Key result
RF-CL and CACS-CL classify up to ~54% of patients as very low CAD likelihood vs PTP.
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Why the study?
The RF-CL and CACS-CL models show superior discrimination in suspected obstructive CAD, but validation against hemodynamic impairment was warranted.
Do the RF-CL and CACS-CL models improve the prediction of hemodynamically obstructive CAD compared to a basic PTP model in patients with stable chest pain?
Cohort (n=4,371)
Do the RF-CL and CACS-CL models improve the prediction of hemodynamically obstructive CAD compared to a basic PTP model in patients with stable chest pain?
Absolute Event Rate: 53.7% vs 12%
p-value: p=<0.001
The RF-CL and CACS-CL models provide superior discrimination and calibration for predicting hemodynamically obstructive CAD compared to the basic guideline-endorsed PTP model, allowing more patients to be safely classified as very low risk.
BACKGROUND: Selection for invasive angiography is recommended to be based on pretest probabilities (PTPs), and physiological measures of hemodynamical impairment by, for example, fractional flow reserve (FFR) should guide revascularization. The risk factor-weighted clinical likelihood (RF-CL) and coronary artery calcium score-weighted clinical likelihood (CACS-CL) models show superior discrimination of patients with suspected obstructive coronary artery disease (CAD), but validation against hemodynamic impairment is warranted. OBJECTIVES: The aim of this study was to validate the RF-CL and CACS-CL models against hemodynamically obstructive CAD. METHODS: Stable de novo chest pain patients (N = 4,371) underwent coronary computed tomography angiography and subsequently invasive coronary angiography with FFR measurements. Hemodynamically obstructive CAD was defined as invasive FFR ≤0.80 or high-grade stenosis by visual assessment (>90% diameter stenosis). For comparison, a guideline-endorsed basic PTP model was calculated based on age, sex, and symptom typicality. The RF-CL model additionally included the number of risk factors, and the CACS-CL model incorporated the coronary artery calcium score into the RF-CL. RESULTS: In total, 447 of 4,371 (10.9%) patients had hemodynamically obstructive CAD. Both the RF-CL and CACS-CL models classified more patients with a very low clinical likelihood (≤5%) of obstructive CAD compared to the basic PTP model (33.0% and 53.7% vs 12.0%; P < 0.001) with a preserved low prevalence of hemodynamically obstructive CAD (<5% for all models). Against hemodynamically obstructive CAD, calibration and discrimination of the RF-CL and CACS-CL models were superior to the basic PTP model. CONCLUSIONS: The RF-CL and CACS-CL models are well calibrated and superior to a currently recommended basic PTP model to predict hemodynamically obstructive CAD. (Danish Study of Non-Invasive Diagnostic Testing in Coronary Artery Disease [Dan-NICAD]; NCT02264717; Danish Study of Non-Invasive Diagnostic Testing in Coronary Artery Disease 2 [Dan-NICAD 2]; NCT03481712, Danish Study of Non-Invasive Diagnostic Testing in Coronary Artery Disease 3 [Dan-NICAD 3]; NCT04707859).
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Rasmussen et al. (2024) conducted a cohort in Stable chest pain with suspected obstructive coronary artery disease (n=4,371). Risk factor-weighted clinical likelihood (RF-CL) and coronary artery calcium score-weighted clinical likelihood (CACS-CL) models vs. Guideline-endorsed basic pretest probability (PTP) model was evaluated on Proportion of patients classified with a very low clinical likelihood (≤5%) of obstructive CAD (p=<0.001). The RF-CL and CACS-CL models classified significantly more patients with a very low clinical likelihood of obstructive CAD compared to the basic PTP model (33.0% and 53.7% vs 12.0%; P<0.001).
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