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 prescreening 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 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 ischaemic 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 8000 invited individuals, 2588 (32%) completed the questionnaire. Of 2375 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 to 29.3), compared with an observed prevalence of 28.4% (95% CI 24.8 to 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 low-density lipoprotein cholesterol ≤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 preselection for CAC imaging and help identify opportunities for preventive treatment among individuals with elevated CAC.