Validation of the Framingham Coronary Heart Disease Prediction Scores: Results of a Multiple Ethnic Groups Investigation
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CONTEXT: The Framingham Heart Study produced sex-specific coronary heart disease (CHD) prediction functions for assessing risk of developing incident CHD in a white middle-class population. Concern exists regarding whether these functions can be generalized to other populations. OBJECTIVE: To test the validity and transportability of the Framingham CHD prediction functions per a National Heart, Lung, and Blood Institute workshop organized for this purpose. DESIGN, SETTING, AND SUBJECTS: Sex-specific CHD functions were derived from Framingham data for prediction of coronary death and myocardial infarction. These functions were applied to 6 prospectively studied, ethnically diverse cohorts (n = 23 424), including whites, blacks, Native Americans, Japanese American men, and Hispanic men: the Atherosclerosis Risk in Communities Study (1987-1988), Physicians' Health Study (1982), Honolulu Heart Program (1980-1982), Puerto Rico Heart Health Program (1965-1968), Strong Heart Study (1989-1991), and Cardiovascular Health Study (1989-1990). MAIN OUTCOME MEASURES: The performance, or ability to accurately predict CHD risk, of the Framingham functions compared with the performance of risk functions developed specifically from the individual cohorts' data. Comparisons included evaluation of the equality of relative risks for standard CHD risk factors, discrimination, and calibration. RESULTS: For white men and women and for black men and women the Framingham functions performed reasonably well for prediction of CHD events within 5 years of follow-up. Among Japanese American and Hispanic men and Native American women, the Framingham functions systematically overestimated the risk of 5-year CHD events. After recalibration, taking into account different prevalences of risk factors and underlying rates of developing CHD, the Framingham functions worked well in these populations. CONCLUSIONS: The sex-specific Framingham CHD prediction functions perform well among whites and blacks in different settings and can be applied to other ethnic groups after recalibration for differing prevalences of risk factors and underlying rates of CHD events.
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Subgroup validity may be a concern in the context of sampling bias, where a minority group may be insufficiently represented in model development data (e.g., certain ethnic groups in the Framingham population) and the model might be tailored to the majority group.
“Subgroup validity may also be a concern in the context of sampling bias, where a minority group may be insufficiently represented in model development data (e.g., certain ethnic groups in the Framingham population25) and the model might be tailored to the majority group.”
From Predictably unequal: understanding and addressing concerns that algorithmic clinical prediction may increase health disparities (2020) · cites this paper as [25]
Sampling bias was a well-known issue with the Framingham Heart Study, which drew its study population from the racially homogeneous town of Framingham, Massachusetts, and consequently can lead to both over- and under-treatment of certain ethnic minorities.
“Sampling bias was a well-known issue with the highly influential Framingham Heart Study, which drew its study population from the racially homogeneous town of Framingham, Massachusetts—and consequently can lead to both over- and under-treatment of certain ethnic minorities25,26.”
From Predictably unequal: understanding and addressing concerns that algorithmic clinical prediction may increase health disparities (2020) · cites this paper as [25]
The Framingham Risk Score is the best available current approach for global risk assessment, and although it was derived from a specific geographic area and may not apply to all populations, its performance within subgroups has been assessed and is good.
“The Framingham Risk Score is the best available current approach, and although it was derived from a specific geographic area and thus may not apply to all populations, its performance within subgroups has been assessed and is good.124,125”
Absolute levels of predicted hard coronary heart disease risk increase substantially with increasing risk factor burden, and risk is augmented further by increases in blood pressure levels from optimal to marked hypertension in men and similarly for women.
“As shown in Figure 1, absolute levels of predicted hard CHD risk (including CHD death or nonfatal myocardial infarction) increase substantially with increasing risk factor burden, and risk is augmented still further by increases in BP levels from optimal to marked hypertension in men and similarly for women.63”
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References 20 · Cited by 2,108
Research works printed but not linked: 5
- Coronary Risk Handbook: Estimating Risk of Coro- nary Heart Disease in Daily Practice. New York, NY: American Heart Association; 1973:1-35.
- Grundy SM, D'Agostino RB Sr, Mosca L, et al. Car- diovascular risk assessment based on US cohort stud- ies: findings from a National Heart, Lung, and Blood Institute workshop. Circulation. 2001;104:1-6.
- Garcia-Palmieri MR, Costas R. Risk factors of coro- nary heart disease: a prospective epidemiologic study in Puerto Rico. In: Yu PH, Goodwin JF, eds. Progress in Cardiology. Vol 14. Philadelphia, Pa: Lea & Fe- biger; 1986:101-190.
- D'Agostino RB Sr, Griffith JL, Schmid CH, Terrin N. Measures for evaluating model performance. From: Annual Meeting of the American Statistical Associa- tion; Chicago, Ill, August 1996. In: American Statis- tical Association 1996 Proceedings of the Section on Biometrics. Alexandria, Va: American Statistical As- sociation; 1997:253-258.
- Nam B-H. Discrimination and Calibration in Sur- vival Analysis [dissertation]. Boston, Mass: Boston Uni- versity; 2000.
- Authors
- D'Agostino, R. B., Grundy, S., Sullivan, L. M., Wilson, P., & for the CHD Risk Prediction Group
- Affiliations
- Boston University (US)
- Venue
- JAMA
- Publisher
- American Medical Association (AMA)
- Published
- 2001-07-11
- Volume
- 286
- Issue
- 2
- Pages
- 180
- ISSN
- 0002-9955 (ISSN-L)
- 0098-7484
- OpenAlex
- W2106665921
- Cited by
- 2,108
- References
- 20
- Citations by year
- 2026: 26 · 2025: 49 · 2024: 55 · 2023: 55 · 2022: 72 · 2021: 80 · 2020: 67 · 2019: 60 · 2018: 73 · 2017: 109 · 2016: 81 · 2015: 111 · 2014: 115 · 2013: 126 · 2012: 152
- FWCI
- 59.57
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- JAMA (publishedVersion)
- PubMed (publishedVersion)
- Funders
- Strong
- National Institutes of Health
- National Heart, Lung, and Blood Institute (N01-HC-380380)
- Topics
- 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
- Health Sciences › Medicine › Surgery › Lipoproteins and Cardiovascular Health
- Keywords
- Framingham risk equation, coronary artery disease, cardiovascular risk prediction, generalizability, recalibration, ethnic differences, myocardial infarction, coronary heart disease mortality, discrimination (statistics), calibration, Atherosclerosis Risk in Communities Study, Honolulu Heart Program, Strong Heart Study, Cardiovascular Health Study, Physicians' Health Study
- MeSH terms
- Asian, Black or African American, Coronary Disease, Data Interpretation, Statistical, Female, Hispanic or Latino, Humans, Indians, North American, Male, Research Design, Risk Factors, Socioeconomic Factors, United States, Multicenter Studies as Topic, Proportional Hazards Models, Risk Assessment, White People
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