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A new look at risk patterns related to coronary heart disease incidence using survival tree analysis: 12 Years Longitudinal Study

We identified risk patterns associated with incident coronary heart disease (CHD) using survival tree, and compared performance of survival tree versus Cox proportional hazards (Cox PH) in a cohort of Iranian adults. Data on 8,279 participants (3,741 men) aged ≥30 yr were used to analysis. Survival...

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Autores principales: Ramezankhani, Azra, Bagherzadeh-Khiabani, Farideh, Khalili, Davood, Azizi, Fereidoun, Hadaegh, Farzad
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5468345/
https://www.ncbi.nlm.nih.gov/pubmed/28607472
http://dx.doi.org/10.1038/s41598-017-03577-0
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author Ramezankhani, Azra
Bagherzadeh-Khiabani, Farideh
Khalili, Davood
Azizi, Fereidoun
Hadaegh, Farzad
author_facet Ramezankhani, Azra
Bagherzadeh-Khiabani, Farideh
Khalili, Davood
Azizi, Fereidoun
Hadaegh, Farzad
author_sort Ramezankhani, Azra
collection PubMed
description We identified risk patterns associated with incident coronary heart disease (CHD) using survival tree, and compared performance of survival tree versus Cox proportional hazards (Cox PH) in a cohort of Iranian adults. Data on 8,279 participants (3,741 men) aged ≥30 yr were used to analysis. Survival trees identified seven subgroups with different risk patterns using four [(age, non-HDL-C, fasting plasma glucose (FPG) and family history of diabetes] and five [(age, systolic blood pressure (SBP), non-HDL-C, FPG and family history of CVD] predictors in women and men, respectively. Additional risk factors were identified by Cox models which included: family history of CVD and waist circumference (in both genders); hip circumference, former smoking and using aspirin among men; diastolic blood pressure and lipid lowering drug among women. Survival trees and multivariate Cox models yielded comparable performance, as measured by integrated Brier score (IBS) and Harrell’s C-index on validation datasets; however, survival trees produced more parsimonious models with a minimum number of well recognized risk factors of CHD incidence, and identified important interactions between these factors which have important implications for intervention programs and improve clinical decision making.
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spelling pubmed-54683452017-06-14 A new look at risk patterns related to coronary heart disease incidence using survival tree analysis: 12 Years Longitudinal Study Ramezankhani, Azra Bagherzadeh-Khiabani, Farideh Khalili, Davood Azizi, Fereidoun Hadaegh, Farzad Sci Rep Article We identified risk patterns associated with incident coronary heart disease (CHD) using survival tree, and compared performance of survival tree versus Cox proportional hazards (Cox PH) in a cohort of Iranian adults. Data on 8,279 participants (3,741 men) aged ≥30 yr were used to analysis. Survival trees identified seven subgroups with different risk patterns using four [(age, non-HDL-C, fasting plasma glucose (FPG) and family history of diabetes] and five [(age, systolic blood pressure (SBP), non-HDL-C, FPG and family history of CVD] predictors in women and men, respectively. Additional risk factors were identified by Cox models which included: family history of CVD and waist circumference (in both genders); hip circumference, former smoking and using aspirin among men; diastolic blood pressure and lipid lowering drug among women. Survival trees and multivariate Cox models yielded comparable performance, as measured by integrated Brier score (IBS) and Harrell’s C-index on validation datasets; however, survival trees produced more parsimonious models with a minimum number of well recognized risk factors of CHD incidence, and identified important interactions between these factors which have important implications for intervention programs and improve clinical decision making. Nature Publishing Group UK 2017-06-12 /pmc/articles/PMC5468345/ /pubmed/28607472 http://dx.doi.org/10.1038/s41598-017-03577-0 Text en © The Author(s) 2017 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.
spellingShingle Article
Ramezankhani, Azra
Bagherzadeh-Khiabani, Farideh
Khalili, Davood
Azizi, Fereidoun
Hadaegh, Farzad
A new look at risk patterns related to coronary heart disease incidence using survival tree analysis: 12 Years Longitudinal Study
title A new look at risk patterns related to coronary heart disease incidence using survival tree analysis: 12 Years Longitudinal Study
title_full A new look at risk patterns related to coronary heart disease incidence using survival tree analysis: 12 Years Longitudinal Study
title_fullStr A new look at risk patterns related to coronary heart disease incidence using survival tree analysis: 12 Years Longitudinal Study
title_full_unstemmed A new look at risk patterns related to coronary heart disease incidence using survival tree analysis: 12 Years Longitudinal Study
title_short A new look at risk patterns related to coronary heart disease incidence using survival tree analysis: 12 Years Longitudinal Study
title_sort new look at risk patterns related to coronary heart disease incidence using survival tree analysis: 12 years longitudinal study
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5468345/
https://www.ncbi.nlm.nih.gov/pubmed/28607472
http://dx.doi.org/10.1038/s41598-017-03577-0
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