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Competing risk of mortality in association studies of non-fatal events

In geriatric research of non-fatal events, participants often die during the study follow-up without having the non-fatal event of interest. Cause-specific (CS) hazard regression and Fine-Gray (FG) subdistribution hazard regression are the two most common estimation approaches addressing such compet...

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Autor principal: Buzkova, Petra
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8362942/
https://www.ncbi.nlm.nih.gov/pubmed/34388170
http://dx.doi.org/10.1371/journal.pone.0255313
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author Buzkova, Petra
author_facet Buzkova, Petra
author_sort Buzkova, Petra
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description In geriatric research of non-fatal events, participants often die during the study follow-up without having the non-fatal event of interest. Cause-specific (CS) hazard regression and Fine-Gray (FG) subdistribution hazard regression are the two most common estimation approaches addressing such competing risk. We explain how the conventional CS approach and the FG approach differ and why many FG estimates of associations are counter-intuitive. Additionally, we clarify the indirect link between models for hazard and models for cumulative incidence. The methodologies are contrasted on data from the Cardiovascular Health Study, a population-based study in adults aged 65 years and older.
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spelling pubmed-83629422021-08-14 Competing risk of mortality in association studies of non-fatal events Buzkova, Petra PLoS One Research Article In geriatric research of non-fatal events, participants often die during the study follow-up without having the non-fatal event of interest. Cause-specific (CS) hazard regression and Fine-Gray (FG) subdistribution hazard regression are the two most common estimation approaches addressing such competing risk. We explain how the conventional CS approach and the FG approach differ and why many FG estimates of associations are counter-intuitive. Additionally, we clarify the indirect link between models for hazard and models for cumulative incidence. The methodologies are contrasted on data from the Cardiovascular Health Study, a population-based study in adults aged 65 years and older. Public Library of Science 2021-08-13 /pmc/articles/PMC8362942/ /pubmed/34388170 http://dx.doi.org/10.1371/journal.pone.0255313 Text en © 2021 Petra Buzkova https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Buzkova, Petra
Competing risk of mortality in association studies of non-fatal events
title Competing risk of mortality in association studies of non-fatal events
title_full Competing risk of mortality in association studies of non-fatal events
title_fullStr Competing risk of mortality in association studies of non-fatal events
title_full_unstemmed Competing risk of mortality in association studies of non-fatal events
title_short Competing risk of mortality in association studies of non-fatal events
title_sort competing risk of mortality in association studies of non-fatal events
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8362942/
https://www.ncbi.nlm.nih.gov/pubmed/34388170
http://dx.doi.org/10.1371/journal.pone.0255313
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