Framingham General Cardiovascular Risk Profile
| To differentiate this Framingham scale from others, some papers have referred to it as the Framingham-D’Agostino scale (after the author) or the Cox-Framingham scale (as it was derived using the Cox proportional hazards model). |
1) End-points measured
- 10-year risk of any cardiovascular disease (CVD) event.
- CVD is defined to include:
- Coronary heart disease (coronary death, myocardial infarction, coronary insufficiency, angina)
- Cerebrovascular events (including ischemic stroke, hemorrhagic stroke, transient ischemic attack)
- Peripheral artery disease (intermittent claudication)
- Heart failure
2) Profile of original population at baseline
- Framingham, USA
- Age: 30 to 74 (mean age 49)
- Baseline free of prevalent CVD
- Participant number: 8491 (4522 women)
- Population selected from:
Framingham Heart Study sample: a group of randomly selected persons in the age where arteriosclerotic and hypertensive cardiovascular disease are known to develop but free of definite signs of CVD (1)
– Note that since the basic sampling unit was the household, many spouses entered the study together
Framingham offspring study: 2656 offspring (aged 12 to 58) of 1202 couples examined. (2) - Limitations of the Framingham cohort (3):
- Developed during the peak incidence of cardiovascular disease in America. Therefore may overestimate risk by up to 50% in contemporary northern European populations.
- Cohort is almost entirely white and recalibration may be needed in some ethnically diverse population
- Equation may underestimate risk in high risk subgroups (e.g. patients from deprived areas, potentially exacerbating health inequalities.
- Risk factors such as social deprivation, body mass index, family history of cardiovascular disease and current treatment with antihypertensives.
3) Validation (the following prospective studies excludes cohort with history of CVD and diabetes at baseline)
| Artigao-Rodenas (4) | 2013 | Spain (Albacete) | 30-74 | 10 years | Stratified according to sex and age | women 0.789 men 0.780 | New model of Framingham provided acceptable results of discrimination and consistency. |
|---|---|---|---|---|---|---|---|
| Badheka (5) | 2013 | United States (NHANES III) | 60.5 +/- 13.6 | 12.5 +/- 4.5 years | Hosmer-Lemeshow test 21.9 (Framingham alone) 10.5 (Framingham + QRS duration) | 0.8102 (Framingham alone) 0.8131 (Framingham + QRS duration) | A model including QRS duration in addition to traditional risk factors was associated with improved CV risk prediction. |
| Badheka (6) | 2013 | United States (NHANES III) | 60.5 +/- 13.6 | 12.5 +/- 4.5 years | Hosmer-Lemeshow test 15.14 (Framingham adjusted for traditional risk factors) 10.98 (Framingham adjusted for traditional risk factors and ECG abnormalities) | 0.851 (Framingham adjusted for traditional risk factors) 0.852 (Framingham adjusted for traditional risk factors and ECG abnormalities) | Further studies needed to assess the prospective application of ECG abnormalities in cardiovascular risk prediction |
| Bell (7) | 2012 | Framingham offspring study | 30-74 | 12 years (maximum) | Hosmer-Lemeshow calibration plots | 0.778 (one measurement of risk factors) 0.781 (average of two measurements of risk factors) | Averaging two measurements of blood pressure and lipids resulted in marked increase in the predictiveness of these risk factors |
| Bell (8) | 2014 | Sweden (Uppsala Longitudinal Study of Adult Men) | 70 | 17.3 years | Groennesby-Borgan tests 0.27 (Framingham only) 0.54 (Framingham and ambulatory systolic BP) | Improvement in discrimination (c-statistic): 0.011 | In addition to standard cardiovascular risk assessment it is not clear that ambulatory BP measurement provides further incremental value. |
