Nomogram for predicting postoperative recurrence in patients with microvascular invasion-negative hepatocellular...

Hepatocellular carcinoma (HCC) imposes a substantial global health burden, while postoperative recurrence remains a pivotal factor contributing to poor prognosis. Although existing prognostic models predominantly focus on patients with HCC with microvascular invasion (MVI), recurrence mechanisms and risk stratification in those with MVI-negative HCC remain underexplored despite their distinct clinicopathological profiles. As such, this study aimed to develop a prognostic nomogram to predict recurrence-free survival (RFS) in patients with MVI-negative HCC.

Data from 547 treatment-naïve patients with MVI-negative HCC were divided into 2 cohorts: training (n=375); and external validation (n=172). Random survival forest and multivariate Cox regression analyses were used to identify independent prognostic factors. A nomogram prediction model was developed based on risk factors identified in the training cohort and subsequently validated in the external validation cohort.

Key findings revealed that Ki-67, alpha-fetoprotein (AFP)-L3, neutrophil-to-lymphocyte ratio, AFP, and systemic immune-inflammation index significantly impacted RFS, with a concordance-index (C-index) exceeding 0.7 for the nomogram model in the training cohort, and an area under the receiver operating characteristic curve (AUC) of 0.758, 0.769, and 0.779 for 1-, 3-, and 5-year RFS, respectively. The external validation cohort corroborated these findings, achieving C-index values > 0.7 and AUC values of 0.717, 0.735, and 0.756 for the same time points. The calibration curves indicated strong agreement between the predicted and actual outcomes. Decision curve analysis revealed that the nomogram model demonstrated good net benefits for 1-, 3-, and 5-year RFS in both the training and external validation cohorts.

This study developed and validated a prognostic nomogram for predicting postoperative disease recurrence in patients with MVI-negative HCC, highlighting the importance of individualized patient management based on the risk factors identified.