Framingham – Anderson
| Background info: Framingham-Anderson |
| The Framingham-Anderson scale as originally presented by Anderson et al. has had many names associated with it in the literature, such as “Framingham risk score” or “Framingham heart study algorithm”. For ease of identifying and naming of the many scales developed by the Framingham Heart Study, we have chosen to use the name “Framingham-Anderson” to refer directly to this particular variant of the Framingham scale. It is one of the first CHD risk profiles from the Framingham Heart Study and has been validated in many population studies around the world. It was the instrument of choice recommended by NICE until 2010 and it is still one of the recommended scales. |
1) End-points measured
- Risk of developing CHD within a chosen number of years from the range 4 – 12 years
2) Profile of original population at baseline
- Framingham, US
- 30-74 years old
- Participant number: 5573 (2983 women and 2590 men)
- Baseline free of cardiovascular disease: stroke, transient ischemia, CHD (angina, coronary insufficiency, myocardial infarction, sudden death), congestive heart failure, intermittent claudication)
- Population selected from: Framingham original and offspring cohort
3) Validation (the following prospective studies excludes cohort with history of CVD and diabetes at baseline)
| Author | Year | Ethnicity | Age group | Follow up | Calibration ^ | Discrimination ^^ | Conclusion |
|---|---|---|---|---|---|---|---|
| Bastuji-Garin (1) | 2002 | Europe (INSIGHT) | 55-75 | median 3.7 years | 2.6 (CVD), 2.3 (CHD), 1.0 (stroke)^^^ | 0.661 | Overestimation of absolute CHD risk was observed in all countries |
| Bhopal (2) | 2005 | South Asians, UK | 25-74 | 9.6 (Europeans) 7.1 (South Asian) | Framingham followed expected results | ||
| Collins (3) | 2010 | UK (THIN) | 35-74 | >= 10 years | Framingham-Anderson: 0.750 (men), 0.774 (women) | Improvement of performance over Framingham-Anderson (also known as Framingham-NICE) | |
| Collins (4) | 2009 | UK (THIN) | 35-74 | >= 10 years | Framingham-Anderson:1.23 | Framingham-Anderson: 0.737 (men), 0.761 (women) | Improvement of performance over Framingham-Anderson (also known as Framingham-NICE) |
| Collins (5) | 2012 | UK (THIN) | 30-84 | >= 10 years | Women 35-74: Framingham-Anderson 1.48 Men 35-74: Framingham-Anderson 1.31 | Women 35-74: Framingham-Anderson 0.776 Men 35-74: Framingham-Anderson 0.752 | Better model than Framingham-Anderson (also known as Framingham-NICE) |
| de la Iglesia (6) | 2011 | England and Wales (THIN) | 35-74 | >= 10 years | 1.16 (1.25 men & 1.02 women) | 0.740 (men), 0.765 (women) | ASSIGN showed better discrimination |
| De Ruijter (7) | 2009 | Netherlands | >85 | 5 years | 0.53 | Framingham cannot identify those at high risk of CVD in very old people | |
| Ferrario (8) | 2005 | Italy (CUORE) | 35-69 | 10 years | 0.723 | CUORE equation showed better accuracy than the Framingham equation | |
| Friis-Moller (9) | 2009 | Europe, Australia | median 4.8 years | 1.14 (CVD), 1.35 (CHD), 1.51 (MI) | 0.775 (CVD, CHD), 0.769 (MI) | Own model works better than Framingham | |
| Hense (10) | 2003 | Germany (MONICA, PROCAM) | 35-64 | median 13.2 and 7.8 years | 1.6-5.7 | MONICA (0.78 men, 0.88 women) PROCAM (0.73 men, 0.77 women) | Predicted absolute risk was about twice as high as absolute risk observed |
| Hippisley-Cox (11) | 2007 | UK (QRESEARCH) | 35-74 | median 6.5 years | 1.35 | 0.7598 (men), 0.7744 (women) | QRISK outperforms Framingham for both calibration and discrimination |
