Key result
The 2024 ESC-PTP model showed improved discrimination for obstructive CAD compared to the 2019 model (C-statistic 0.76 vs 0.74, p=0.031), but underestimated disease likelihood by 19.4%.
Why the study?
Does the 2024 ESC-PTP model improve discrimination and reclassification for obstructive CAD compared to the 2019 ESC-PTP model in symptomatic patients undergoing CCTA?
Observational (n=1,595)
Does the 2024 ESC-PTP model improve discrimination and reclassification for obstructive CAD compared to the 2019 ESC-PTP model in symptomatic patients undergoing CCTA?
Absolute Event Rate: 0.76% vs 0.74%
p-value: p=0.031
The 2024 ESC-PTP model offers slightly better discrimination for obstructive CAD than the 2019 model and safely reclassifies nearly half of symptomatic patients to lower risk categories, potentially reducing unnecessary downstream testing.
Introduction The 2024 ESC guidelines on chronic coronary syndromes incorporate risk factors alongside traditional parameters such as age, sex and symptom typicality to estimate the pre-test probability (PTP) of obstructive coronary artery disease (CAD). The Guidelines also suggest using coronary artery calcium score (CACS, Class IIa recommendation) to reclassify patients with a low PTP (>5% to ≤15%). Aim To assess the potential impact of using the new 2024 ESC-PTP model in symptomatic patients undergoing coronary computed tomography angiography (CCTA) for suspected CAD. Methods We conducted a retrospective analysis of prospectively collected data from consecutive patients undergoing CCTA for suspected CAD. CACS was performed immediately prior to CCTA. Key exclusion criteria included asymptomatic patients, symptoms other than chest pain or dyspnea, known CAD, preoperative assessment, known LVEF <50%, suspected acute coronary syndrome or age < 30 years. Obstructive CAD was defined as any luminal stenosis ≥50% on CCTA. Whenever downstream testing was performed, patients were reclassified accordingly. Discrimination and calibration were assessed. Reclassification was analyzed across PTP categories [Very Low (≤5%); Low (>5 to ≤15%); Moderate (>15 to ≤50%); High (>50%)]. Results A total of 1595 patients were included (42% male (n=671); median age 64 [IQR 56–72] years). Obstructive CAD prevalence was 14.2% (n=226). Compared to the 2019 ESC-PTP, the 2024 ESC-PTP showed improved discrimination, with C-statistics of 0.76 (95% CI: 0.74–0.78, p<0.001) vs. 0.74 (95% CI: 0.72–0.76, p<0.001), p=0.031 for comparison - Fig1A. In terms of calibration, the 2019 ESC-PTP overestimated the likelihood of CAD by 18.0% (p<0.001), while the 2024 ESC-PTP underestimated it by 19.4% (p<0.001) - Fig1B. The 2024 ESC-PTP model reclassified 47.3% of patients (n=755) previously categorized by the 2019 ESC-PTP model, with 97.2% (n=734) of these being reassigned to a lower risk category - Fig2. The proportion classified as Very Low PTP increased from 11.3% to 35.6%. Among patients classified as Low PTP by 2024 ESC-PTP (n=617), adding CACS to the diagnostic pathway would reclassify 41.3% (n=255) to Very Low PTP, with only 1.6% of these (n=4) showing obstructive CAD. Conclusions In patients undergoing CCTA for suspected CAD, the 2024 ESC-PTP offers slightly better discrimination than the 2019 ESC-PTP but seems to underestimate the likelihood of disease. This new method reclassifies almost half of these patients to lower categories, potentially impacting testing decisions. Using CACS in patients with Low PTP could obviate further testing in roughly 40% of these patients, but at the cost of 1-2% missed diagnoses.
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Sousa et al. (2025) conducted an observational in Suspected coronary artery disease (n=1,595). 2024 ESC-PTP model vs. 2019 ESC-PTP model was evaluated on Discrimination for obstructive CAD (luminal stenosis ≥50% on CCTA) (p=0.031). The 2024 ESC-PTP model showed improved discrimination for obstructive CAD compared to the 2019 model (C-statistic 0.76 vs 0.74, p=0.031), but underestimated disease likelihood by 19.4%.
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