Coronary Artery Calcium Scoring (CACS) can be used to predict the likelihood of future cardiovascular events.  However, whether this provides extra information on top of traditional cardiovascular risk factors remains unclear.
In this study 6814 participants in the Multi-Ethnic Study of Atherosclerosis (MESA) underwent CACS and were then followed up for five year.  None of the participants were known to have cardiovascular disease, but patients with diabetes were excluded from the primary analysis.  The authors used two predictive models; the first contained the traditional cardiovascular risk factors of age, sex, tobacco use, systolic blood pressure, antihypertensive use, total and HDL cholesterol and race/ethnicity.  The second used all of these factors and in addition CACS.  The authors calculated the net reclassification improvement and compared the distribution of risk using both models.
Median follow-up was 5.8 years, during which 209 coronary heart disease (CHD) events occurred, of which were 122 myocardial infarctions, death from CHD, or resuscitated cardiac arrest.  The use of CACS resulted in significant improvements in risk prediction compared to the use of traditional risk factors alone (net reclassification benefit 0.25, 95% CI 0.16-0.34; p<0.001).  A larger number of patients were classified either in the very high risk or the very low risk category using CACS (77% vs 69%).  Of note, 23% of patients who experienced events were reclassified as high risk when CACS was used, and 13% of patients without an event were reclassified as low risk using CACS.

Conclusion:

The use of CACS in a cardiovascular risk prediction model significantly improved the classification of risk, and placed more individuals in the high and low risk categories.  However, whether this can be used to improve patient outcomes remains to be proven.

• Polonsky TS, McClelland RL, Jorgensen NW et al.  Coronary Artery Calcium Score and Risk Classification for Coronary Heart Disease Prediction.  JAMA 2010;303(16):1610-1616