Nomogram Model for Prediction of Portal Vein Thrombosis in Patients with Liver Cirrhosis After Splenectomy: A Retrospective Analysis of 2 Independent Cohorts

Background: The aim of this study was to establish and validate an easy-to-use nomogram to predict portal vein thrombosis (PVT) in patients with cirrhosis after splenectomy and to test its predictive ability. Material/Methods: This retrospective study included 315 patients with cirrhosis who underwent splenectomy at 2 high-volume medical centers. The least absolute shrinkage and selection operator (LASSO) regression method was used to select the predictors in the training cohort, and multivariable logistic regression analysis was performed to establish the predictive nomogram model. We determined the prediction value of the nomogram by the area under the receiver operating characteristic curve (AUROC), the calibration curve, and decision curve analysis. Finally, the applicability of the nomogram was internally and independently validated. Results: The predictors of PVT included portal vein diameter, splenic vein diameter, body mass index, and platelet count. Based on the clinical and radiomic models, the nomogram had good predictive efficiency for predicting PVT in patients with cirrhosis after splenectomy, with an AUROC of 0.887 (0.856 in internal validation and 0.796 in independent validation). The decision curve analysis revealed that the nomogram had good clinical application value. Conclusions: We successfully developed an easy-to-use nomogram to predict the probability of PVT in patients with cirrhosis after splenectomy. The nomogram can help clinicians make timely, individualized clinical decisions for PVT in patients with cirrhosis after splenectomy.