Key result
Combining CAD-RADS with clinical risk factors and CAC strongly predicts MACE with 0.82 AUC.
Why the study?
Although CAD-RADS offers structured reporting for coronary computed tomography angiography and has been deemed useful for prognostication, its overall prognostic value in suspected CAD required meta-analytic assessment.
Does CAD-RADS categorization predict major adverse cardiovascular events in patients with suspected coronary artery disease?
Meta-Analysis (n=37,596)
Does CAD-RADS categorization predict major adverse cardiovascular events in patients with suspected coronary artery disease?
CAD-RADS categorization provides significant prognostic value for predicting major adverse cardiovascular events and all-cause mortality in patients with suspected coronary artery disease.
Answers are grounded in this paper and cite their sources.
Supports integrating CAD-RADS with clinical factors and CAC for MACE stratification in suspected CAD; extends prior data with pooled high predictive value.
Background: Coronary Artery Disease-Reporting and Data System (CAD-RADS) is a standardized reporting system that offers a structured method for interpreting and reporting results obtained through coronary computed tomography angiography. It has been deemed useful in the prognostication of patients with suspected coronary artery disease (CAD). Purpose: The present meta-analysis sought to assess the prognostic value of CAD-RADS in individuals with suspected CAD. Materials and Methods: We conducted a systematic search of the electronic databases of PubMed, Web of Science Core Collection, Cochrane advanced search, and EMBASE. A random-effects model was implemented to evaluate the pooled hazard ratio (HR) for each CAD-RADS category and area under the receiver operating characteristics curve for predicting major adverse cardiovascular events. Results: Data from 37 596 coronary computed tomography angiography examinations from 13 studies were analyzed. During follow-up, 2,536 (6.7%) adverse events were observed. Pooled HRs for prediction of adverse events were significant for all CAD-RADS categories, with incremental increase in HRs with progressively higher categories. For prediction of all-cause mortality, all categories except CAD-RADS 1 showed significant HR compared with CAD-RADS 0. Combination of CAD-RADS to conventional clinical risk factors and CAC resulted in a high predictive capacity for adverse events (pooled area under the receiver operating characteristics curve: 0.82 ([95% confidence interval, 0.73-0.91]). Conclusion: The CAD-RADS category imparts information on the CAD severity and shows incremental increase in HR for adverse events with progressively higher categories, especially beyond CAD-RADS4b.
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Kato et al. (2024) conducted a meta-analysis in Suspected coronary artery disease (n=37,596). CAD-RADS vs. CAD-RADS 0 was evaluated on Major adverse cardiovascular events (AUC 0.82, 95% CI 0.73-0.91). Combining CAD-RADS with conventional clinical risk factors and CAC resulted in a high predictive capacity for adverse events (pooled AUC 0.82; 95% CI 0.73-0.91).
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