Evaluation of survival extrapolation in immuno-oncology using multiple pre-planned data cuts: learnings to aid in model selection

Bullement, A. orcid.org/0000-0001-7091-0972, Willis, A., Amin, A. et al. (3 more authors) (2020) Evaluation of survival extrapolation in immuno-oncology using multiple pre-planned data cuts: learnings to aid in model selection. BMC Medical Research Methodology, 20. 103. ISSN 1471-2288

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Copyright, Publisher and Additional Information: © The Author(s). 2020. Open Access: This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
Keywords: Survival; Extrapolation; Cancer; Immune-oncology; Immunotherapy
Dates:
  • Accepted: 28 April 2020
  • Published (online): 6 May 2020
  • Published: 6 May 2020
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)
Depositing User: Symplectic Sheffield
Date Deposited: 12 Jan 2021 12:41
Last Modified: 12 Jan 2021 12:41
Status: Published
Publisher: Springer Science and Business Media LLC
Refereed: Yes
Identification Number: https://doi.org/10.1186/s12874-020-00997-x
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