Development and validation of prediction models
The study was a population-based retrospective cohort study. Number and percentage (The time-dependent receiver operating characteristic (ROC) curves and concordance index (C-index) were used to evaluate the predictability of the models. The areas under ROC curves (AUCs) and C-index ranged from 0.5 to 1, and the values over 0.7 indicated nice predictability. Calibration curve plots were used to assess the difference degree between the predicted and actual risks. Decision curve analysis (DCA) was performed to evaluate the clinical benefit and utility of the constructed prediction models. Furthermore, we divided all the patients into low-risk and high-risk levels according to the model-predicted risk score. The patients with a risk score higher than the median were assigned into the high-risk group, and the rest were assigned into the low-risk group. The Kaplan–Meier (K-M) plots and log-rank test were used to perform survival analysis to compare the survival difference between the two groups. The hazard ratio (HR) with 95% confidence interval (CI) was calculated. It was regarded as a significant difference when 