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• W2892692544 abstract "Abstract 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." @default.
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• W2892692544 date "2018-09-27" @default.
• W2892692544 modified "2023-10-14" @default.
• W2892692544 title "A novel inflammation-based nomogram system to predict survival of patients with hepatocellular carcinoma" @default.
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• W2892692544 doi "https://doi.org/10.1002/cam4.1787" @default.
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