Nomogram for predicting survival in patients with advanced hepatocellular carcinoma treated with PD-1 inhibitors: incorporating pre-treatment and post- treatment clinical parameters

Abstract

Abstract Background: Immunotherapy has transformed cancer treatment patterns for advanced hepatocellular carcinoma (aHCC) in recent years. Therefore, the identification of predictive biomarkers has important clinical implications. Methods: We collected medical records from 117 aHCC patients treated with anti-PD-1 antibody. Kaplan-Meier analysis and Cox proportional hazard regression were used to evaluate the association between peripheral blood biomarkers and overall survival (OS) and progression-free survival (PFS). Finally, the prognostic nomogram was constructed. Results: The mPFS and mOS were 7.0 months and 18.7 months, respectively. According to Kaplan-Meier analysis and Cox regression analysis, we regarded the treatment regimen (p = 0.020), Hb at 6-week (p= 0.042), NLR at 6-week (p < 0.001), SII at 6-week (p = 0.125) as predictors of PFS, and AFP (p = 0.035), PLR (p = 0.012), Hb at 6-week (p = 0.010) and NLR at 6-week (p = 0.020) as predictors of OS. Furthermore, the results suggest that the OS and PFS nomogram model were in agreement with actual observations. Conclusion: Biomarkers in peripheral blood can predict the prognosis of patients with aHCC treated with anti-PD-1 antibody. The development of nomogram models can help us to screen potential patients who can benefit from immunotherapy.