An early relapse prediction model based on pathological features following neoadjuvant immunotherapy for hepatocellular carcinoma

Background 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. Materials and Methods 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. Results 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. Conclusions 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.