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Published on: August 28, 2018
Prognostic value of CAD-RADS classification by coronary CTA in patients with suspected CAD
Zengfa Huang1, Shutong Zhang1, Nan Jin2
1Department of Radiology, The Central Hospital of Wuhan, Tongji Medical College, Huazhong University of Science and Technology, 26 Shengli Avenue, Jiangan, Wuhan, 430014, Hubei, China.
Insights
The Coronary Artery Disease Reporting and Data System (CAD-RADS) classification effectively predicts mortality risk in suspected coronary artery disease (CAD) patients. This system is as effective as traditional methods and the Duke Prognostic CAD Index for assessing patient outcomes.
Area of Science:
- Cardiology
- Medical Imaging
- Prognostic Biomarkers
Background:
- Coronary artery disease (CAD) poses a significant global health burden.
- Accurate risk stratification is crucial for managing patients with suspected CAD.
- Existing classification systems for CAD vary in their prognostic capabilities.
Purpose of the Study:
- To compare the prognostic value of the Coronary Artery Disease Reporting and Data System (CAD-RADS) classification against traditional CAD classifications and the Duke Prognostic CAD Index.
- To evaluate the ability of these systems to predict all-cause mortality in patients with suspected CAD.
Main Methods:
- A retrospective analysis of 9625 patients with suspected CAD who underwent coronary computed tomography angiography (CTA).
- Assessment of CAD-RADS, traditional CAD classifications, and Duke Prognostic CAD Index for predicting all-cause mortality.
- Utilized Kaplan-Meier analysis, multivariable Cox regression, and time-dependent receiver-operating characteristic (ROC) curves.
Main Results:
- All-cause mortality increased significantly with higher CAD-RADS grades, traditional classifications, and the Duke Prognostic CAD Index.
- CAD-RADS demonstrated a graded increase in mortality risk, with HRs rising from 0.861 for CAD-RADS 1 to 2.761 for CAD-RADS 4B/5.
- The discriminatory ability of CAD-RADS for predicting all-cause mortality was non-inferior to traditional methods and the Duke Prognostic CAD Index across 1, 3, and 5 years.
Conclusions:
- CAD-RADS classification offers valuable prognostic information for suspected CAD patients, comparable to established methods.
- While effective, the complexity of CAD-RADS and Duke Prognostic CAD Index may favor simpler, traditional classifications for routine use.
- The study highlights the prognostic utility of noninvasive imaging-based classifications in cardiovascular risk assessment.
Background:
The study sought to compare Coronary Artery Disease Reporting and Data System (CAD-RADS) classification with traditional coronary artery disease (CAD) classifications and Duke Prognostic CAD Index for predicting the risk of all-cause mortality in patients with suspected CAD.
Methods:
9625 consecutive suspected CAD patients were assessed by coronary CTA for CAD-RADS classification, traditional CAD classifications and Duke Prognostic CAD Index. Kaplan-Meier and multivariable Cox models were used to estimate all-cause mortality. Discriminatory ability of classifications was assessed using time dependent receiver-operating characteristic (ROC) curves and The Hosmer-Lemeshow goodness-of-fit test was employed to evaluate calibration.
Results:
A total of 540 patients died from all causes with a median follow-up of 4.3 ± 2.1 years. Kaplan-Meier survival curves showed the cumulative events increased significantly associated with CAD-RADS, three traditional CAD classifications and Duke Prognostic CAD Index. In multivariate Cox regressions, the risk for the all-cause death increased from HR 0.861 (95% CI 0.420-1.764) for CAD-RADS 1 to HR 2.761 (95% CI 1.961-3.887) for CAD-RADS 4B&5, using CAD-RADS 0 as the reference group. The relative HRs for all-cause death increased proportionally with the grades of the three traditional CAD classifications and Duke Prognostic CAD Index. The area under the time dependent ROC curve for prediction of all-cause death was 0.7917, 0.7805, 0.7991for CAD-RADS in 1 year, 3 year, 5 year, respectively, which was non-inferior to the traditional CAD classifications and Duke Prognostic CAD Index.
Conclusions:
The CAD-RADS classification provided important prognostic information for patients with suspected CAD with noninvasive evaluation, which was non-inferior than Duke Prognostic CAD Index and traditional stenosis-based grading schemes in prognostic value of all-cause mortality. Traditional and simplest CAD classification should be preferable, given the more number of groups and complexity of CAD-RADS and Duke prognostic index, without using more time consuming classification.
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