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Curative hepatectomy is currently the first-line treatment for hepatocellular carcinoma (HCC), but the prognosis is still not optimistic. The prediction model for prognosis of hepatitis B virus (HBV)-related BCLC 0-A stage HCC has not been well established. Therefore, we aimed to develop new nomograms to predict recurrence and survival in these patients. A total of 982 patients with HBV-related BCLC 0-A stage HCC who underwent curative hepatectomy at West China Hospital from February 2007 to February 2016 were retrospectively collected and randomly allocated to a training set and a validation set in a ratio of 4:1. Prognostic nomograms using data from the training set were developed using a Cox regression model and validated on the validation set. We constructed nomograms based on independent factors for recurrence-free survival (RFS) (tumor size, satellite, microvascular invasion, capsular invasion, differentiation and aspartate aminotransferase to albumin ratio (ASAR)) and overall survival (OS) (gender, tumor size, satellite, microvascular invasion, differentiation, lymphocyte count, and ASAR). Compared with conventional HCC staging systems and other nomograms reported by previous literature, our ASAR integrated nomograms predicted RFS and OS with the highest C-indexes (0.682 (95%CI: 0.646–0.709), 0.729 (95%CI: 0.691–0.766), respectively) and had well-fitted calibration curves in the training set. Concurrently, the nomograms also obtained consistent results in the validation set. DCA revealed that our nomograms provided the largest clinical net benefits. We first constructed ASAR integrated nomograms to predict the prognosis of HBV-related BCLC 0-A stage HCC patients after curative hepatectomy with good performance.

Prognostic nomograms for HBV-related BCLC 0-a stage hepatocellular carcinoma incorporating aspartate aminotransferase to albumin ratio