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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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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Public Library of Science
2021
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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 |
collection | PubMed |
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. |
format | Online Article Text |
id | pubmed-8362942 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
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 |
work_keys_str_mv | AT buzkovapetra competingriskofmortalityinassociationstudiesofnonfatalevents |