Assessing 10-year coronary heart disease risk in people with Type 2 diabetes mellitus: Framingham versus United Kingdom Prospective Diabetes Study


Aims: Previous studies have suggested that the Framingham coronary heart disease risk prediction equation underestimates risk among people with Type 2 diabetes. We compared the 10-year absolute risks of coronary heart disease (CHD) using a Framingham equation and a United Kingdom Prospective Diabetes Study (UKPDS) equation in adults with Type 2 diabetes. Methods: Participants were from a cross-sectional survey of a randomly selected population. There were 461 people with newly (n = 132) or previously diagnosed (n = 329) diabetes aged 35 to 74 years with no past history of cardiovascular disease or nephropathy. We examined predicted 10-year CHD risk by age, gender, and newly or previously diagnosed diabetes. Results: Overall the mean 10-year CHD risks predicted by the two equations were similar. Among men, the UKPDS and Framingham scores were almost identical below 60 years of age but at older ages, the UKPDS score was 4% - 11% higher than Framingham. For women, the Framingham score was higher than the UKPDS score between ages 40 and 65 years, but the UKPDS score was about 4% - 5% higher for women aged 70 years and over. The UKPDS equation tended to give higher risk estimates in people with a predicted 10-year Framingham CHD risk above 15%. Conclusion: Framingham CHD risk scores tended to be lower than UKPDS scores primarily in people above standard thresholds for drug treatment, so the clinical impact of underestimating risk is likely to be limited. Moreover, the UKPDS equation predicted lower risks than Framingham for women and newly diagnosed diabetes at otherwise low to moderate CHD risk, which could result in later initiation of therapy in these groups if the UKPDS score was used instead of the Framingham score.

Share and Cite:

Metcalf, P. , Wells, S. and Jackson, R. (2014) Assessing 10-year coronary heart disease risk in people with Type 2 diabetes mellitus: Framingham versus United Kingdom Prospective Diabetes Study. Journal of Diabetes Mellitus, 4, 12-18. doi: 10.4236/jdm.2014.41003.

Conflicts of Interest

The authors declare no conflicts of interest.


