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Quantifying Importance of Major Risk Factors for Coronary Heart Disease

BACKGROUND: To optimize preventive strategies for coronary heart disease (CHD), it is essential to understand and appropriately quantify the contribution of its key risk factors. Our objective was to compare the associations of key modifiable CHD risk factors—specifically lipids, systolic blood pres...

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Autores principales: Pencina, Michael J., Navar, Ann Marie, Wojdyla, Daniel, Sanchez, Robert J., Khan, Irfan, Elassal, Joseph, D’Agostino, Ralph B., Peterson, Eric D., Sniderman, Allan D.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Lippincott Williams & Wilkins 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6433489/
https://www.ncbi.nlm.nih.gov/pubmed/30586759
http://dx.doi.org/10.1161/CIRCULATIONAHA.117.031855
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author Pencina, Michael J.
Navar, Ann Marie
Wojdyla, Daniel
Sanchez, Robert J.
Khan, Irfan
Elassal, Joseph
D’Agostino, Ralph B.
Peterson, Eric D.
Sniderman, Allan D.
author_facet Pencina, Michael J.
Navar, Ann Marie
Wojdyla, Daniel
Sanchez, Robert J.
Khan, Irfan
Elassal, Joseph
D’Agostino, Ralph B.
Peterson, Eric D.
Sniderman, Allan D.
author_sort Pencina, Michael J.
collection PubMed
description BACKGROUND: To optimize preventive strategies for coronary heart disease (CHD), it is essential to understand and appropriately quantify the contribution of its key risk factors. Our objective was to compare the associations of key modifiable CHD risk factors—specifically lipids, systolic blood pressure (SBP), diabetes mellitus, and smoking—with incident CHD events based on their prognostic performance, attributable risk fractions, and treatment benefits, overall and by age. METHODS: Pooled participant-level data from 4 observational cohort studies sponsored by the National Heart, Lung, and Blood Institute were used to create a cohort of 22 626 individuals aged 45 to 84 years who were initially free of cardiovascular disease. Individuals were followed for 10 years from baseline evaluation for incident CHD. Proportional hazards regression was used to estimate metrics of prognostic model performance (likelihood ratio, C index, net reclassification, discrimination slope), hazard ratios, and population attributable fractions for SBP, non–high-density lipoprotein cholesterol (non–HDL-C), diabetes mellitus, and smoking. Expected absolute risk reductions for antihypertensive and lipid-lowering treatment were assessed. RESULTS: Age, sex, and race capture 63% to 80% of the prognostic performance of cardiovascular risk models. In contrast, adding either SBP, non–HDL-C, diabetes mellitus, or smoking to a model with other risk factors increases the C index by only 0.004 to 0.013. However, primordial prevention could have a substantial effect as demonstrated by population attributable fractions of 28% for SBP≥130 mm Hg and 17% for non–HDL-C≥130 mg/dL. Similarly, lowering the SBP of all individuals to <130 mm Hg or lowering low-density lipoprotein cholesterol by 30% would be expected to lower a baseline 10-year CHD risk of 10.7% to 7.0 and 8.0, respectively (absolute risk reductions: 3.7% and 2.7%, respectively). Prognostic performance decreases with age (C indices for age groups 45–54, 55–64, 65–74, 75–84 are 0.75, 0.72, 0.66, and 0.62, respectively), whereas absolute risk reductions increase (SBP: 1.1%, 2.3%, 5.4%, 10.3%, respectively; non–HDL-C: 1.1%, 2.0%, 3.7%, 5.9%, respectively). CONCLUSIONS: Although individual modifiable CHD risk factors contribute only modestly to prognostic performance, our models indicate that eliminating or controlling these individual factors would lead to substantial reductions in total population CHD events. Metrics used to judge importance of risk factors should be tailored to the research objectives.
