Nomogram based on tumor burden score for prediction of prognosis of patients with hepatocellular carcinoma before hepatectomy

基于肿瘤负荷评分的列线图用于预测肝细胞癌患者肝切除术前的预后

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Abstract

PURPOSE: To develop nomogram models predicting the prognosis for patients with hepatocellular carcinoma (HCC) before hepatectomy. METHODS: Patients treated at the Eastern Hepatobiliary Surgery Hospital and Zhongda Hospital, Southeast University, from January 2012 to July 2014, were retrospectively enrolled. Prediction models for overall survival (OS) and recurrence-free survival (RFS) were constructed. RESULTS: A total of 1117 patients with HCC were enrolled in this study, and were divided into a training cohort (n=838) and a validation cohort (n=279). A prediction model for OS in the training cohort (OS-nomo, C-index=0.71), including alpha-fetoprotein (AFP), estimated hepatectomy extent, and tumor burden score (TBS) as independent factors (all P<0.05), was constructed. For clinical application, we stratified all patients into three distinct risk groups: low-, medium-, and high-risk group for OS, based on total points (TPs). Patients undergoing major hepatectomy, with AFP>20 ng/mL and high level of TBS had the worst OS. CONCLUSION: When selecting patients with HCC for hepatectomy, factors including sex, CPS, AFP level, estimated hepatectomy extent, and TBS should be carefully considered. OS-nomo model could serve as important tool for personalized survival prediction.

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