Ouwens, M.J.N.M., Mukhopadhyay, P., Zhang, Y. et al. (3 more authors) (2019) Estimating lifetime benefits associated with immuno-oncology therapies : challenges and approaches for overall survival extrapolations. PharmacoEconomics, 37 (9). pp. 1129-1138. ISSN 1170-7690
Abstract
Background
Standard parametric survival models are commonly used to estimate long-term survival in oncology health technology assessments; however, they can inadequately represent the complex pattern of hazard functions or underlying mechanism of action (MoA) of immuno-oncology (IO) treatments.
Objective
The aim of this study was to explore methods for extrapolating overall survival (OS) and provide insights on model selection in the context of the underlying MoA of IO treatments.
Methods
Standard parametric, flexible parametric, cure, parametric mixture and landmark models were applied to data from ATLANTIC (NCT02087423; data cut-off [DCO] 3 June 2016). The goodness of fit of each model was compared using the observed survival and hazard functions, together with the plausibility of corresponding model extrapolation beyond the trial period. Extrapolations were compared with updated data from ATLANTIC (DCO 7 November 2017) for validation.
Results
A close fit to the observed OS was seen with all models; however, projections beyond the trial period differed. Estimated mean OS differed substantially across models. The cure models provided the best fit for the new DCO.
Conclusions
Standard parametric models fitted to the initial ATLANTIC DCO generally underestimated longer-term OS, compared with the later DCO. Cure, parametric mixture and response-based landmark models predicted that larger proportions of patients with metastatic non-small cell lung cancer receiving IO treatments may experience long-term survival, which was more in keeping with the observed data. Further research using more mature OS data for IO treatments is needed.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © The Author(s) 2019. This article is distributed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. |
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 |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 04 Jul 2019 08:13 |
Last Modified: | 07 Dec 2021 08:27 |
Status: | Published |
Publisher: | Springer |
Refereed: | Yes |
Identification Number: | 10.1007/s40273-019-00806-4 |
Related URLs: | |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:146932 |
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