| Collins (9) | 2009 | British (THIN database) | 35-74 | ≥ 10 years | 1.18 (1.25 men, 1.04 women) | 0.752 (men), 0.770 (women) | Improvement of performance over Framingham-NICE |
| de la Iglesia (10) | 2011 | English & Wales (THIN database) | 35-74 | ≥ 10 years | 1.17 (1.25 men, 1.04 women) | 0.752 (men), 0.771 (women) | ASSIGN showed better discrimination. For calibration, ASSIGN performed as well as or better than QRISK |
| Dhamoon (11) | 2011 | US (Northern Manhattan Study) | ≥ 40 | 10 years (median) | Adding stroke to the risk stratification outcome cluster resulted in a 55% relative increase in estimated risk | ||
| Gander (12) | 2014 | US: Aerobics Center Longitudinal Study (ACLS) population | 42 (mean), 75% men, >95% non-Hispanic whites | 12 years | 0.7697 | Framingham Risk Score significantly predicts CHD events in the ACLS cohort. | |
| Goh (13) | 2014 | Australian adult women | 20-69 | 10 years | Hosmer-Lemeshow chi sq: 4.74 | 0.858 | Both Framingham risk score model and SCORE risk chart for low-risk regions are recommended for use in Australian women population for predicting 10-year CVD mortality risk. |
| Hurley (14) | 2010 | Non-Hispanic white, Hispanic black, Mexican American | 40-80 | 10 years | 0.8126 (non-Hispanic black) 0.7679 (non-Hispanic black) 0.7854 (Mexican American) | Predict CVD mortality equally well in all 3 groups | |
| Jee (15) | 2014 | Korean | 45.8 (men) 47.6 (women) | 10 years | 3-6 times as many CHD events than observed | 0.764 (men), 0.815 (women) | Framingham risk function overestimates the risk of CVD in the Korean population. |
| Liu (16) | 2004 | Chinese | 35-64 | 10 years | 0.705 (men), 0.742 (women) | Framingham functions overestimate risk of CHD in the Chinese population | |
| Majed (17) | 2013 | France and Ireland (PRIME study) | 50-59 (men only) | 10 years | 1.94 (PRIME-combined) 2.23 (PRIME-France) 1.42 (PRIME-Ireland) | 0.68 (PRIME-combined) 0.67 (PRIME-France) 0.67 (PRIME-France) | The calibrated Framingham equation predicted accurate number of CHD and stroke events but discriminated poorly individuals at higher from those at lower event risk. |
| Peng (18) | 2014 | Inner Mongolian | 10 years | Modified Hosmer-Lemeshow chi-sq: 9.22 | 0.81 | Framingham General Cardiovascular Risk Score had a good performance in predicting 10-year risk of CVD in Mongolians. | |
| Versteylen (19) | 2011 | Netherlands (with chest pain) | 19±9 months | 0.74 | Ability of Framingham and SCORE to predict was similar | ||
| Zomer (20) | 2011 | Australia | 30-74 (mean 50.6) | 5 years | 0.76 | Discrimination ability was increased compared to Framingham-Anderson but not significant. Both equations not ideal. |
Note:
|
4) Length of follow up
- Maximum follow up period of 12 years
5) Risk factors involved
- Non-modifiable risk factors
- Age
- Gender
- Modifiable risk factors
- Diabetes
- Smoking
- Treated and untreated Systolic Blood Pressure
- Total cholesterol
- HDL cholesterol OR BMI
References
Primary publication:
D’Agostino RB Sr, Vasan RS, Pencina MJ, et al. General Cardiovascular Risk Profile for Use in Primary Care: The Framingham Heart Study. Circulation. 2008;117:743-753. http://circ.ahajournals.org/content/117/6/743.full
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2. Kannel WB, Feinleib M, McNamara PM, Garrison RJ, Castelli WP. An investigation of coronary heart disease in families: the Framingham offspring study. Am J Epidemiol. 1979;110:281-290. http://www.ncbi.nlm.nih.gov/pubmed/474565
3. Hippisley-Cox J et al. Derivation and validation of QRISK, a new cardiovascular disease risk score for the United Kingdom: prospective open cohort study.BMJ. 2007 Jul 21;335(7611):136.http://www.qrisk.org/BMJ-QRISK1.pdf
4. Artigao-Rodenas LM, Carbayo-Herencia JA, Divison-Garrote JA, et. al. Framingham Risk Score for Prediction of Cardiovascular Disease: A Population Based Study from Southern Europe. PLos One. 2013;8(9):e73529.