[1] Stevens, R., Kothari, V., Adler, A. and Stratton, I. (2001) The UKPDS risk engine: A model for the risk of coronary heart disease in Type II diabetes (UKPDS 56). Clinical Science, 101, 671-679.
[2] McEwan, P., Williams, J., Griffiths, J., Bagust, A., Peters, J., Hopkinson, P. and Currie, C.J. (2004) Evaluating the performance of the Framingham equations in a population with diabetes. Diabetic Medicine, 21, 318-323.
[3] Coleman, R., Stevens, R., Retnakaran, R. and Holman, R. (2007) Framingham, SCORE, and DECODE risk equations do not provide reliable cardiovascular risk estimates in Type 2 diabetes. Diabetes Care, 30, 1292-1294.
[4] Hernaez, R., Choque, L., Gimenez, M., Marquez, J. and Conget, I. (2004) Coronary risk assessment in subjects with Type 2 diabetes mellitus. General population-based scores or specific scores? Revista Espanola de Cardiología, 57, 577-580.
[5] Song, S. and Brown, P. (2004) Coronary heart disease risk assessment in diabetes mellitus: Comparison of UKPDS risk engine with Framingham risk assessment and its clinical implications. Diabetic Medicine, 21, 238-245.
[6] Protopsaltis, I. and Nikolopoulos, G. and Melidonis, A. (2004) Comparative study of the prognostic value for coronary heart disease risk between the UK prospective diabetes study and Framingham models. Diabetes Care, 27, 277-278.
[7] New Zealand Guidelines Group. (2003) The assessment and management of cardiovascular risk. Wellington, New Zealand.
[8] Stephens, J., Ambler, G., Vallance, P., Betteridge, D., Humphries, S. and Hurel, S. (2004) Cardiovascular risk and diabetes. Are the methods of risk prediction satisfactory? The European Journal of Cardiovascular Prevention & Rehabilitation, 11, 521-528.
[9] Yeo, W. and Yeo, K. (2001) Predicting CHD risk in patients with diabetes mellitus. Diabetic Medicine, 18, 341-344.
[10] Guzder, R., Gatling, W., Mullee, M., Mehta, R. and Byrne, C. (2005) Prognostic value of the Framingham cardiovascular risk equation and the UKPDS risk engine for coronary heart disease in newly diagnosed Type 2 diabetes: Results from a United Kingdom study. Diabetic Medicine, 22, 554-562.
[11] Game, F., Bartlett, W., Bayley, G. and Jones, A. (2001) Comparative accuracy of cardiovascular risk prediction methods in patients with diabetes mellitus. Diabetes, Obesity and Metabolism, 3, 279-286.
[12] Metcalf, P., Wells, S., Scragg, R. and Jackson, R. (2008) Comparison of three different methods of assessing cardiovascular disease risk in New Zealanders with Type 2 diabetes mellitus. NZ Medical Journal, 121, 49-57.
[13] National Collaborating Centre for Primary Care (NCCPC) (2008) Lipid modification: Cardiovascular risk assessment and the modification of blood lipids for the primary and secondary prevention of cardiovascular disease. Clinical guideline 67. London, NICE.
[14] Clinical Knowledge Summaries (CKS). (2008) Cardiovascular risk assessment and management. Version 1.5. Newcastle upon Tyne, CKS.
[15] Scottish Intercollegiate Guidelines Network (SIGN). (2007) Risk estimation and the prevention of cardiovascular disease. SIGN Publication No. 97. Edinburgh, SIGN.
[16] Joint British Societies (JBS). (2005) JBS 2: Joint British Societies’ guidelines on prevention of cardiovascular disease in clinical practice. Heart, 91, V1-V5. 079988
[17] Expert panel on detection e, and treatment of high blood cholesterol. (2001) Executive summary of the third report of the National Cholesterol Education Program (NCEP) expert panel on detection, evaluation, and treatment of high blood cholesterol in adults. The Journal of the American Medical Association, 285, 2486-2497.
[18] Jackson, R. (2000) Updated New Zealand cardiovascular disease risk-benefit prediction guide. British Medical Journal, 320, 709-710.
[19] Anderson, K., Odell, P., Wilson, P. and Kannel, W. (1990) Cardiovascular disease risk profiles. American Heart Journal, 121, 293-298.
[20] Alberti, K. and Zimmet, P. (1998) Definition, diagnosis and classification of diabetes mellitus and its complications. Part 1: Diagnosis and classification of diabetes mellitus. Provisional report of a WHO consultation. Diabetic Medicine, 15, 539-553. 15:7<539::AID-DIA668>3.0.CO;2-S
[21] Allain, C., Poon, L., Chan, C., Richmond, W. and Fu, P. (1974) Enzymatic determination of total serum cholesterol. Clinical Chemistry, 20, 470-475.
[22] SAS Institute Inc. (2011) SAS/STAT User’s Guide. Version 9.3. SAS Institute Inc, Cary.
[23] Metcalf, P. and Scott, A. (2009) Using multiple frames in health surveys. Statistics in Medicine, 28, 1512-1523.
[24] Abbot, R., Donahue, R., Kannel, W. and Wilson, P. (1988) The impact of diabetes on survival following myocardial infarction in men vs women. The Framingham Study. The Journal of the American Medical Association, 260, 3456-3460.
[25] Wilson, S., Johnston, A., Robson, J., Poulter, N., Collier, D., Feder, G. and Caulfield, M.J. (2003) Predicting coronary risk in the general population—Is it necessary to measure high-density lipoprotein cholesterol? Journal of Cardiovascular Risk, 10, 137-141. 00043798-200304000-00009
[26] Asia Pacific Cohort Studies Collaboration. (2006) Coronary risk prediction for those with and without diabetes. The European Journal of Cardiovascular Prevention & Rehabilitation, 13, 30-36.

Copyright © 2021 by authors and Scientific Research Publishing Inc.

Creative Commons License

This work and the related PDF file are licensed under a Creative Commons Attribution 4.0 International License.