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A nomogram for predicting overall survival in advanced hepatocellular carcinoma patients receiving radiotherapy
Xiaoqin Liu1,2, Bin Zeng2, Jun Liu2
1Department of Oncology, The Affiliated Hospital, Southwest Medical University, Luzhou, China.
Background:
Although radiotherapy (RT) combined with targeted therapy has emerged as a viable treatment for advanced hepatocellular carcinoma (HCC), predicting survival outcomes remains difficult. This study aimed to develop and validate a prognostic model integrating clinical parameters to predict overall survival (OS) in patients with advanced-stage HCC receiving RT combined with targeted therapy.
Methods:
A total of 248 advanced HCC patients treated with intensity-modulated RT (IMRT) combined with targeted therapy were retrospectively enrolled from three tertiary hospitals in China and randomly divided into training (n=148) and validation (n=100) cohorts. Least absolute shrinkage and selection operator (LASSO) regression followed by multivariable Cox analysis was used to identify independent prognostic factors. A nomogram was constructed to predict 1-, 2-, and 3-year OS, and its performance was evaluated using time-dependent receiver operating characteristic (ROC) curves, calibration plots, and decision curve analysis (DCA).
Results:
In the training cohort, a prognostic nomogram was developed based on four independent prognostic factors: Child-Pugh classification, portal vein tumor thrombosis (PVTT), M stage, and alpha-fetoprotein (AFP) level. In the validation cohort, this nomogram achieved promising predictive performance, with AUC values of 0.688, 0.817, and 0.847 for 1-, 2-, and 3-year OS, respectively. Calibration curves indicated excellent consistency between predicted and actual survival outcomes. Moreover, DCA demonstrated favorable net clinical benefit across all time points.
Conclusions:
The proposed LASSO-Cox-based nomogram enables individualized survival prediction in patients with advanced HCC treated with RT combined with targeted therapy.
