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Survival extrapolation using the poly-Weibull model

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 nec...

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Detalles Bibliográficos
Autores principales: Demiris, Nikolaos, Lunn, David, Sharples, Linda D
Formato: Online Artículo Texto
Lenguaje:English
Publicado: SAGE Publications 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4456429/
https://www.ncbi.nlm.nih.gov/pubmed/21937472
http://dx.doi.org/10.1177/0962280211419645
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author Demiris, Nikolaos
Lunn, David
Sharples, Linda D
author_facet Demiris, Nikolaos
Lunn, David
Sharples, Linda D
author_sort Demiris, Nikolaos
collection PubMed
description 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.
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spelling pubmed-44564292015-06-16 Survival extrapolation using the poly-Weibull model Demiris, Nikolaos Lunn, David Sharples, Linda D Stat Methods Med Res Articles 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. SAGE Publications 2015-04 /pmc/articles/PMC4456429/ /pubmed/21937472 http://dx.doi.org/10.1177/0962280211419645 Text en © The Author(s) 2011 Reprints and permissions: sagepub.co.uk/journalsPermissions.nav http://creativecommons.org/licenses/by/3.0/ 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).
spellingShingle Articles
Demiris, Nikolaos
Lunn, David
Sharples, Linda D
Survival extrapolation using the poly-Weibull model
title Survival extrapolation using the poly-Weibull model
title_full Survival extrapolation using the poly-Weibull model
title_fullStr Survival extrapolation using the poly-Weibull model
title_full_unstemmed Survival extrapolation using the poly-Weibull model
title_short Survival extrapolation using the poly-Weibull model
title_sort survival extrapolation using the poly-weibull model
topic Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4456429/
https://www.ncbi.nlm.nih.gov/pubmed/21937472
http://dx.doi.org/10.1177/0962280211419645
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