Development and Validation of a Nomogram Predictive Model for Massive Ascites After Hepatectomy in Patients with Primary Hepatocellular Carcinoma.

OBJECTIVE

To develop and validate a nomogram for predicting massive ascites after hepatectomy in hepatocellular carcinoma (HCC) patients.

METHODS

A retrospective, single‑center study of 232 HCC patients who underwent hepatectomy (February 2021 - July 2025) was conducted. Patients with preoperative bile leakage or active hemorrhage were excluded. Patients were grouped by postoperative ascites status (massive, n=66; non-massive, n=166). Predictors were screened via univariate and multivariate logistic regression. A nomogram was built and internally validated using 1000 bootstrap samples. Performance was assessed via ROC analysis, calibration, and decision curve analysis (DCA), Clinical Impact Curve (CIC.

RESULTS

Multivariate analysis identified four independent predictors: platelet count (OR=0.985), AST (OR=1.027), portal hypertension (OR=5.288), and operative time (OR=5.011). The nomogram achieved an AUC of 0.837 (95% CI: 0.781-0.892) with good calibration (H-L test, P=0.860). DCA showed clinical net benefit across thresholds [0.00-0.71] and [0.86-0.93]and the clinical impact curve showing good concordance at risk thresholds above 0.4.

CONCLUSION

The nomogram accurately predicts massive ascites risk using four perioperative variables and demonstrates strong clinical utility for individualized management.