| Hippisley-Cox (12) | 2008 | UK (THIN, QRESEARCH) | 35-74 | QRESEARCH (1.49 men, 1.19 women), THIN (1.32 men, 1.10 women) | QSEARCH (0.7619 men, 0.7759 women), THIN (0.7365 men, 0.7595 women) | Framingham over-predict CVD risk by 35%, ASSIGN by 36%, QRISK by 0.4% | |
| Hippisley-Cox (13) | 2008 | England and Wales (QRESEARCH) | 35-74 | mean 7.3 years (women), 6.9 years (men) | 0.779 (men), 0.800 (women) | QRISK2 has improved discrimination and calibration compared to Framingham-NICE | |
| Jimenez-Corona (14) | 2009 | Mexican | 35-64 | median 6.2 years | 3.17 (men), 1.57 (women) | Framingham overestimated incident MI and CHD death risk in men | |
| Knuiman (15) | 1997 | Western Australia | 10 years | ||||
| Liao (16) | 1999 | US (Framingham, NHANES I & II) | Mean: Framingham (49.6), NHANES I (53.2), II (54.3) | Framingham (24 years), NHANES I (20 years), II (15 years) | NHANES I (0.71 men, 0.80 women), II (0.74 men, 0.76 women) | Framingham risk model for the prediction of CHD mortality rates provides a reasonable rank ordering of risk for individuals in the US white population. | |
| Menotti (17) | 2000 | Italy (men only) | 40-59 | 23 years | Overestimates absolute coronary risk in countries characterised by a lower incidence of coronary events. | ||
| Milne (18) | 2003 | New Zealand | 35-74 | 5 year | Accurately predicts 5-year risk of hospitalisation or death from first CVD | ||
| Riddell (19) | 2010 | New Zealand (Maori, Pacific, Indian) | 5 years (median 2.11 years) | 0.989-0.978 (<15%), 1.024-1.041 (>15%) | Overestimates risk for New Zealand population but underestimates risk for combined high risk ethnic populations | ||
| Tunstall-Pedoe (20) | 2006 | Scottish (SHHEC) | 30-74 | 2.128-1.266 (men), 4-1.35 (women) | Overestimates risk overall, seriously underestimate variation in risk with deprivation. | ||
| Vergnaud (21) | 2008 | French (men only) | 45-60 | 10 years | 2.01 | 0.74 | Not valid for estimating absolute 10 year CHD risk in French population |
| Wannamethee (22) | 2005 | UK | 40-59 | 20 years | 0.67 | Framingham is a better predictor of CVD than metabolic syndrome | |
| Woodward (23) | 2007 | Scotland | 30-74 | 10 years | 0.69 | 0.716 (men), 0.741 (women) | ASSIGN shifts preventive treatment towards the socially deprived |
| Zomer (24) | 2011 | Australia | 30-74 (mean 50.6) | 5 years | >1 | 0.74 | Not ideal and calibration is needed |
| Zhang (25) | 2005 | Chinese | 18-74 | 13.5 years | 0.76 (CHD), 0.72 (ischaemic), 0.82 (haemorrhagic stroke) | Framingham scale greatly overestimates the risk of CHD in Orientals |
Note:
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4) Length of follow up
- approximately 12 years
5) Risk factors involved
- Non-modifiable risk factors
- Age
- Gender
- Modifiable risk factors
- Systolic and diastolic blood pressure
- Cholesterol (total, HDL)
- Smoking
- Diabetes
- Left ventricle hypertrophy
References
Primary publication:
Anderson KM, Wilson PW, Odell PM, Kannel WB. An updated coronary risk profile: a statement for health professionals. Circulation. 1991;83:356-362. http://circ.ahajournals.org/content/83/1/356.full.pdf
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5. Collins GS, Altman DG. Predicting the 10 year risk of cardiovascular disease in the United Kingdom: independent and external validation of an updated version of QRISK2. BMJ.2012;344:e4181.
6. 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.
