Abstract
OBJECTIVE: To develop a nomogram to predict the risk of portal vein tumor thrombosis (PVTT) in hepatocellular carcinoma (HCC) patients. METHODS: Patients diagnosed with HCC at Hunan Provincial People's Hospital between January 2010 and January 2022 were enrolled. Data on demographic characteristics, comorbidities, and laboratory tests were collected. Multivariate logistic regression was used to identify independent risk factors for PVTT, which were then incorporated into a predictive nomogram. The nomogram's discriminative ability was evaluated using the area under the receiver operating characteristic (AUC) curve. Clinical utility was assessed through decision curve analysis (DCA). RESULTS: Being male (OR 1.991, 95% CI 1.314-3.017, P = 0.001), Barcelona Clinic Liver Cancer (BCLC) staging (stage C: OR 8.043, 95% CI 4.334-14.926, P<0.001; stage D: OR 7.977, 95% CI 3.532-18.017, P<0.001), tumor size >5 cm (OR 1.792, 95% CI 1.116-2.876, P = 0.016), and D-dimer (OR 1.126, 95% CI 1.083-1.171, P<0.001) were identified as independent risk factors for PVTT. The nomogram formula is: Logit = -2.8961 + 0.6586 (male) + BCLC staging (-0.1922 for B, 1.9251 for C, or 1.7938 for D) + 0.5418 (tumor size >5 cm) + 0.1051 DDi. The nomogram achieved an AUC of 0.798 (95% CI 0.774-0.822) in the training set and 0.822 (95% CI 0.782-0.862) in the validation set. Sensitivities were 86.6% and 90.7%, while specificies were 68.2% and 71.8% in the training and validation sets, respectively, demonstrating strong discrimination and predictive accuracy. DCA indicated a favorable risk threshold probability. CONCLUSION: A nomogram incorporating male sex, BCLC staging, tumor size, and D-dimer demonstrated good predictive performance for PVTT. This tool may aid in the early comprehensive assessment of PVTT risk in HCC patients.