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spelling pubmed-64334892019-04-19 Quantifying Importance of Major Risk Factors for Coronary Heart Disease Pencina, Michael J. Navar, Ann Marie Wojdyla, Daniel Sanchez, Robert J. Khan, Irfan Elassal, Joseph D’Agostino, Ralph B. Peterson, Eric D. Sniderman, Allan D. Circulation Original Research Articles BACKGROUND: To optimize preventive strategies for coronary heart disease (CHD), it is essential to understand and appropriately quantify the contribution of its key risk factors. Our objective was to compare the associations of key modifiable CHD risk factors—specifically lipids, systolic blood pressure (SBP), diabetes mellitus, and smoking—with incident CHD events based on their prognostic performance, attributable risk fractions, and treatment benefits, overall and by age. METHODS: Pooled participant-level data from 4 observational cohort studies sponsored by the National Heart, Lung, and Blood Institute were used to create a cohort of 22 626 individuals aged 45 to 84 years who were initially free of cardiovascular disease. Individuals were followed for 10 years from baseline evaluation for incident CHD. Proportional hazards regression was used to estimate metrics of prognostic model performance (likelihood ratio, C index, net reclassification, discrimination slope), hazard ratios, and population attributable fractions for SBP, non–high-density lipoprotein cholesterol (non–HDL-C), diabetes mellitus, and smoking. Expected absolute risk reductions for antihypertensive and lipid-lowering treatment were assessed. RESULTS: Age, sex, and race capture 63% to 80% of the prognostic performance of cardiovascular risk models. In contrast, adding either SBP, non–HDL-C, diabetes mellitus, or smoking to a model with other risk factors increases the C index by only 0.004 to 0.013. However, primordial prevention could have a substantial effect as demonstrated by population attributable fractions of 28% for SBP≥130 mm Hg and 17% for non–HDL-C≥130 mg/dL. Similarly, lowering the SBP of all individuals to <130 mm Hg or lowering low-density lipoprotein cholesterol by 30% would be expected to lower a baseline 10-year CHD risk of 10.7% to 7.0 and 8.0, respectively (absolute risk reductions: 3.7% and 2.7%, respectively). Prognostic performance decreases with age (C indices for age groups 45–54, 55–64, 65–74, 75–84 are 0.75, 0.72, 0.66, and 0.62, respectively), whereas absolute risk reductions increase (SBP: 1.1%, 2.3%, 5.4%, 10.3%, respectively; non–HDL-C: 1.1%, 2.0%, 3.7%, 5.9%, respectively). CONCLUSIONS: Although individual modifiable CHD risk factors contribute only modestly to prognostic performance, our models indicate that eliminating or controlling these individual factors would lead to substantial reductions in total population CHD events. Metrics used to judge importance of risk factors should be tailored to the research objectives. Lippincott Williams & Wilkins 2019-03-26 2018-12-07 /pmc/articles/PMC6433489/ /pubmed/30586759 http://dx.doi.org/10.1161/CIRCULATIONAHA.117.031855 Text en © 2018 The Authors. Circulation is published on behalf of the American Heart Association, Inc., by Wolters Kluwer Health, Inc. This is an open access article under the terms of the Creative Commons Attribution Non-Commercial-NoDerivs (https://www.ahajournals.org/doi/suppl/10.1161/circulationaha.117.031855) License, which permits use, distribution, and reproduction in any medium, provided that the original work is properly cited, the use is noncommercial, and no modifications or adaptations are made.
spellingShingle Original Research Articles
Pencina, Michael J.
Navar, Ann Marie
Wojdyla, Daniel
Sanchez, Robert J.
Khan, Irfan
Elassal, Joseph
D’Agostino, Ralph B.
Peterson, Eric D.
Sniderman, Allan D.
Quantifying Importance of Major Risk Factors for Coronary Heart Disease
title Quantifying Importance of Major Risk Factors for Coronary Heart Disease
title_full Quantifying Importance of Major Risk Factors for Coronary Heart Disease
title_fullStr Quantifying Importance of Major Risk Factors for Coronary Heart Disease
title_full_unstemmed Quantifying Importance of Major Risk Factors for Coronary Heart Disease
title_short Quantifying Importance of Major Risk Factors for Coronary Heart Disease
title_sort quantifying importance of major risk factors for coronary heart disease
topic Original Research Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6433489/
https://www.ncbi.nlm.nih.gov/pubmed/30586759
http://dx.doi.org/10.1161/CIRCULATIONAHA.117.031855
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