A Clinical-Imaging Nomogram for Predicting Post-Hepatectomy Recurrence in Hepatocellular Carcinoma with Microvascular Invasion.

Authors

Shiyuan Huang, Bin Chen, Yunyun Wei, Yi Tang

Published in

Journal of gastrointestinal surgery : official journal of the Society for Surgery of the Alimentary Tract. Pages 102524. Aug 13, 2026. Epub Aug 13, 2026.

Abstract

This study aimed to develop an individualized nomogram incorporating clinical and imaging features for predicting recurrence in hepatocellular carcinoma (HCC) patients with microvascular invasion (MVI) after hepatectomy.
A total of 317 pathologically confirmed MVI-positive HCC patients who underwent curative resection between January 2016 and December 2022 were analyzed retrospectively. Independent risk factors for recurrence-free survival (RFS) were identified through univariate and multivariate Cox regression analyses. A nomogram was developed based on these factors, and its performance was evaluated by the concordance index (C-index), time-dependent receiver operating characteristic (ROC) curves, and calibration curves. Its clinical utility was assessed with decision curve analysis (DCA).
The developed nomogram incorporated four independent predictors for estimating RFS, including MVI grade, AFP, liver cirrhosis, and smooth tumor margin. The model demonstrated good discriminative ability, with a C-index of 0.758 (95% confidence interval [CI]: 0.720-0.803) in the training cohort and 0.702 (95% CI: 0.642-0.790) in the validation cohort. Calibration curves showed good agreement between predictions and observations. Stratified by the nomogram score, patients in the high-risk group had significantly worse RFS than those in the low-risk group (Log-rank p < 0.0001). Additionally, DCA demonstrated the clinical utility of the nomogram across a wide range of threshold probabilities.
The proposed clinical-imaging nomogram provides individualized risk estimates for post-hepatectomy recurrence in MVI-positive HCC patients. This tool facilitates risk stratification, aids clinicians in tailoring postoperative surveillance and adjuvant therapy, and helps identify high-risk patients for timely intervention.

PMID:
42594999
Bibliographic data and abstract were imported from PubMed on 14 Aug 2026.

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