Prognostic nomogram validation
The concordance index (C-index) was used to measure the accuracy of model predictions. A value above 0.7 indicates that the predictive model has excellent discriminative ability. The receiver operating characteristic (ROC) curve was employed to evaluate the performance of classification models. An area under the ROC curve (AUC) above 0.7 signifies that the model possesses excellent discriminative ability. The calibration curve was used to verify the accuracy of probability predictions. A curve close to the 45-degree diagonal line indicates that the predicted probabilities are consistent with the actual observed probabilities. Finally, decision curve analysis (DCA) was utilized to appraise the clinical utility of a predictive model at different thresholds.