TUESDAY, April 27 (HealthDay News) -- Adding coronary artery calcium scores (CACS) to traditional risk factors for coronary heart disease (CHD) events significantly improves predictions of risk, and results in more individuals being placed in the highest and lowest risk categories, according to research published in the April 28 issue of the Journal of the American Medical Association.
Tamar S. Polonsky, M.D., of Northwestern University in Chicago, and colleagues measured CACS in 6,814 individuals without known cardiovascular disease, 5,878 of whom completed a median 5.8 years of follow-up. Prediction model one used age, sex, tobacco use, and other traditional risk factors; model two used those risk factors and CACS.
The researchers found that model two resulted in significant improvements in risk prediction over model one. With model two, 77 percent of the cohort was classified as being in the highest or lowest risk category, compared with 69 percent in model one. Also, when model two was used, an additional 23 percent of participants who experienced events were reclassified as high risk; similarly, an additional 13 percent of participants who did not experience any events were reclassified as low risk. There were significant improvements in risk prediction when model two was used instead of model one (net reclassification improvement, 0.25).
"In this multi-ethnic 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," the authors write.
A co-author disclosed financial ties to Pfizer, and another disclosed ties to Pfizer and GE/Toshiba.
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