness Analyses for the Treatment of Chronic Myeloid Leukaemia: A Review and Summary of Challenges," PharmacoEconomics, Springer, vol. 32(9), pages 853-864, September.
    4. Xiaomin Wan & Liubao Peng & Yuanjian Li, 2015. "A Review and Comparison of Methods for Recreating Individual Patient Data from Published Kaplan-Meier Survival Curves for Economic Evaluations: A Simulation Study," PLOS ONE, Public Library of Science, vol. 10(3), pages 1-21, March.
    5. Kevin Marsh & Peng Xu & Panagiotis Orfanos & James Gordon & Ingolf Griebsch, 2014. "Model-Based Cost-Effectiveness Analyses for the Treatment of Chronic Lymphocytic Leukaemia: A Review of Methods to Model Disease Outcomes and Estimate Utility," PharmacoEconomics, Springer, vol. 32(10), pages 981-993, October.
    6. K. Ishak & Irina Proskorovsky & Agnes Benedict, 2015. "Simulation and Matching-Based Approaches for Indirect Comparison of Treatments," PharmacoEconomics, Springer, vol. 33(6), pages 537-549, June.
    7. Sandjar Djalalov & Jaclyn Beca & Emmanuel M. Ewara & Jeffrey S. Hoch, 2019. "A Comparison of Different Analysis Methods for Reconstructed Survival Data to Inform Cost‑Effectiveness Analysis," PharmacoEconomics, Springer, vol. 37(12), pages 1525-1536, December.
    8. Helen Bell Gorrod & Ben Kearns & John Stevens & Praveen Thokala & Alexander Labeit & Nicholas Latimer & David Tyas & Ahmed Sowdani, 2019. "A Review of Survival Analysis Methods Used in NICE Technology Appraisals of Cancer Treatments: Consistency, Limitations, and Areas for Improvement," Medical Decision Making, , vol. 39(8), pages 899-909, November.
    9. Gabrielle Jongeneel & Marjolein J. E. Greuter & Felice N. Erning & Miriam Koopman & Jan P. Medema & Raju Kandimalla & Ajay Goel & Luis Bujanda & Gerrit A. Meijer & Remond J. A. Fijneman & Martijn G. H, 2020. "Modeling Personalized Adjuvant TreaTment in EaRly stage coloN cancer (PATTERN)," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 21(7), pages 1059-1073, September.
    10. Ben Kearns & John Stevens & Shijie Ren & Alan Brennan, 2020. "How Uncertain is the Survival Extrapolation? A Study of the Impact of Different Parametric Survival Models on Extrapolated Uncertainty About Hazard Functions, Lifetime Mean Survival and Cost Effective," PharmacoEconomics, Springer, vol. 38(2), pages 193-204, February.
    11. Eberechukwu Onukwugha & Jason Bergtold & Rahul Jain, 2015. "A Primer on Marginal Effects—Part I: Theory and Formulae," PharmacoEconomics, Springer, vol. 33(1), pages 25-30, January.

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