Comparison of competing risks models based on cumulative incidence function in analyzing time to cardiovascular diseases

<div><div><p class="abstract"><strong>BACKGROUND:</strong> Competing risks arise when the subject is exposed to more than one cause of failure. Data consists of the time that the subject failed and an indicator of which risk caused the subject to fail.</p&g...

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Main Authors: Minoo Dianatkhah, Mehdi Rahgozar, Mohammad Talaei, Masoud Karimloua, Masoumeh Sadeghi, Shahram Oveisgharan, Nizal Sarrafzadegan
Format: Article
Language:English
Published: Vesnu Publications 2014-01-01
Series:ARYA Atherosclerosis
Online Access:http://arya.mui.ac.ir/index.php/arya/article/view/746
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spelling doaj-e574527208d242de8a9c3814df4510022020-11-24T23:27:08ZengVesnu PublicationsARYA Atherosclerosis1735-39552251-66382014-01-01101612446Comparison of competing risks models based on cumulative incidence function in analyzing time to cardiovascular diseasesMinoo Dianatkhah0Mehdi Rahgozar1Mohammad Talaei2Masoud Karimloua3Masoumeh Sadeghi4Shahram Oveisgharan5Nizal Sarrafzadegan6Department of Statistics and Computer Sciences, University of Social Welfare and Rehabilitation Sciences, Tehran AND Isfahan Cardiovascular Research Center, Isfahan Cardiovascular Research Institute, Isfahan University of Medical Sciences, Isfahan, IranAssistant Professor, Department of Statistics and Computer Sciences, University of Social Welfare and Rehabilitation Sciences, Tehran, IranIsfahan Cardiovascular Research Center, Isfahan Cardiovascular Research Institute, Isfahan University of Medical Sciences, Isfahan, Iran AND Saw Swee Hock School of Public Health, National University of Singapore, Singapore, SingaporeAssistant Professor, Department of Statistics and Computer Sciences, University of Social Welfare and Rehabilitation Sciences, Tehran, IranAssociate Professor, Cardiac Rehabilitation Research Center, Isfahan Cardiovascular Research Institute, Isfahan University of Medical Sciences, Isfahan, IranDepartment of Neurology, Tehran University of Medical Sciences, Tehran, IranProfessor, Isfahan Cardiovascular Research Center, Isfahan Cardiovascular Research Institute, Isfahan University of Medical Sciences, Isfahan, Iran<div><div><p class="abstract"><strong>BACKGROUND:</strong> Competing risks arise when the subject is exposed to more than one cause of failure. Data consists of the time that the subject failed and an indicator of which risk caused the subject to fail.</p> <p class="abstract"><strong>METHODS:</strong> With three approaches consisting of Fine and Gray, binomial, and pseudo-value, all of which are directly based on cumulative incidence function, cardiovascular disease data of the Isfahan Cohort Study were analyzed. Validity of proportionality assumption for these approaches is the basis for selecting appropriate models. Such as for the Fine and Gray model, establishing proportionality assumption is necessary. In the binomial approach, a parametric, non-parametric, or semi-parametric model was offered according to validity of assumption. However, pseudo-value approaches do not need to establish proportionality.</p> <p class="abstract"><strong>RESULTS:</strong><strong> </strong>Following fitting the models to data, slight differences in parameters and variances estimates were seen among models. This showed that semi-parametric multiplicative model and the two models based on pseudo-value approach could be used for fitting this kind of data.</p> <p class="abstract"><strong>CONCLUSION:</strong> We would recommend considering the use of competing risk models instead of normal survival methods when subjects are exposed to more than one cause of failure.</p> <p class="abstract">&nbsp;</p></div> <strong>Keywords:</strong> Competing Risks, Cumulative Incidence Function, Fine and Gray Model, Binomial Approach, Pseudo-value Approach, Cardiovascular Diseases<p class="abstract">&nbsp;</p></div>http://arya.mui.ac.ir/index.php/arya/article/view/746
collection DOAJ
language English
format Article
sources DOAJ
author Minoo Dianatkhah
Mehdi Rahgozar
Mohammad Talaei
Masoud Karimloua
Masoumeh Sadeghi
Shahram Oveisgharan
Nizal Sarrafzadegan
spellingShingle Minoo Dianatkhah
Mehdi Rahgozar
Mohammad Talaei
Masoud Karimloua
Masoumeh Sadeghi
Shahram Oveisgharan
Nizal Sarrafzadegan
Comparison of competing risks models based on cumulative incidence function in analyzing time to cardiovascular diseases
ARYA Atherosclerosis
author_facet Minoo Dianatkhah
Mehdi Rahgozar
Mohammad Talaei
Masoud Karimloua
Masoumeh Sadeghi
Shahram Oveisgharan
Nizal Sarrafzadegan
author_sort Minoo Dianatkhah
title Comparison of competing risks models based on cumulative incidence function in analyzing time to cardiovascular diseases
title_short Comparison of competing risks models based on cumulative incidence function in analyzing time to cardiovascular diseases
title_full Comparison of competing risks models based on cumulative incidence function in analyzing time to cardiovascular diseases
title_fullStr Comparison of competing risks models based on cumulative incidence function in analyzing time to cardiovascular diseases
title_full_unstemmed Comparison of competing risks models based on cumulative incidence function in analyzing time to cardiovascular diseases
title_sort comparison of competing risks models based on cumulative incidence function in analyzing time to cardiovascular diseases
publisher Vesnu Publications
series ARYA Atherosclerosis
issn 1735-3955
2251-6638
publishDate 2014-01-01
description <div><div><p class="abstract"><strong>BACKGROUND:</strong> Competing risks arise when the subject is exposed to more than one cause of failure. Data consists of the time that the subject failed and an indicator of which risk caused the subject to fail.</p> <p class="abstract"><strong>METHODS:</strong> With three approaches consisting of Fine and Gray, binomial, and pseudo-value, all of which are directly based on cumulative incidence function, cardiovascular disease data of the Isfahan Cohort Study were analyzed. Validity of proportionality assumption for these approaches is the basis for selecting appropriate models. Such as for the Fine and Gray model, establishing proportionality assumption is necessary. In the binomial approach, a parametric, non-parametric, or semi-parametric model was offered according to validity of assumption. However, pseudo-value approaches do not need to establish proportionality.</p> <p class="abstract"><strong>RESULTS:</strong><strong> </strong>Following fitting the models to data, slight differences in parameters and variances estimates were seen among models. This showed that semi-parametric multiplicative model and the two models based on pseudo-value approach could be used for fitting this kind of data.</p> <p class="abstract"><strong>CONCLUSION:</strong> We would recommend considering the use of competing risk models instead of normal survival methods when subjects are exposed to more than one cause of failure.</p> <p class="abstract">&nbsp;</p></div> <strong>Keywords:</strong> Competing Risks, Cumulative Incidence Function, Fine and Gray Model, Binomial Approach, Pseudo-value Approach, Cardiovascular Diseases<p class="abstract">&nbsp;</p></div>
url http://arya.mui.ac.ir/index.php/arya/article/view/746
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