IDEAS home Printed from https://ideas.repec.org/a/spr/pharme/v37y2019i12d10.1007_s40273-019-00830-4.html
   My bibliography  Save this article

A Comparison of Different Analysis Methods for Reconstructed Survival Data to Inform Cost‑Effectiveness Analysis

Author

Listed:
  • Sandjar Djalalov

    (Westminster International University in Tashkent
    Tashkent Pharmaceutical Institute
    Toronto Health Economics and Technology Assessment (THETA) Collaborative Toronto General Hospital)

  • Jaclyn Beca

    (Cancer Care Ontario)

  • Emmanuel M. Ewara

    (Janssen Inc.)

  • Jeffrey S. Hoch

    (Division of Health Policy and Management, Department of Public Health Sciences, University of California Davis)

Abstract

Objectives The aim of this study was to use Microsoft Excel spreadsheet software to fit parametric survival distributions. We also explain the differences between individual patient data (IPD) and survival data reconstructed in Excel and SAS. Methods Three sets of patient data on overall survival were compared using different methods: ‘original’ IPD, ‘reconstructed SAS’, and ‘reconstructed Excel’. The best-fit distribution was selected using visual observation, supported by linear plots of predicted probabilities, goodness-of-fit coefficients, and the sum of squared error of prediction. Outcomes included the incremental cost-effectiveness ratio (ICER), incremental net benefit (INB), incremental cost, and life-years gained over short-term and lifetime horizons. These were compared for different data sets. Results In this example, log-normal, log-logistic, and Weibull distributions showed best-fit with the visual tests and goodness-of-fit statistics. Weibull and exponential distributions showed significant differences compared with IPD data. Data on short-term (5 years) time horizons produced by different data re-creation methods showed closeness with data reconstructed from SAS. The ICER and INB results were dependent on the time horizon and selected parametric distribution from the model. Conclusions Different approaches used in fitting parametric survival distributions yielded predicted probabilities that substantially differed from those using original IPD. Our study highlights the importance of following guidelines for economic evaluations with a systematic approach to parametric survival analysis techniques in order to select best fitting parametric survival distributions.

Suggested Citation

  • 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.
    • Handle: RePEc:spr:pharme:v:37:y:2019:i:12:d:10.1007_s40273-019-00830-4
    DOI: 10.1007/s40273-019-00830-4
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s40273-019-00830-4
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s40273-019-00830-4?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. 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.
    2. 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.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. 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.
    2. 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.
    3. 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.
    4. Deborah Plana & Geoffrey Fell & Brian M. Alexander & Adam C. Palmer & Peter K. Sorger, 2022. "Cancer patient survival can be parametrized to improve trial precision and reveal time-dependent therapeutic effects," Nature Communications, Nature, vol. 13(1), pages 1-13, December.
    5. 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.
    6. 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.
    7. 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.
    8. 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.
    9. 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.
    10. 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.
    11. 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.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:pharme:v:37:y:2019:i:12:d:10.1007_s40273-019-00830-4. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.