The use of a coronary artery calcium (CAC) score in addition to traditional risk factors was determined to be associated with improved prediction of heart disease risk, and placed more individuals in the most extreme risk categories, said a study published April 28 in the Journal of the American Medical Association.
Led by Tamar Polonsky, MD, a post-doctoral fellow in cardiovascular epidemiology and prevention at the Feinberg School of Medicine at Northwestern University in Chicago, the researchers sought to determine whether adding CAC score to a prediction model based on traditional risk factors alone can improve classification of risk of future cardiovascular events.
“The extent to which adding CAC score to traditional coronary heart disease (CHD) risk factors improves classification of risk is unclear,” explained the authors.
Beginning in July 2000, with a follow-up period through May 2008, Polonsky and colleagues recruited 6,814 participants from a population-based cohort, the Multi-Ethnic Study of Atherosclerosis (MESA). The participants, who were between the ages of 45 to 84, identified themselves as white, black, Hispanic or Chinese and had no known cardiovascular disease.
In all of the participants, CAC score was measured by way of CT. Using two predication models, the researchers first predicted five-year risk estimates for the participants who would be most likely to experience a cardiac event based solely on their traditional risk factors alone, including age, gender, tobacco use, blood pressure, antihypertensive medication use, cholesterol levels and race or ethnicity. Secondly, they predicted who would have an event by evaluating traditional factors plus CAC score.
According to the authors, five-year risk estimates for new CHD were categorized as 0 percent to less than 3 percent, 3 percent to less than 10 percent and 10 percent or more. The models were compared and evaluated to learn which method improved their predictions of the participants at risk.
After a follow-up period of 5.8 years in a final group of 5,878 participants, the authors found that 209 individuals experienced some form of CHD events, including 122 major events (heart attack, death from CHD or resuscitated cardiac arrest).
In the first prediction model, 69 percent of the cohort was classified in the highest or lowest risk categories compared with 77 percent in the second model with CAC score. The authors wrote that when CAC score was added to their predictions, a further 23 percent of those who experienced events were reclassified as high risk and an additional 13 percent of those who did not experience events were reclassified as low risk. Sixteen percent were reclassified as high risk while 39 percent were classified as low risk among the cohort of intermediate risk individuals.
The authors wrote: “The results of this study demonstrate that when CAC score is added to traditional risk factors, it results in a significant improvement in the classification of risk for the prediction of CHD events in an asymptomatic population-based sample of men and women drawn from four U.S. racial/ethnic groups.”
An accompanying editorial on the study, however, warned that determining whether CAC score should be used routinely still requires testing in a randomized intervention trial.
“The authors have not yet demonstrated that the added accuracy in risk stratification can actually aid clinicians in better treating patients or improving their clinical outcomes. Therefore, their findings, no matter how promising, do not suffice to recommend this marker for widespread routine use,” stated John P. A. Ioannidis, MD, of the University of Ioannina School of Medicine in Ioannina, Greece, and Ioanna Tzoulaki, PhD, of the Imperial College of Medicine in London.
The study researchers agreed that more research is warranted before the test is routinely recommended. “The results provide encouragement for moving to the next stage of evaluation to assess the use of CAC score on clinical outcomes,” they concluded.