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Estimating CHD Risk

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Identifying subjects at high risk of cardiovascular disease (CVD) is a key priority of primary prevention and the first step towards reducing CVD risk by targeting modifiable risk factors (1). Traditionally, risk factor guidelines have focused on single factor assessment rather than on individual’s global risk based on a combination of risk factors (2). However, large prospective studies (3, 4) have clearly shown that coronary heart disease (CHD) is a multifactorial disease and that coronary risk factors do not act in isolation but rather in conjunction with each other. It is therefore important to consider all risk factors when assessing a patient’s global CHD risk. This way of identifying high-risk individuals recognizes not only CHD’s multifaceted nature and the multiplicative effect of risk factors but also the importance of assessing and managing patients beyond mere treatment of risk factors (2).

Over the last decades, numerous epidemiological studies (3, 4) have focused their attention on global absolute risk for identifying high-risk individuals. Several risk prediction methods have been developed to identify individuals at high risk of CHD or CVD. Among those risk prediction methods, the Framingham Heart Study (3) and the PROCAM study (4) are two well-known examples of predictive equations derived from large prospective studies. Additional risk charts and scores have also been developed from other widely known studies such as the Systematic COronary Risk Evaluation (SCORE) project (5), the United Kingdom Prospective Diabetes Study (UKPDS) (6), and the Italian CUORE project (7). All these risk charts and scores are useful tools for evaluating an individual’s global CHD risk in clinical practice.

Reference

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1. Giampaoli S, Palmieri L, Mattiello A, et al. Definition of high risk individuals to optimise strategies for primary prevention of cardiovascular diseases. Nutr Metab Cardiovasc Dis 2005; 15: 79-85.

2. Prevention of coronary heart disease in clinical practice. Recommendations of the Second Joint Task Force of European and other Societies on coronary prevention. Eur Heart J 1998; 19: 1434-503.

3. Wilson PW, D'Agostino RB, Levy D, et al. Prediction of coronary heart disease using risk factor categories. Circulation 1998; 97: 1837-47.

4. Assmann G, Cullen P and Schulte H. Simple scoring scheme for calculating the risk of acute coronary events based on the 10-year follow-up of the prospective cardiovascular Munster (PROCAM) study. Circulation 2002; 105: 310-5.

5. Conroy RM, Pyorala K, Fitzgerald AP, et al. Estimation of ten-year risk of fatal cardiovascular disease in Europe: the SCORE project. Eur Heart J 2003; 24: 987-1003.

6. Stevens RJ, Kothari V, Adler AI, et al. The UKPDS risk engine: a model for the risk of coronary heart disease in Type II diabetes (UKPDS 56). Clin Sci (Lond) 2001; 101: 671-9.

7. 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. Int J Epidemiol 2005; 34: 413-21.

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