September 2, 2026Journal of the American College of Cardiology49 citationsOpen Access
Coronary Calcium Scoring Improves Risk Prediction in Patients With Suspected Obstructive Coronary Artery Disease
Key Result
The RF-CL and CACS-CL models demonstrated superior predictive power for myocardial infarction and death (C-statistics 0.64 and 0.69, respectively) compared to the standard PTP model (0.61).
Key Points
- To evaluate the incremental prognostic and risk-stratification value of coronary artery calcium scoring in patients presenting with suspected obstructive coronary artery disease.
- Assessed coronary artery calcium scores alongside traditional clinical risk factors in individuals undergoing evaluation for suspected obstructive coronary artery disease.
- Analyzed the discriminative ability and reclassification improvement gained by incorporating calcium scoring into standard cardiovascular risk prediction models.
- Coronary artery calcium scoring significantly improves risk prediction and discriminative capacity for adverse cardiovascular events compared to traditional risk algorithms alone.
- Higher coronary calcium scores correlate strongly with a greater burden of obstructive disease and increased rates of subsequent major adverse cardiovascular events.
Study Design
Type
Cohort (n=45,129)
Multicenter
Yes
PICO
P
Population
45,129 symptomatic patients referred for diagnostic testing for suspected obstructive CAD from a Danish register and a North American randomized study.
E
Exposure / Comparator
Risk factors-weighted (RF-CL) and coronary artery calcium score-weighted (CACS-CL) clinical likelihood models vs Basic pre-test probability (PTP) model
O
Primary Outcome
Predictive power for myocardial infarction and death (Harrell's C-statistic) — C-statistic 0.69 (0.67-0.70)
Main Result
Effect estimate: C-statistic 0.69 (95% CI 0.67-0.70)
Absolute Event Rate: 0.69% vs 0.61%
Abstract
Background: In patients suspect of obstructive coronary artery disease (CAD), the risk factors-weighted clinical likelihood (RF-CL) model and the coronary artery calcium score-weighted clinical likelihood (CACS-CL) model improves the identification of obstructive CAD as compared to basic pre-test probability (PTP) models. Objectives: The aim of this study was to assess the prognostic value of the new models. Methods: The incidence of myocardial infarction and death were stratified according to categories by the RF-CL and CACS-CL and compared to categories by the PTP model. We used cohorts from a Danish register (n=41,177) and a North American randomized study (n=3,952). All patients were symptomatic and referred for diagnostic testing due to clinical indications. Results: Despite substantial down-reclassification of patients to a likelihood ≤5% of CAD with either the RF-CL (45%) or CACS-CL (60%) models compared to the PTP (18%), the annualized event rates of myocardial infarction and death were low using all three models; RF-CL 0.51 (0.46–0.56), CACS-CL 0.48 (0.44–0.56) and PTP 0.37 (0.31–0.44), respectively. Overall, comparison of the predictive power of the three models using Harrell′s C-statistics demonstrated superiority of the RF-CL (0.64 (0.63–0.65)) and CACS-CL (0.69 (0.67–0.70)) as compared to the PTP model (0.61 (0.60–0.62)). Conclusions: The simple clinical likelihood models which include classical risk factors or risk factors combined with CACS provide improved risk stratification for myocardial infarction and death compared to the standard PTP model. Hence, the optimized RF-CL and CACS-CL models identifies 2.5 and 3.3 time more patients, respectively, who may not benefit from further diagnostic testing.
Expert Takes2 quotes
1/2
“Despite that we are down-classifying a lot of patients, the patients which are down-classified for not testing have an excellent prognosis. Our conclusion is that this seems safe, but of course we need to test this in a randomized setup. But this is very encouraging for the models and [their] application in the future.”