基于病理特征的肝细胞癌新辅助免疫治疗后早期复发预测模型

The emergence of neoadjuvant immunotherapy has improved outcomes for hepatocellular carcinoma (HCC) patients, yet early postoperative recurrence remains a critical challenge. This study aimed to identify clinicopathological and immune microenvironment features associated with recurrence-free survival (RFS) and develop a predictive model for early recurrence in HCC patients undergoing neoadjuvant anti-PD-1 antibody therapy.

Clinicopathological characteristics and immune microenvironment profiles were analyzed in 70 HCC patients treated with neoadjuvant anti-PD-1 antibody and 20 patients receiving transarterial chemoembolization (TACE). Key variables, including microvascular invasion (MVI), tumor capsule integrity, and immune cell infiltration, were evaluated. Statistical analyses included multivariate Cox regression, Kaplan-Meier survival analysis, and nomogram construction with internal validation to predict recurrence risk.

Foam cell response and tumor-infiltrating lymphocytes (TILs) were strongly linked to favorable immunotherapy responses. Patients without MVI, those with intact tumor capsules, and those exhibiting high CD4+ T cell density in central tumor regions demonstrated significantly prolonged RFS. A nomogram integrating these three factors achieved robust predictive accuracy for early recurrence stratifying patients into distinct risk groups.

This study highlights MVI absence, tumor capsule integrity, and CD4+ T cell infiltration as key predictors of RFS in HCC patients receiving neoadjuvant immunotherapy. The proposed nomogram provides a clinically actionable tool for early recurrence risk assessment, enabling personalized postoperative monitoring and adjuvant therapy strategies to improve survival outcomes.