The coronary calcium score is a strong predictor of incident coronary heart disease and provides predictive information beyond that provided by standard risk factors in four major racial and ethnic groups in the United States. No major differences among racial and ethnic groups in the predictive value of calcium scores were detected.

The electron beam CT coronary calcium score predicts CAD events independent of standard risk factors, more accurately than standard risk factors and CRP, and refines Framingham risk stratification.

Context Coronary artery calcium score (CACS) has been shown to predict future coronary heart disease (CHD) events. However, the extent to which adding CACS to traditional CHD risk factors improves classification of risk is unclear. Objective To determine whether adding CACS to a prediction model based on traditional risk factors improves classification of risk. Design, Setting and Participants CACS was measured by computed tomography on 6,814 participants from the Multi-Ethnic Study of Atherosclerosis (MESA), a population-based cohort without known cardiovascular disease. Recruitment spanned July 2000 to September 2002; follow-up extended through May 2008. Participants with diabetes were excluded for the primary analysis. Five-year risk estimates for incident CHD were categorized as 0-<3%, 3-<10%, and ≥10% using Cox proportional hazards models. Model 1 used age, gender, tobacco use, systolic blood pressure, antihypertensive medication use, total and high-density lipoprotein cholesterol, and race/ethnicity. Model 2 used these risk factors plus CACS. We calculated the net reclassification improvement (NRI) and compared the distribution of risk using Model 2 versus Model 1. Main Outcome Measures Incident CHD events Results Over 5.8 years median follow-up, 209 CHD events occurred, of which 122 were myocardial infarction, death from CHD, or resuscitated cardiac arrest. Model 2 resulted in significant improvements in risk prediction compared to Model 1 (NRI=0.25, 95% confidence interval 0.16-0.34, P<0.001). With Model 1, 69% of the cohort was classified in the highest or lowest risk categories, compared to 77% with Model 2. An additional 23% of those who experienced events were reclassified to high risk, and an additional 13% without events were reclassified to low risk using Model 2. Conclusions In the MESA cohort, addition of CACS to a prediction model based on traditional risk factors significantly improved the classification of risk and placed more individuals in the most extreme risk categories.

In asymptomatic adults, EBCT of the coronary arteries predicts coronary death and nonfatal MI and the need for revascularization procedures.

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