NASA, cardiologists collaborate on CVD risk calculator
Researchers have developed an online tool to more accurately calculate which middle-aged individuals are at the highest risk of heart attack or stroke during the next 10 years.
The predictive model is the first to incorporate both coronary artery calcium (CAC) score and traditional risk factors for this population (aged 40 to 65). The study, published in Circulation, was triggered by NASA, which wanted to look at cardiovascular risk prediction among astronauts, who are mostly middle-aged men and women.
With participation from NASA and led by cardiologists with the University of Texas Southwestern Medical Center, the researchers derived the model using three cohorts: the Prospective Army Coronary Calcium Project and the first phases of the Dallas Heart Study and the Multi-Ethnic Study of Atherosclerosis. Combined, the population encompassed 7,382 individuals with a mean age of 51 years. More than half of the derivation population was non-white and 55 percent were men.
The model showed “good discrimination” for predicting the primary composite endpoint of myocardial infarction, stroke or death from coronary heart disease, the authors reported. A calculation using only traditional risk factors, body measurements and family history achieved a c-statistic—a measure of predictive accuracy—of 0.784, while the new tool boasted a c-statistic of 0.817.
The new model was then validated in a similar aged cohort from the Framingham Heart Study, demonstrating a c-statistic of 0.78—again showing “good” discrimination and calibration.
“The Astro-CHARM tool significantly improves ASCVD (atherosclerotic cardiovascular disease) risk prediction compared with traditional risk factors,” wrote lead author Amit Khera, MD, MSc, and colleagues. “It could be useful in risk-based decision making for CV disease prevention in the middle-aged general population.”
Khera et al. noted the 10-year risk assessment of ASCVD already drives recommendations for statin and aspirin use. With that in mind, there is always a need for more accurate prediction models, as well as increased communication of risk to patients so they can more actively engage in their care.
“Determining an individual’s absolute risk allows calculation of the absolute risk reduction and number needed to treat for any preventive strategy, thus providing quantitative measures of potential benefits,” Khera and coauthors wrote.
The researchers said their risk model is best applied to individuals not already taking statins, because more than 90 percent of patients in their middle-aged dataset weren’t on those particular drugs.