7. de Ruijter W, Westendorp RGJ, Assendelft WJJ, et al. Use of Framingham risk score and new biomarkers to predict cardiovascular mortality in older people: population based observational cohort study. BMJ. 2009;338:a3083.
8. Ferrario M, Chiodini P, Chambless LE, et al. Prediction of coronary events in a low incidence population. Assessing accuracy of the CUORE Cohort Study prediction equation. International Journal of Epidemiology. 2005;34(2):413-421.
9. Friis-Moller N, Thiebaut R, Reiss P, et al. Predicting the risk of cardiovascular disease in HIV-infected patients: the data collection on adverse effects of anti-HIV drugs study. European Journal of Cardiovascular Prevention & Rehabilitation. 2010;17(5):491-501.
10. Hense H-W, Schulte H, Lowel H, Assmann G, Keil U. Framingham risk function overestimates risk of coronary heart disease in men and women from Germany–results from the MONICA Augsburg and the PROCAM cohorts. European Heart Journal. 2003;24(10):937-945.
11. Hippisley-Cox J, Coupland C, Vinogradova Y, Robson J, May M, Brindle P. Derivation and validation of QRISK, a new cardiovascular disease risk score for the United Kingdom: prospective open cohort study. BMJ (Clinical research ed.). 2007;335(7611):136.
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13. Hippisley-Cox J, Coupland C, Vinogradova Y, et al. Predicting cardiovascular risk in England and Wales: Prospective derivation and validation of QRISK2. BMJ. 28 Jun 2008;336(7659):1475-1482.
14. Jimenez-Corona A, Lopez-Ridaura R, Williams K, Gonzalez-Villalpando ME, Simon J, Gonzalez-Villalpando C. Applicability of Framingham risk equations for studying a low-income Mexican population. Salud Publica de Mexico. 2409;51(4):298-305.
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16. Liao Y, McGee DL, Cooper RS, Sutkowski MBE. How generalizable are coronary risk prediction models? Comparison of Framingham and two national cohorts. American Heart Journal. 1999;137(5):837-845.
17. Menotti A, Puddu PE, Lanti M. Comparison of the Framingham risk function-based coronary chart with risk function from an Italian population study. European Heart Journal. 2000;21(5):365-370.
18. Milne R, Gamble G, Whitlock G, Jackson R. Framingham Heart Study risk equation predicts first cardiovascular event rates in New Zealanders at the population level. The New Zealand medical journal. 7 Nov 2003;116(1185):U662.
19. Riddell T, Wells S, Jackson R, et al. Performance of Framingham cardiovascular risk scores by ethnic groups in New Zealand: PREDICT CVD-10. New Zealand Medical Journal. 19 Feb 2010;123(1309):50-61.
20. Tunstall-Pedoe H, Woodward M, estimation Sgor. By neglecting deprivation, cardiovascular risk scoring will exacerbate social gradients in disease. Heart. 2006;92(3):307-310.
21. Vergnaud AC, Bertrais S, Galan P, Hercberg S, Czernichow S. Ten-year risk prediction in French men using the Framingham coronary score: Results from the national SU.VI.MAX cohort. Preventive Medicine. July 2008;47(1):61-65.
22. Wannamethee SG, Shaper AG, Lennon L, Morris RW. Metabolic syndrome vs Framingham Risk Score for prediction of coronary heart disease, stroke, and type 2 diabetes mellitus. Archives of Internal Medicine. 2005;165(22):2644-2650.
23. Woodward M, Brindle P, Tunstall-Pedoe H, estimation Sgor. Adding social deprivation and family history to cardiovascular risk assessment: the ASSIGN score from the Scottish Heart Health Extended Cohort (SHHEC). Heart. 2007;93(2):172-176.
24. 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.
25. Zhang X-F, Attia J, D’Este C, Yu X-H, Wu X-G. A risk score predicted coronary heart disease and stroke in a Chinese cohort. Journal of Clinical Epidemiology. 2005;58(9):951-958.