A novel inflammation-based nomogram system to predict survival of patients with hepatocellular carcinoma

Background and Aim: The existed staging systems were limited in the accuracy of prediction for overall survival (OS) of hepatocellular carcinoma (HCC) patients. The aim of this study is to establish a novel inflammation-based prognostic system with nomogram for HCC patients. Methods: A prospective cohort of patients was recruited and assigned to the training cohort (n = 659) and validation cohort (n = 320) randomly. Different inflammation-based score systems were evaluated to select the best one predicting overall survival (OS). The inflammation-based score system with the highest predicting value and the parameters best reflecting tumor burden identified by multivariate analysis were selected to construct a novel predicting nomogram system. The predictive accuracy and discriminative ability of the nomogram were evaluated by concordance index (C-index) and calibration curve and compared with conventional staging systems. Results: With a highest C-index and areas under the receiver operating characteristic curve (AUC), C-reactive protein/albumin ratio (CAR) was selected to construct the novel system, along with tumor number, tumor size, macrovascular invasion and extra-hepatic metastases. The C-index of the nomogram was 0.813 (95% CI, 0.789-0.837) in the training cohort and 0.794 (95% CI, 0.756-0.832) in the validation cohort. The calibration curve for predicting probability of survival showed that the nomogram had a high consistency with follow-up data. The C-index of the novel system was higher than other conventional staging systems (P < 0.001). Conclusions: The novel inflammation-based nomogram, developed from prospectively collected data in the present study, predicted the OS of HCC patients.