Fig. 4

Evaluation of the performance of the nomogram. Validation of the discrimination power of the nomogram by ROC curve analysis in the training (A) internal test (B) and external test set (C); Time-dependent AUCs indicated that the nomogram had favorable accuracy for predicting PFS in the range of 5 months to 25 months (D, E, and F). Calibration plot of the nomogram in the training (G) internal test (H) and external test set (I), the blue diagonal line indicates the perfect prediction of the ideal model. The solid black line represents the performance of the nomogram, and the closer the fit to the diagonal line, the more accurate the prediction. The gray dashed line represents the performance of the model trained after bootstrapping validation (1000 bootstrap resamples), which corrects the overfitting situation; DCA analysis of the nomogram in the training (J) internal test (K) and external test set (L). The Y-axis represents the net benefit, the X-axis represents the threshold probability. The red line represents the nomogram, and the blue and orange lines represent the all-patient treatment scenario and the no-patient treatment scenario, respectively. Abbreviations: ROC: receiver operating characteristic; AUC: area under the curve; DCA: decision curve analysis