5. Badheka AO, Singh V, Patel NJ, et. al. QRS duration on electrocardiography and cardiovascular mortality (From the National health and nutrition examination survey – III). Am J Med. 2013;126(4):319-326.
6. Badheka AO, Patel N, Tuliani TA, et. al. Electrocardiographic abnormalities and reclassification of cardiovascular risk: insights from NHANES-III. Am J Cardiol. 2013;112(5):671-677.
7. Bell K, Hayen A, McGeechan K, et. al. Effects of additional blood pressure and lipid measurement on the prediction of cardiovascular risk. Eur J Prev Cardiol
8. Bell KJL, Beller E, Sundstrom J, et. al. Ambulatory blood pressure adds little to Framingham Risk Score for the primary prevention of cardiovascular disease in older men: secondary analysis of observational study data. BMJ Open. 2014;4:e006044.
9. Chamnan P, Simmons RK, Khaw K-T, Wareham NJ, Griffin SJ. Estimating the population impact of screening strategies for identifying and treating people at high risk of cardiovascular disease: modelling study. BMJ. 2010;340:c1693.
9. Collins GS, Altman DG. An independent external validation and evaluation of QRISK cardiovascular risk prediction: a prospective open cohort study. BMJ (Clinical research ed.). 2009;339:b2584.
10. de la Iglesia B, Potter JF, Poulter NR, Robins MM, Skinner J. Performance of the ASSIGN cardiovascular disease risk score on a UK cohort of patients from general practice. Heart. 2011;97(6):491-499.
11. Dhamoon MS, Moon YP, Paik MC, et al. The inclusion of stroke in risk stratification for primary prevention of vascular events: the Northern Manhattan Study. Stroke. 2011;42(10):2878-2882.
12. Gander J, Sui Xuemei, Hazlett LJ, et al. Factors related to coronary heart disease risk among men: validation of the Framingham Risk Score. Preventing Chronic Disease. 2014;11:E140.
13. Goh LGH, Welborn TA, Dhaliwal SS. Independent external validation of cardiovascular disease mortality in women utilising Framingham and SCORE risk models: a mortality follow-up study. BMC Women’s Health. 2014;14:118.
14. Hurley LP, Dickinson LM, Estacio RO, Steiner JF, Havranek EP. Prediction of cardiovascular death in racial/ethnic minorities using Framingham risk factors. Circulation. Cardiovascular Quality & Outcomes. 2010;3(2):181-187.
15. Jee SH, Jang Y, Oh DJ, et al. A coronary heart disease prediction model: the Korean heart study. BMJ Open. 2014;4:e005025.
16. Liu J, Hong Y, D’Agostino RB, Sr., et al. Predictive value for the Chinese population of the Framingham CHD risk assessment tool compared with the Chinese Multi-Provincial Cohort Study. JAMA. 2004;291(21):2591-2599.
17. Majed B, Tafflet M, Kee F, et al. External validation of the 2008 Framingham cardiovascular risk equation for CHD and stroke events in a European population of middle-aged men. The PRIME study. Preventive Medicine. 2013;57:49-54.
18. Peng H, Jiao Y, Zeng Q, et al. Utility of Framingham general cardiovascular disease risk score for predicting 10-year cardiovascular risk in an inner Mongolian population: a prospective cohort study. International Journal of Cardiology. 2014;172(1):274-275.
19. Versteylen MO, Joosen IA, Shaw LJ, Narula J, Hofstra L. Comparison of Framingham, PROCAM, SCORE, and Diamond Forrester to predict coronary atherosclerosis and cardiovascular events. Journal of Nuclear Cardiology. 2011;18(5):904-911.
20. Zomer E, Owen A, Magliano DJ, Liew D, Reid C. Validation of two Framingham cardiovascular risk prediction algorithms in an Australian population: the ‘old’ versus the ‘new’ Framingham equation. European Journal of Cardiovascular Prevention & Rehabilitation. 2011;18(1):115-120.
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