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PREVENT vs PCE thresholds for coronary artery calcium referral: Detection-optimized strategies in ELSA-Brasil
Daniel A Added1,2, Fernando Y Cesena3, Marcio H Miname1
1Lipid Clinic, Heart Institute (InCor), University of São Paulo Medical School Hospital, São Paulo, SP, Brazil.
Insights
The Pooled Cohort Equations (PCE) and PREVENT risk scores showed similar accuracy for detecting coronary artery calcium (CAC) but missed many individuals, especially women. Optimized thresholds may improve detection but require further study.
Area of Science:
- Cardiovascular disease risk assessment
- Medical imaging and diagnostics
- Public health and epidemiology
Background:
- Current 10-year atherosclerotic cardiovascular disease (ASCVD) risk equations were not specifically designed for guiding coronary artery calcium (CAC) testing.
- Clinical guidelines suggest using CAC scoring for refining ASCVD risk in adults with borderline or intermediate risk estimates.
- Comparing the performance of different risk prediction tools is crucial for optimizing CAC screening strategies.
Purpose of the Study:
- To compare the performance of the Predicting Risk of Cardiovascular Disease EVENTs (PREVENT) equation against the Pooled Cohort Equations (PCE) in detecting CAC.
- To identify optimized CAC testing referral thresholds for both risk prediction tools.
- To evaluate the reclassification of ASCVD risk based on CAC findings using different risk score thresholds.
Main Methods:
- Cross-sectional analysis of 3477 participants free of ASCVD from the ELSA-Brasil study.
- Estimation of 10-year ASCVD risk using both PCE and PREVENT risk equations.
- Comparison of discrimination for CAC presence (CAC >0) and significant calcification (CAC ≥100 Agatston units) using Area Under the Receiver Operating Characteristic Curve (AUC-ROC).
- Evaluation of prespecified and Youden-derived thresholds for sensitivity, specificity, scanning proportion, and number needed to scan (NNS).
Main Results:
- Both PCE and PREVENT demonstrated comparable discrimination for CAC ≥100 (AUC 0.81 vs. 0.80, p > 0.05).
- Standard thresholds (PCE 7.5%; PREVENT 3.7% men, 4.9% women) resulted in a significant proportion of individuals with CAC ≥100 being classified below the referral cutpoints (36.5% vs. 38.8%), with higher rates in women.
- Youden-derived thresholds (PCE 5.6%; PREVENT 2.7%) improved sensitivity for CAC detection but decreased specificity and increased the proportion eligible for CAC scanning.
Conclusions:
- While PCE and PREVENT show similar discriminatory power for significant CAC, their standard thresholds inadequately identify individuals needing further evaluation, particularly women.
- Optimized, lower referral thresholds for both PCE and PREVENT may enhance the detection of subclinical atherosclerosis.
- Further research is warranted to validate these optimized thresholds and assess their clinical utility in guiding CAC testing decisions.
Background:
Risk equations estimate 10-year ASCVD risk but were not designed to guide coronary artery calcium (CAC) testing, although guidelines consider CAC for risk refinement in borderline or intermediate-risk adults.
Objectives:
To compare the Predicting Risk of Cardiovascular Disease EVENTs (PREVENT) with Pooled Cohort Equations (PCE) for detecting CAC, identifying optimized CAC referral thresholds.
Methods:
In a cross-sectional analysis of 3477 ASCVD-free ELSA-Brasil participants, 10-year ASCVD risk was estimated using both tools, and reclassification assessed. Discrimination for CAC >0 and CAC ≥100 Agatston units was compared using area under receiver operating characteristic curve (AUC-ROC). Prespecified thresholds (PCE 7.5%; PREVENT 3.7% in men, 4.9% in women) and Youden-derived cutpoints were evaluated for sensitivity, specificity, scanning proportion, and number needed to scan (NNS).
Results:
Discrimination for CAC ≥100 was similar (AUC 0.81 vs 0.80 for PCE and PREVENT, respectively; p > 0.05). Using standard thresholds (7.5% for PCE; 3.7%/4.9% for PREVENT in men/women), 36.5% vs 38.8% of with CAC ≥100 were classified below cutpoints, more often in women (70.8% vs 67.4%). Youden-derived thresholds (5.6% vs 2.7%) increased sensitivity (73.3% vs 78.4%) but reduced specificity (74.1% vs 66.7%) and expanded referral eligibility (30.6% vs 38.2%), respectively.
Conclusions:
Both tools showed comparable discrimination for CAC ≥100, but standard cutpoints miss individuals, especially women. Lower, optimized thresholds (PCE 5.6%; PREVENT 2.7%) may improve detection but warrant further evaluation.
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