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Analysis of recurrent events with an associated informative dropout time: Application of the joint frailty model
This paper considers the analysis of a repeat event outcome in clinical trials of chronic diseases in the context of dependent censoring (e.g. mortality). It has particular application in the context of recurrent heart failure hospitalisations in trials of heart failure. Semi‐parametric joint frailt...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
John Wiley and Sons Inc.
2016
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5019155/ https://www.ncbi.nlm.nih.gov/pubmed/26751714 http://dx.doi.org/10.1002/sim.6853 |
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author | Rogers, Jennifer K. Yaroshinsky, Alex Pocock, Stuart J. Stokar, David Pogoda, Janice |
author_facet | Rogers, Jennifer K. Yaroshinsky, Alex Pocock, Stuart J. Stokar, David Pogoda, Janice |
author_sort | Rogers, Jennifer K. |
collection | PubMed |
description | This paper considers the analysis of a repeat event outcome in clinical trials of chronic diseases in the context of dependent censoring (e.g. mortality). It has particular application in the context of recurrent heart failure hospitalisations in trials of heart failure. Semi‐parametric joint frailty models (JFMs) simultaneously analyse recurrent heart failure hospitalisations and time to cardiovascular death, estimating distinct hazard ratios whilst individual‐specific latent variables induce associations between the two processes. A simulation study was carried out to assess the suitability of the JFM versus marginal analyses of recurrent events and cardiovascular death using standard methods. Hazard ratios were consistently overestimated when marginal models were used, whilst the JFM produced good, well‐estimated results. An application to the Candesartan in Heart failure: Assessment of Reduction in Mortality and morbidity programme was considered. The JFM gave unbiased estimates of treatment effects in the presence of dependent censoring. We advocate the use of the JFM for future trials that consider recurrent events as the primary outcome. © 2016 The Authors. Statistics in Medicine Published by John Wiley & Sons Ltd. |
format | Online Article Text |
id | pubmed-5019155 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | John Wiley and Sons Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-50191552016-09-23 Analysis of recurrent events with an associated informative dropout time: Application of the joint frailty model Rogers, Jennifer K. Yaroshinsky, Alex Pocock, Stuart J. Stokar, David Pogoda, Janice Stat Med Research Articles This paper considers the analysis of a repeat event outcome in clinical trials of chronic diseases in the context of dependent censoring (e.g. mortality). It has particular application in the context of recurrent heart failure hospitalisations in trials of heart failure. Semi‐parametric joint frailty models (JFMs) simultaneously analyse recurrent heart failure hospitalisations and time to cardiovascular death, estimating distinct hazard ratios whilst individual‐specific latent variables induce associations between the two processes. A simulation study was carried out to assess the suitability of the JFM versus marginal analyses of recurrent events and cardiovascular death using standard methods. Hazard ratios were consistently overestimated when marginal models were used, whilst the JFM produced good, well‐estimated results. An application to the Candesartan in Heart failure: Assessment of Reduction in Mortality and morbidity programme was considered. The JFM gave unbiased estimates of treatment effects in the presence of dependent censoring. We advocate the use of the JFM for future trials that consider recurrent events as the primary outcome. © 2016 The Authors. Statistics in Medicine Published by John Wiley & Sons Ltd. John Wiley and Sons Inc. 2016-01-10 2016-06-15 /pmc/articles/PMC5019155/ /pubmed/26751714 http://dx.doi.org/10.1002/sim.6853 Text en © 2016 The Authors. Statistics in Medicine Published by John Wiley & Sons Ltd. This is an open access article under the terms of the Creative Commons Attribution‐NonCommercial (http://creativecommons.org/licenses/by-nc/4.0/) License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited and is not used for commercial purposes. |
spellingShingle | Research Articles Rogers, Jennifer K. Yaroshinsky, Alex Pocock, Stuart J. Stokar, David Pogoda, Janice Analysis of recurrent events with an associated informative dropout time: Application of the joint frailty model |
title | Analysis of recurrent events with an associated informative dropout time: Application of the joint frailty model |
title_full | Analysis of recurrent events with an associated informative dropout time: Application of the joint frailty model |
title_fullStr | Analysis of recurrent events with an associated informative dropout time: Application of the joint frailty model |
title_full_unstemmed | Analysis of recurrent events with an associated informative dropout time: Application of the joint frailty model |
title_short | Analysis of recurrent events with an associated informative dropout time: Application of the joint frailty model |
title_sort | analysis of recurrent events with an associated informative dropout time: application of the joint frailty model |
topic | Research Articles |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5019155/ https://www.ncbi.nlm.nih.gov/pubmed/26751714 http://dx.doi.org/10.1002/sim.6853 |
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