Progression of Coronary Artery Calcification Seems To Be Inevitable, but Predictable - Results of the Heinz Nixdorf Recall (HNR) Study

Study Questions:

Can coronary artery calcification (CAC) be detected?


Data from the Heinz Nixdorf Recall (HNR) study were used for the present analysis. Caucasians (ages 45–75 years) from the three cities in the Ruhr area, Germany, were enrolled between December 2000 and August 2003. Subjects with prior coronary artery disease were excluded. CAC percentiles at baseline (CACb) and after 5 years (CAC5y) were examined. The male cohort was subdivided in five categories according to the percentiles of the CAC distribution: 0–25th, 25–50th, 50–75th, 75–90th, and >90th percentiles. The female cohort was subdivided in four categories, because in women, CAC values were 0 up to the 40th percentile. Using quintile regression on the log-scale (log[CACb+1]), a tool was developed to individually predict CAC5y, and compared to observed CAC5y.


A total of 3,481 participants (45–74 years, 53.1% women) were included. In men, all baseline risk factors showed a significant association with CAC except for high-density lipoprotein cholesterol (HDL-C), serum creatinine, and glomerular filtration rate. For women, the association to risk factors was similar, but not significant for smoking and serum creatinine. After 5 years, the demographics in men showed a higher body mass index with a higher prevalence of obesity and diabetes and higher glycated hemoglobin level. Systolic blood pressure was higher and diastolic blood pressure was lower despite a higher use of antihypertensive agents. A lower prevalence of smoking as well as lower low-density lipoprotein cholesterol levels with a higher rate of lipid-lowering medication was also observed. The 5-year follow-up data in women showed very similar trends. The difference between observed and predicted CAC5y (log-scale, mean ± standard deviation) was 0.08 ± 1.11 and 0.06 ± 1.29 in men and women. Agreement reached a kappa value of 0.746 (95% confidence interval, 0.732–0.760) and concordance correlation (log-scale) of 0.886 (0.879–0.893). Explained variance of observed by predicted log(CAC5y+1) was 80.1% and 72.0% in men and women, and 81.0% and 73.6% including baseline risk factors. Evaluating the tool in 1,940 individuals with CAC5y >0 and CAC5y <400 at baseline, of whom 242 (12.5%) developed CAC5y >400, yielded a sensitivity of 59.5%, specificity 96.1%, (+) and (–) predictive values of 68.3% and 94.3%. A predefined acceptance range around predicted CAC5y contained 68.1% of observed CAC5y; only 20% were expected by chance. Age, blood pressure, lipid-lowering medication, diabetes, and smoking contributed to progression above the acceptance range in men and, excepting age, in women.


The authors concluded that CAC nearly inevitably progresses with limited influence of cardiovascular risk factors. This allowed the development of a mathematical tool for prediction of individual CAC progression, enabling anticipation of the age when CAC thresholds of high risk are reached.


It may be useful to incorporate tools such as the one described above, to identify the timing of prevention measures such as statin therapy using CAC information gathered years prior, in addition to identification of those at higher risk for CAD events. Further data are warranted in other nonwhite populations.

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