Development and Validation of a Nomogram for Predicting Response to TACE Combined with Lenvatinib and Anti-PD-1 Therapy in Unresectable Hepatocellular Carcinoma

Background: The prognosis for unresectable hepatocellular carcinoma (u-HCC) patients receiving monotherapy remains poor, driving the need for more effective combination therapies. Although transarterial chemoembolization (TACE) combined with targeted therapy and immunotherapy shows promising efficacy, robust biomarkers are needed to identify patients most likely to benefit. This study aimed to develop and validate a nomogram to predict treatment response in u-HCC patients receiving triple therapy. Methods: We conducted a multicenter retrospective study including u-HCC patients who received triple therapy between January 2021 and June 2024. Patients from one hospital (n=91) were assigned to the training cohort, and those from two other centers (n=54) constituted the external validation cohort. Treatment response was evaluated according to mRECIST criteria. Univariate and multivariate logistic regression analyses were performed to identify independent predictors of the objective response rate (ORR). A nomogram integrating clinical and imaging features was constructed and evaluated using receiver operating characteristic (ROC) curves, calibration plots, and decision curve analysis (DCA). Results: Multivariate analysis identified six independent predictors of ORR: alpha-fetoprotein (AFP) level, lymphocyte-to-monocyte ratio (LMR), portal vein tumor thrombus (PVTT), tumor number, irregular arterial phase enhancement, and tumor rupture. The combined nomogram, integrating clinical and imaging features, demonstrated superior predictive performance, with AUCs of 0.915 (95% CI: 0.838– 0.963) in the training cohort and 0.933 (95% CI: 0.831– 0.983) in the validation cohort. Calibration curves showed good agreement between predicted and observed probabilities, and DCA confirmed the clinical utility of the model. The incidence of adverse events did not differ significantly among treatment regimens (P > 0.05). Conclusion: We developed and validated a non-invasive nomogram that integrates readily available clinical and imaging features to effectively predict treatment response to triple therapy in u-HCC patients. This tool holds potential for personalizing treatment strategies and improving prognostic assessment. Keywords: unresectable hepatocellular carcinoma, transcatheter arterial chemoembolization, lenvatinib, immunotherapy, radiological characteristics, predictive model