Prospective evaluation of a self-report-guided strategy for targeted coronary artery calcium imaging

Background Coronary artery calcium (CAC) imaging directly assesses subclinical calcified coronary atherosclerosis, but population-wide imaging is not recommended. Simple pre-screening may help identify individuals most likely to benefit from CAC imaging. We previously developed a self-report-based model to estimate the probability of CAC ≥100. This study prospectively evaluated a strategy based on this model to select individuals for CAC imaging. We assessed agreement between model-predicted probability and observed prevalence of CAC ≥100 among participants undergoing computed tomography (CT) imaging and examined patterns of preventive lipid-lowering therapy. Methods The PRedict and Identify cOronary atherosclerosis–Now (PRIO-Now) study applied a prospective, two-step, population-based screening approach. Individuals aged 59– 60 years were invited to complete a self-report questionnaire. Eligible respondents without previous ischemic heart disease whose model-predicted probability of CAC ≥100 exceeded the predefined threshold were invited to clinical assessment and non-contrast coronary CT imaging. The primary analysis assessed agreement between model-predicted probabilities and the observed prevalence of CAC ≥100 among CT completers. Results Of 8,000 invited individuals, 2,588 (32%) completed the questionnaire. Of 2,375 eligible respondents, 814 were classified as high risk and 563 underwent CT imaging. Among CT completers, the mean predicted probability of CAC ≥100 was 28.3% (95% CI 27.2–29.3), compared with an observed prevalence of 28.4% (95% CI 24.8–32.4), corresponding to an expected/observed ratio of 0.99 and a Brier score of 0.19. Among participants with CAC ≥100, 64% were not receiving lipid-lowering therapy and 11% had LDL-C ≤1.8 mmol/L. Conclusions A self-report-guided strategy enabled targeted CAC imaging in a model-selected cohort. Among participants completing CT imaging, the observed prevalence of CAC ≥100 was comparable with the mean model-predicted probability. These findings suggest that self-report data may support pre-selection for CAC imaging and help identify opportunities for preventive treatment among individuals with elevated CAC. What is already known on this topic Coronary artery calcium (CAC) is a direct measure of subclinical coronary atherosclerosis and refines cardiovascular risk assessment beyond traditional risk factors. However, population-wide CAC screening is not recommended, and current risk-based selection approaches may miss individuals with prognostically relevant disease. What this study adds This prospective evaluation assessed a previously developed self-report-based model for identifying individuals with moderate to severe coronary atherosclerosis (CAC ≥100). In the model-selected high-risk group, the predicted probability of CAC ≥100 was similar to the observed prevalence among participants completing CT imaging. The study also showed that many individuals with CAC ≥100 were not receiving lipid-lowering therapy. How this study might affect research, practice or policy Self-report-based pre-screening may support more selective use of CAC imaging in future prevention strategies. By identifying individuals with substantial subclinical coronary atherosclerosis, this approach may help detect treatment opportunities and guide more targeted preventive intervention.