Prediction of coronary heart disease using risk factor categories
Abstract
Background —The objective of this study was to examine the association of Joint National Committee (JNC-V) blood pressure and National Cholesterol Education Program (NCEP) cholesterol categories with coronary heart disease (CHD) risk, to incorporate them into coronary prediction algorithms, and to compare the discrimination properties of this approach with other noncategorical prediction functions. Methods and Results —This work was designed as a prospective, single-center study in the setting of a community-based cohort. The patients were 2489 men and 2856 women 30 to 74 years old at baseline with 12 years of follow-up. During the 12 years of follow-up, a total of 383 men and 227 women developed CHD, which was significantly associated with categories of blood pressure, total cholesterol, LDL cholesterol, and HDL cholesterol (all P <.001). Sex-specific prediction equations were formulated to predict CHD risk according to age, diabetes, smoking, JNC-V blood pressure categories, and NCEP total cholesterol and LDL cholesterol categories. The accuracy of this categorical approach was found to be comparable to CHD prediction when the continuous variables themselves were used. After adjustment for other factors, ≈28% of CHD events in men and 29% in women were attributable to blood pressure levels that exceeded high normal (≥130/85). The corresponding multivariable-adjusted attributable risk percent associated with elevated total cholesterol (≥200 mg/dL) was 27% in men and 34% in women. Conclusions —Recommended guidelines of blood pressure, total cholesterol, and LDL cholesterol effectively predict CHD risk in a middle-aged white population sample. A simple coronary disease prediction algorithm was developed using categorical variables, which allows physicians to predict multivariate CHD risk in patients without overt CHD.
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Epidemiological and pathological data have shown that obesity and diabetes are risk factors for cardiovascular disease.
“Although these studies did not directly report outcomes on long-term CVD events, epidemiological and pathological data have shown that obesity and diabetes are risk factors for cardiovascular disease [7,8].”
Epidemiological evidence shows that diabetes is an independent risk factor for the development of cardiovascular disease.
“Epidemiological evidence shows that diabetes is an independent risk factor for the development of CVD [7,11,12,13,14,15,16]”
From Recent Experimental Studies of Maternal Obesity, Diabetes during Pregnancy and the Developmental Origins of Cardiovascular Disease (2022) · cites this paper as [16]
The 1998 Wilson Framingham Risk Score for coronary heart disease became the basis of the risk calculator adopted by the Adult Treatment Panel of the National Cholesterol Education Program in the United States.
“The best known risk profile is the Framingham Risk Score for coronary heart disease, published in 1998 by Wilson and colleagues.50 This function became the basis of the risk calculator adopted by the Adult Treatment Panel of the National Cholesterol Education Program in the United States.51”
From The Framingham Heart Study and the epidemiology of cardiovascular disease: a historical perspective (2014) · cites this paper as [51]
The Framingham risk score is a global index of CHD risk used in clinical settings.
“The Framingham risk score is a global index of CHD risk used in clinical settings (8, 17, 30).”
From Effects of Low-Carbohydrate and Low-Fat Diets: A Randomized Trial (2014) · cites this paper as [17]
Framingham Risk Score is a Cox proportional hazards regression model developed in 1998 for predicting the 10-year risk of CHD in the general population free from CHD and not on treatment.
“This Cox proportional hazards regression model was developed in 1998 for predicting the 10-year risk of CHD in the general population free from CHD and not on treatment”
From A framework for meta-analysis of prediction model studies with binary and time-to-event outcomes (2019) · cites this paper as [4]
Randomized controlled trials show that statin use did not significantly decrease ASCVD risk in dialysis patients, suggesting the importance of implementing effective measures in patients with earlier stages of CKD.
“This finding is consistent with the results of randomized controlled trials revealing that the use of statin did not decrease the risk for ASCVD significantly in dialysis patients158, 159), suggesting the importance of implementing effective measures on patients with earlier stages of CKD.”
From Japan Atherosclerosis Society (JAS) guidelines for prevention of atherosclerotic cardiovascular diseases 2017 (2018) · cites this paper as [159]
Cumulative scores such as the metabolic syndrome and Framingham Risk Score have been shown to predict outcomes better than their individual components.
“These latter cumulative scores-like their analogs in the childhood psychosocial risk literature-have been shown to predict outcomes better than their individual components.179”
From Socio‐economic differentials in peripheral biology: Cumulative allostatic load (2010) · cites this paper as [179]
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- Authors
- Wilson, P. W. F., D’Agostino, R. B., Levy, D., Belanger, A. M., Silbershatz, H., & Kannel, W. B.
- Affiliations
- Boston University (US)
- From the Framingham Heart Study, National Heart, Lung, and Blood Institute, Framingham, Mass (P.W.F.W., D.L.); Boston University Mathematics Department, Boston, Mass (R.B.D., A.M.B., H.S.); and Framingham Heart Study, Boston University School of Medicine, Framingham, Mass (W.B.K.).
- Venue
- Circulation
- Published
- 1998-05-12
- Volume
- 97
- Issue
- 18
- Pages
- 1837-1847
- ISSN
- 0009-7322 (ISSN-L)
- 1524-4539
- OpenAlex
- W2165884492
- Cited by
- 9,581
- References
- 65
- Citations by year
- 2026: 162 · 2025: 229 · 2024: 257 · 2023: 259 · 2022: 312 · 2021: 389 · 2020: 332 · 2019: 344 · 2018: 328 · 2017: 410 · 2016: 432 · 2015: 490 · 2014: 572 · 2013: 558 · 2012: 555
- FWCI
- 95.99
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Circulation (publishedVersion)
- PubMed (publishedVersion)
- Funders
- National Institutes of Health (n01hc038038-022)
- National Heart, Lung, and Blood Institute (N01-HC-38038)
- Topics
- Health Sciences › Medicine › Surgery › Lipoproteins and Cardiovascular Health
- Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Health Promotion and Cardiovascular Prevention
- Health Sciences › Medicine › Cardiology and Cardiovascular Medicine › Cardiovascular Health and Risk Factors
- Keywords
- coronary artery disease, cardiovascular risk prediction, blood pressure categories, LDL cholesterol, HDL cholesterol, total cholesterol, risk prediction equations, attributable risk, middle-aged adults
- MeSH terms
- Adult, Aged, Algorithms, Blood Pressure, Cholesterol, Coronary Disease, Diabetes Mellitus, Female, Follow-Up Studies, Humans, Lipids, Cholesterol, LDL, Male, Middle Aged, National Health Programs, Risk Factors, Smoking, Cohort Studies, Comorbidity, Body Mass Index, Proportional Hazards Models
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
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