Coronary artery calcium (CAC) and traditional risk factors can accurately estimate 10-year coronary heart disease (CHD) and help clinicians recommend prevention strategies, according to research published in the Journal of the American College of Cardiology.

Clinicians frequently use CAC scores from cardiac-gated noncontrast computed tomography scans to predict cardiovascular risk in patients. Dr. Robyn McClelland, PhD, of the University of Washington, and colleagues conducted the Muti-Ethnic Study of Atherosclerosis (MESA) to study the prevalence and risk factors of subclinical cardiovascular disease (CVD) in a multi-ethnic population. Researchers then examined the MESA risk scores with CAC to measure the accuracy of CAC when predicting cardiovascular events.

“We present a predictive algorithm to integrate CAC measurement with traditional risk factors and demonstrate that a risk score that includes CAC improves CHD risk prediction compared with single measurements of traditional risk factors alone,” the authors wrote.


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The MESA study included 6814 patients from 6 communities in the United States, ages 45 to 84 years, without heart disease at the beginning of the study. Researchers followed the participants for a median of 10.2 years. The cohort was sex-balanced and included participants who identified as non-Hispanic white (39%), Chinese (12%), African American (28%), and Hispanic American (22%).

A telephone interviewer called the participants every 9 to 12 months to survey interim hospitalizations, cardiovascular diagnoses, and deaths. The researchers then used a list of covariates, including cholesterol levels, antihypertensive medication use, smoking status, diabetes, and CAC to develop the algorithm for cardiovascular risk scores.

There were 422 observed cardiovascular events throughout the 10-year study, including 68 CHD deaths, 190 nonfatal myocardial infarctions, 149 angina-driven revascularizations, and 15 resuscitated cardiac arrests. 

The data showed that when researchers included CAC in the MESA risk score, the risk prediction increased (C-statistic 0.80 vs 0.75). Participants who had experienced a cardiovascular event during the study had a 10-year risk score with CAC that was 8.6% higher than the participants who did not experience a cardiovascular event. Without CAC, the risk scores of participants who experienced cardiovascular events were only 5.2% higher than those who did not.

Researchers also tested the risk scores of the Heinz Nixdorf Recall and the Dallas Heart studies to validate the findings. Both studies showed “very good to excellent” mean calibration, or calibration-in-the-large (-0.50% for HNR and -0.46% for DHS) and discrimination. However, the model without CAC was not as well calibrated and had substantially worse discrimination (HNR calibration slope 0.74; C-statistic without CAC 0.720, discrimination slope 0.053). The C-statistic without CAC in DHS was “very good” (0.782), but the discrimination slope was only 0.046. The difference in predicted probability between events and nonevents ranged from 7.8% to 9.5%.

CHD scores are typically influenced by age, sex, and ethnicity. Including CAC in the risk scores decreases the effects of the demographic risk factors, because CAC integrates the effects of all measured and unmeasured risk factors across the individual’s lifetime. Measuring all of the risk factors together with one algorithm can help individualize the risk scores and can influence prevention recommendations.

“The risk scores can be used by the physician to motivate patient lifestyle change, encourage adherence to existing therapy, or to guide decisions about treatment intensity,” the authors concluded.

Reference

  1. McClelland RL, Jorgensen NW, Budoff M, et al. 10-Year Coronary Heart Disease Risk Prediction Using Coronary Artery Calcium and Traditional Risk Factors. J Am Coll Cardiol. 2015; doi: 10.1016/j/jack.2015.08.035.