Demiris, N, Lunn, D and Sharples, LD (2015) Survival extrapolation using the poly-Weibull model. Statistical Methods in Medical Research, 24 (2). 287 - 301. ISSN 0962-2802
Abstract
Recent studies of (cost-) effectiveness in cardiothoracic transplantation have required estimation of mean survival over the lifetime of the recipients. In order to calculate mean survival, the complete survivor curve is required but is often not fully observed, so that survival extrapolation is necessary. After transplantation, the hazard function is bathtub-shaped, reflecting latent competing risks which operate additively in overlapping time periods. The poly-Weibull distribution is a flexible parametric model that may be used to extrapolate survival and has a natural competing risks interpretation. In addition, treatment effects and subgroups can be modelled separately for each component of risk. We describe the model and develop inference procedures using freely available software. The methods are applied to two problems from cardiothoracic transplantation.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © The Author(s), 2011. This article is distributed under the terms of the Creative Commons Attribution 3.0 License (http://www.creativecommons.org/licenses/by/3.0/) which permits any use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access page (http://www.uk.sagepub.com/aboutus/openaccess.htm). |
Keywords: | Bayesian survival analysis; heart lung transplantation; life years gained; poly-Weibull models; survival extrapolation; WinBUGS |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Medicine and Health (Leeds) > School of Medicine (Leeds) > Inst of Clinical Trials Research (LICTR) (Leeds) |
Depositing User: | Symplectic Publications |
Date Deposited: | 08 Oct 2015 09:42 |
Last Modified: | 08 Oct 2015 09:42 |
Published Version: | http://dx.doi.org/10.1177/0962280211419645 |
Status: | Published |
Publisher: | SAGE |
Identification Number: | 10.1177/0962280211419645 |
Related URLs: | |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:86966 |