Bullement, A. orcid.org/0000-0001-7091-0972, Stevenson, M.D., Baio, G. et al. (2 more authors) (2023) A systematic review of methods to incorporate external evidence into trial-based survival extrapolations for health technology assessment. Medical Decision Making, 43 (5). pp. 610-620. ISSN 0272-989X
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.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © The Author(s) 2023. This article is distributed under the terms of the Creative Commons Attribution 4.0 License (https://creativecommons.org/licenses/by/4.0/) which permits any use, reproduction and distribution of the work without further permission provided the original work is properly attributed. |
Keywords: | external evidence; extrapolation systematic review; health technology assessment; survival analysis |
Dates: |
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Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Medicine, Dentistry and Health (Sheffield) > School of Health and Related Research (Sheffield) > ScHARR - Sheffield Centre for Health and Related Research |
Funding Information: | Funder Grant number Yorkshire Cancer Research S406NL |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 07 Jun 2023 11:28 |
Last Modified: | 13 Jul 2023 07:41 |
Status: | Published |
Publisher: | SAGE Publications |
Refereed: | Yes |
Identification Number: | 10.1177/0272989x231168618 |
Related URLs: | |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:199831 |