Evaluating the American Heart Association/American College of Cardiology Guideline-Recommended and Contemporary Pretest Probability Models in a Mixed Asian Cohort: The Contribution of Coronary Artery Calcium.

Background: Most pretest probability (PTP) tools for obstructive coronary artery disease (CAD) were Western -developed. The most appropriate PTP models and the contribution of coronary artery calcium score (CACS) in Asian populations remain unknown. In a mixed Asian cohort, we compare 5 PTP models: local assessment of the heart (LAH), CAD Consortium (CAD2), risk factor-weighted clinical likelihood, the American Heart Association/American College of Cardiology and the European Society of Cardiology PTP and 3 extended versions of these models that incorporated CACS: LAH, CAD2, and the CACS-clinical likelihood.

Methods And Results: The study cohort included 771 patients referred for stable chest pain. Obstructive CAD prevalence was 27.5%. Calibration, area under the receiver-operating characteristic curves (AUC) and net reclassification index were evaluated. LAH clinical had the best calibration (χ 5.8; =0.12). For CACS models, LAH showed least deviation between observed and expected cases (χ 37.5; <0.001). There was no difference in AUCs between the LAH clinical (AUC, 0.73 [95% CI, 0.69-0.77]), CAD2 clinical (AUC, 0.72 [95% CI, 0.68-0.76]), risk factor-weighted clinical likelihood (AUC, 0.73 [95% CI: 0.69-0.76) and European Society of Cardiology PTP (AUC, 0.71 [95% CI, 0.67-0.75]). CACS improved discrimination and reclassification of the LAH (AUC, 0.88; net reclassification index, 0.46), CAD2 (AUC, 0.87; net reclassification index, 0.29) and CACS-CL (AUC, 0.87; net reclassification index, 0.25).

Conclusions: In a mixed Asian cohort, Asian-derived LAH models had similar discriminatory performance but better calibration and risk categorization for clinically relevant PTP cutoffs. Incorporating CACS improved discrimination and reclassification. These results support the use of population-matched, CACS-inclusive PTP tools for the prediction of obstructive CAD.