Abstract
Background
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.
Methods
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.
Results
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.
Conclusion
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.
Author contributions
WYW and WP offered the idea of this study, JYS collected and analyzed the patient data. WYW drafted the manuscript. WP and XYZ performed the statistical analysis. TFW and CL made major contributions to the revision of the manuscript. All authors read and approved the final manuscript.
Disclosure statement
No potential conflict of interest was reported by the author(s).
Data availability statement
The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.