Residual CatLet score predicts the long-term prognosis in “all-comers” patients with coronary artery disease: a survival analysis study based on time-dependent receiver operating characteristic curves

Background: In recent years, the incidence and mortality rates of coronary artery disease (CAD) have been rising annually. This study aimed to evaluate the ability of the coronary artery tree description and lesion evaluation (CatLet) angiographic scoring system to stratify risk and to elucidate its independent prognostic value in “all-comers” patients with CAD. Methods: A total of 373 consecutive CAD patients were enrolled at The First People’s Hospital of Hefei following coronary angiography. The residual CatLet (rCatLet) score was calculated based on the residual lesions after completion of required revascularization at physicians’ discretion during this hospitalization for all enrolled patients, who subsequently underwent follow-ups. The primary endpoint was major adverse cardiac and cerebrovascular events (MACCEs). Secondary endpoints included all-cause death and cardiac death. Survival rates were estimated using the Kaplan-Meier method, and Cox regression analysis was performed to identify independent prognostic factors, while the prognostic value of the rCatLet score was evaluated by the time-dependent area under the receiver operating characteristic (ROC) curve (AUC). Results: This was a single-center cohort study of 279 patients, including 56 (20.07%) with acute coronary syndrome (ACS) and 223 (79.93%) with chronic coronary syndrome (CCS). Kaplan-Meier analysis showed progressively worse prognosis across higher rCatLet score tertiles for all endpoints (all log-rank P<0.001). Cox regression revealed that, compared with the low tertile, the highest rCatLet tertile was associated with a significantly increased risk of MACCEs [hazard ratio (HR) =4.96; 95% confidence interval (CI): 3.03–8.12], and the medium tertile showed a non-significant trend toward higher risk (HR =1.39; 95% CI: 0.79–2.43). Time-dependent ROC analysis showed that the rCatLet model predicted 1-, 3-, and 6-year MACCEs with AUCs (95% CIs) of 0.85 (0.77–0.92), 0.73 (0.64–0.81), and 0.71 (0.64–0.77). The multivariable-adjusted models performed better, and their AUCs (95% CIs) at the three time points were 0.87 (0.83–0.92), 0.78 (0.72–0.86), and 0.78 (0.73–0.84), respectively. Conclusions: Our exploratory findings suggest that the rCatLet score has predictive value for the short- and long-term clinical prognosis in “all-comers” patients with CAD. Furthermore, the rCatLet score adjusted for clinical variables showed improved prognostic predictive values. These findings require further validation in future studies.