A preoperative prediction model for microvascular invasion in hepatocellular carcinoma based on inflammatory...

The high postoperative recurrence rate of hepatocellular carcinoma (HCC) is closely associated with microvascular invasion (MVI). Inflammatory biomarkers play a crucial role in MVI progression. However, a preoperative prediction model integrating inflammatory biomarkers and clinical characteristics remains lacking. This study aimed to develop and validate a preoperative prediction model for MVI in HCC based on inflammatory factors and tumor features.

A retrospective analysis was conducted on 300 patients with HCC who underwent radical hepatectomy between 2019 and 2024. Independent predictors were identified via group difference tests and univariate and multivariate logistic regression analyses. A nomogram model was constructed and evaluated using calibration curves, decision curve analysis (DCA), and receiver operating characteristic (ROC) curves.

Poorly differentiated pathology, tumor diameter of ≥5 cm, des-γ-carboxyprothrombin of ≥90 mAU/mL, and platelet-to-lymphocyte ratio of ≥150 were identified as independent predictors of MVI. The nomogram exhibited area under the ROC curve values of 0.81 (95% CI, 0.75-0.88) in the internal training set and 0.83 (95% CI, 0.73-0.94) in the internal validation set (both derived from the same single-center dataset via 7:3 random splitting). Calibration curves showed excellent agreement between predicted and observed probabilities, and DCA confirmed the model's net benefit superiority over no-intervention or all-intervention strategies across a risk threshold range of 0.1 to 0.8.

The model integrates inflammatory biomarkers and tumor characteristics. This noninvasive prediction of MVI risk provides a quantitative basis for individualized preoperative treatment strategies. Prospective multicenter validation is warranted to improve its generalizability.