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A comparison of published time invariant Markov models with Partitioned Survival models for cost effectiveness estimation; three case studies of treatments for glioblastoma multiforme


  • Martin Connock

    (University of Warwick)

  • Peter Auguste

    (University of Warwick)

  • Xavier Armoiry

    (University of Warwick
    University of Lyon)


Background Cost-effectiveness analyses of treatments for glioblastoma multiforme (GBM) have mostly used state transition Markov models with time invariant transition probabilities (TIMMs). In three case studies of GBM treatments, we compared Partitioned Survival model (PSM) results with published outputs from TIMMs. Methods PSMs used the same RCT data sources, utility values, time horizons, cycle times and annual discounting used in published TIMMs. Reported overall survival and progression-free survival plots were digitised and fitted with a range of parametric models. Economic model outputs were generated in the same form as reported for the TIMMs. PSM output uncertainty was explored in univariate and in multivariate sensitivity analyses. Results PSMs generated incremental cost-effectiveness ratios that were different to the published TIMMs. The magnitude of difference was substantial in two cases. The PSMs were reasonably robust and in sensitivity analyses were sensitive to variations in the same model inputs as were the TIMMs. When compared to the RCT data, the TIMMs tended to generate underestimates of the likely overall survival gain. TIMM estimates for depletion of individuals from the stable disease state and for accumulation in the dead state had relatively poor resemblance to the source RCT data. Conclusion TIMMs delivered different cost-effectiveness estimates to PSMs; in two cases, TIMMs produced substantially lower ICER values than PSMs. Model output differences appear attributable to less realistic cost-and-benefit estimates generated in TIMMs due to rapid depletion from the stable disease state and/or accumulation in the dead state.

Suggested Citation

  • Martin Connock & Peter Auguste & Xavier Armoiry, 2021. "A comparison of published time invariant Markov models with Partitioned Survival models for cost effectiveness estimation; three case studies of treatments for glioblastoma multiforme," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 22(1), pages 89-100, February.
  • Handle: RePEc:spr:eujhec:v:22:y:2021:i:1:d:10.1007_s10198-020-01239-z
    DOI: 10.1007/s10198-020-01239-z

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    References listed on IDEAS

    1. Bin Wu & Yifeng Miao & Yongrui Bai & Min Ye & Yuejuan Xu & Huafeng Chen & Jinfang Shen & Yongming Qiu, 2012. "Subgroup Economic Analysis for Glioblastoma in a Health Resource-Limited Setting," PLOS ONE, Public Library of Science, vol. 7(4), pages 1-9, April.
    2. Patrick Royston & Paul C. Lambert, 2011. "Flexible Parametric Survival Analysis Using Stata: Beyond the Cox Model," Stata Press books, StataCorp LP, number fpsaus, March.
    3. Anders Alexandersson, 2004. "Graphing confidence ellipses: An update of ellip for Stata 8," Stata Journal, StataCorp LP, vol. 4(3), pages 242-256, September.
    4. Daniel Gallacher & Felix Achana, 2018. "Assessing the health economic agreement of different data sources," Stata Journal, StataCorp LP, vol. 18(1), pages 223-233, March.
    5. Angel Cronin & Lu Tian & Hajime Uno, 2016. "strmst2 and strmst2pw: New commands to compare survival curves using the restricted mean survival time," Stata Journal, StataCorp LP, vol. 16(3), pages 702-716, September.
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    Blog mentions

    As found by, the blog aggregator for Economics research:
    1. Rita Faria’s journal round-up for 8th February 2021
      by Rita Faria in The Academic Health Economists' Blog on 2021-02-08 12:00:01

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    More about this item


    Markov model; Partitioned survival model; Cost-effectiveness;
    All these keywords.

    JEL classification:

    • I10 - Health, Education, and Welfare - - Health - - - General
    • I19 - Health, Education, and Welfare - - Health - - - Other
    • C18 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Methodolical Issues: General


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