Abstract 4366598: Comparative Performance of PCE, PREVENT, and CAC for MACE Prediction in Asymptomatic Patients

Introduction/Background: Current prediction models including the Pooled Cohort Equations (PCE) and the novel PREVENT score are used for assessing atherosclerotic cardiovascular disease (ASCVD) risk. Coronary artery calcium (CAC) scoring can further refine risk stratification, but its integration with PREVENT remains unknown. Research Questions/Hypothesis: How does the performance of PCE, PREVENT, and CAC—individually and combined— compare for predicting Major Adverse Cardiac Events (MACE) in asymptomatic adults? Methods/Approach: Among 14,570 asymptomatic patients from the Emory CAC Registry (2010–2023), PCE and PREVENT 10-year risk scores were calculated, and CAC was quantified via Agatston scoring using a validated AI method. MACE (myocardial infarction, stroke, revascularization>90 days) was ascertained via ICD/CPT codes. Kaplan-Meier survival curves and Cox proportional hazard ratios were used to evaluate MACE across stratified risk groups. Discrimination was assessed using Harrell’s C-statistic across PCE risk strata (0–2.5%, 2.5-5%, 5-7.5%, 7.5-10%, 10-20% and >20%). Results/Data: The mean age was 56.5 years, 42% were women, 78% were white. Median CACS was 1.3 (IQR 0,49) (44% had CAC = 0). Mean PCE was 7% and mean ASCVD PREVENT was 4%. PREVENT alone outperformed PCE alone (C-statistic 0.64 vs. 0.59, p<0.01), with higher hazard ratios for increasing risk groups (5-7.5% risk: PCE HR 1.7 vs PREVENT HR 2.1 and 10-20% risk: PCE HR 2.8 vs PREVENT HR 4 (vs 0-2.5% risk group)). CAC showed a graded association with MACE (CAC >300: HR=3.8, p<0.001 vs CAC=0). Across all risk strata groups, adding CAC to PCE and PREVENT improved discrimination, with the most substantial improvement in PCE risk groups 2.5-5% and 10-20% (Δ C-statistic =+0.1 for both). Sex-based differences in model performance existed (C-statistics of 0.57-0.74 in men versus 0.57-0.59 in women). Conclusion(s): CAC further enhances MACE risk discrimination with PCE and PREVENT, particularly in intermediate-risk groups and in males. Integrating CAC with PREVENT may assist in optimizing primary prevention strategies.

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Journal
Circulation
Published
2025-11-03
DOI
https://doi.org/10.1161/circ.152.suppl_3.4366598
Primary Topic
Cardiovascular Health and Risk Factors
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article
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article

Abstract 4366598: Comparative Performance of PCE, PREVENT, and CAC for MACE Prediction in Asymptomatic Patients

Laurence S. Sperling, Alexander C. Razavi, Yanxu Yang, Marly van Assen et al.
Circulation
Cardiovascular Health and Risk Factors
article

Abstract 4366598: Comparative Performance of PCE, PREVENT, and CAC for MACE Prediction in Asymptomatic Patients

Laurence S. Sperling, Alexander C. Razavi, Yanxu Yang, Marly van Assen, Martin Halicek, Omar Dzaye, Carlo N. De Cecco, Seamus P. Whelton, Roger S. Blumenthal, Gabrielle Gershon, Jaret Barr, Michael J. Blaha, Eshan Momin
article en

Abstract

Introduction/Background: Current prediction models including the Pooled Cohort Equations (PCE) and the novel PREVENT score are used for assessing atherosclerotic cardiovascular disease (ASCVD) risk. Coronary artery calcium (CAC) scoring can further refine risk stratification, but its integration with PREVENT remains unknown. Research Questions/Hypothesis: How does the performance of PCE, PREVENT, and CAC—individually and combined— compare for predicting Major Adverse Cardiac Events (MACE) in asymptomatic adults? Methods/Approach: Among 14,570 asymptomatic patients from the Emory CAC Registry (2010–2023), PCE and PREVENT 10-year risk scores were calculated, and CAC was quantified via Agatston scoring using a validated AI method. MACE (myocardial infarction, stroke, revascularization>90 days) was ascertained via ICD/CPT codes. Kaplan-Meier survival curves and Cox proportional hazard ratios were used to evaluate MACE across stratified risk groups. Discrimination was assessed using Harrell’s C-statistic across PCE risk strata (0–2.5%, 2.5-5%, 5-7.5%, 7.5-10%, 10-20% and >20%). Results/Data: The mean age was 56.5 years, 42% were women, 78% were white. Median CACS was 1.3 (IQR 0,49) (44% had CAC = 0). Mean PCE was 7% and mean ASCVD PREVENT was 4%. PREVENT alone outperformed PCE alone (C-statistic 0.64 vs. 0.59, p<0.01), with higher hazard ratios for increasing risk groups (5-7.5% risk: PCE HR 1.7 vs PREVENT HR 2.1 and 10-20% risk: PCE HR 2.8 vs PREVENT HR 4 (vs 0-2.5% risk group)). CAC showed a graded association with MACE (CAC >300: HR=3.8, p<0.001 vs CAC=0). Across all risk strata groups, adding CAC to PCE and PREVENT improved discrimination, with the most substantial improvement in PCE risk groups 2.5-5% and 10-20% (Δ C-statistic =+0.1 for both). Sex-based differences in model performance existed (C-statistics of 0.57-0.74 in men versus 0.57-0.59 in women). Conclusion(s): CAC further enhances MACE risk discrimination with PCE and PREVENT, particularly in intermediate-risk groups and in males. Integrating CAC with PREVENT may assist in optimizing primary prevention strategies.

CirculationVol. 152(Suppl_3)
Johns Hopkins University (US), Emory University (US), Johns Hopkins Hospital (US)
Openalex Percentile: Top 52%
Cardiovascular Health and Risk Factors
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