Coronary Risk Stratification, Discrimination, and Reclassification Improvement Based on Quantification of Subclinical Coronary Atherosclerosis

Objectives

The purpose of this study was to determine net reclassification improvement (NRI) and improved risk prediction based on coronary artery calcification (CAC) scoring in comparison with traditional risk factors.

Background

CAC as a sign of subclinical coronary atherosclerosis can noninvasively be detected by CT and has been suggested to predict coronary events.

Methods

In 4,129 subjects from the HNR (Heinz Nixdorf Recall) study (age 45 to 75 years, 53% female) without overt coronary artery disease at baseline, traditional risk factors and CAC scores were measured. Their risk was categorized into low, intermediate, and high according to the Framingham Risk Score (FRS) and National Cholesterol Education Panel Adult Treatment Panel (ATP) III guidelines, and the reclassification rate based on CAC results was calculated.

Results

After 5 years of follow-up, 93 coronary deaths and nonfatal myocardial infarctions occurred (cumulative risk 2.3%; 95% confidence interval: 1.8% to 2.8%). Reclassifying intermediate (defined as 10% to 20% and 6% to 20%) risk subjects with CAC <100 to the low-risk category and with CAC ≥400 to the high-risk category yielded an NRI of 21.7% (p = 0.0002) and 30.6% (p < 0.0001) for the FRS, respectively. Integrated discrimination improvement using FRS variables and CAC was 1.52% (p < 0.0001). Adding CAC scores to the FRS and National Cholesterol Education Panel ATP III categories improved the area under the curve from 0.681 to 0.749 (p < 0.003) and from 0.653 to 0.755 (p = 0.0001), respectively.

Conclusions

CAC scoring results in a high reclassification rate in the intermediate-risk cohort, demonstrating the benefit of imaging of subclinical coronary atherosclerosis. Our study supports its application, especially in carefully selected individuals with intermediate risk.