Nomogram models for 
tumor
TUMOR, RECURRENCE
Among the four variables discussed above, three variables (total CTC count, tumor size, and node number) were available preoperatively. We established two nomogram models based on three risk factors and four total risk factors for preoperative and postoperative prediction, respectively (Figure Extrahepatic recurrence (EHR) prediction nomogram models establishment and the predictive performance evaluation. (A, B) The nomograms of the three risk factors model and the four risk factors model. (C, D) Calibration curve for the three risk factors model and the four risk factors model in the development cohort. (E, F) ROC curves analyses indicated the good performance of EHR of the two nomogram models in the development cohort. Area under the curve (AUC) values of (E) 82.2% for the three risk factors model and (F) 84.1% for the four risk factors model in the development cohort. (G, H) DCA of the (G) three risk factors model and (H) four risk factors model for predicting EHR in the development cohort. (I, J) Clinical impact curves of the (I) three risk factors model and (J) four risk factors model for predicting EHR in the development cohort.