Early and accurate identification of individuals at risk for a first coronary event remains a critical priority in primary prevention. A population-based cohort study published in JAMA evaluated whether adding CCTA-derived measures of coronary atherosclerosis improves risk prediction compared with PCE and CACS alone.

The analysis included 24,791 adults aged 50–64 years without previous cardiovascular disease, recruited from 6 Swedish university hospitals. The median follow-up duration was 7.8 years. CCTA assessments included segment involvement score, noncalcified atherosclerosis, and coronary obstructive disease defined as stenosis ≥50%. The primary outcome was nonfatal myocardial infarction or death from coronary heart disease.

A total of 304 coronary events occurred during follow-up. Individuals with segment involvement scores of 3–4 and >4 had higher event risk (hazard ratios 2.71 and 5.27, respectively). Noncalcified atherosclerosis was also associated with increased risk (hazard ratio 1.66).
Adding CCTA to risk models significantly improved performance, increasing the C statistic from 0.764 to 0.779 (P = .004) and achieving a net reclassification improvement of 0.133. Most reclassification benefits occurred among individuals categorized as low risk (<5%) by PCE.

These findings indicate that incorporating CCTA-based coronary atherosclerosis information modestly enhances first-event risk prediction and may better identify patients who could benefit from targeted preventive therapies.