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A Systematic Review of Methods to Incorporate External Evidence into Trial-Based Survival Extrapolations for Health Technology Assessment

Author

Listed:
  • Ash Bullement

    (School of Health and Related Research, University of Sheffield, UK
    Delta Hat Limited, Nottingham, UK)

  • Matthew D. Stevenson

    (School of Health and Related Research, University of Sheffield, UK)

  • Gianluca Baio

    (Department of Statistical Science, University College London, UK)

  • Gemma E. Shields

    (School of Health Sciences, University of Manchester, UK)

  • Nicholas R. Latimer

    (School of Health and Related Research, University of Sheffield, UK)

Abstract

Background External evidence is commonly used to inform survival modeling for health technology assessment (HTA). While there are a range of methodological approaches that have been proposed, it is unclear which methods could be used and how they compare. Purpose This review aims to identify, describe, and categorize established methods to incorporate external evidence into survival extrapolation for HTA. Data Sources Embase, MEDLINE, EconLit, and Web of Science databases were searched to identify published methodological studies, supplemented by hand searching and citation tracking. Study Selection Eligible studies were required to present a novel extrapolation approach incorporating external evidence (i.e., data or information) within survival model estimation. Data Extraction Studies were classified according to how the external evidence was integrated as a part of model fitting. Information was extracted concerning the model-fitting process, key requirements, assumptions, software, application contexts, and presentation of comparisons with, or validation against, other methods. Data Synthesis Across 18 methods identified from 22 studies, themes included use of informative prior(s) ( n  = 5), piecewise ( n  = 7), and general population adjustment ( n  = 9), plus a variety of “other†( n  = 8) approaches. Most methods were applied in cancer populations ( n  = 13). No studies compared or validated their method against another method that also incorporated external evidence. Limitations As only studies with a specific methodological objective were included, methods proposed as part of another study type (e.g., an economic evaluation) were excluded from this review. Conclusions Several methods were identified in this review, with common themes based on typical data sources and analytical approaches. Of note, no evidence was found comparing the identified methods to one another, and so an assessment of different methods would be a useful area for further research. Highlights This review aims to identify methods that have been used to incorporate external evidence into survival extrapolations, focusing on those that may be used to inform health technology assessment. We found a range of different approaches, including piecewise methods, Bayesian methods using informative priors, and general population adjustment methods, as well as a variety of “other†approaches. No studies attempted to compare the performance of alternative methods for incorporating external evidence with respect to the accuracy of survival predictions. Further research investigating this would be valuable.

Suggested Citation

  • Ash Bullement & Matthew D. Stevenson & Gianluca Baio & Gemma E. Shields & Nicholas R. Latimer, 2023. "A Systematic Review of Methods to Incorporate External Evidence into Trial-Based Survival Extrapolations for Health Technology Assessment," Medical Decision Making, , vol. 43(5), pages 610-620, July.
  • Handle: RePEc:sae:medema:v:43:y:2023:i:5:p:610-620
    DOI: 10.1177/0272989X231168618
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    References listed on IDEAS

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