The Establishment Of Two Novel Online Nomograms For Predicting The Survival Of Individual Patients Undergoing Partial Hepatectomy For Huge Hepatocellular Carcinoma

Background and Aim:Hepatectomy is an effective treatment in selective patients with huge hepatocellular carcinoma(Huge HCC,diameter≥10cm).Assessing the average survival rate of patients with Huge HCC after radical resection is significant for making critical decisions in clinical practice.This study is aimed at establishing two online nomograms for predicting the overall survival(OS)and disease-free survival(DFS)of such HCC patients.Methods:A total of 303 consecutive huge HCC patients who underwent hepatectomy from the First Affiliated Hospital of Anhui Medical University between January 2005 and December 2018 were set as training cohort.An external validation was performed in an independent cohort including 147 cases from the First Affiliated Hospital of University of Science and Technology of China in the same period.The clinicopathologic characteristics and follow-up information of the two groups were observed.A Cox model was used to identify predictors of the prognosis in the training cohort.Two dynamic nomograms for OS and DFS were developed and validated based on the data.The performance of the nomograms was evaluated by concordance index(C-index)and calibration curve.And the discrimination of the two nomograms were compared with that of conventional staging systems.Results:Based on multivariate analysis of the training cohort,independent factors including HBV DNA load,alpha-fetoprotein(AFP),gamma-glutamyl transpeptidase to platelet ratio(GPR),liver cirrhosis,satellite,portal vein tumor thrombus(PVTT),tumor morphology and diameter were screened and incorporated into the nomogram for OS.In the same situation,besides the above factors,microvascular invasion(MVI)were incorporated into the nomogram for DFS.In the training cohort,the OS-nomogram achieved a C-index of 0.745(95% confidence interval,0.708-0.782)in predicting the1-,3-,and 5-year OS and 0.738(95% confidence interval,0.703-0.773)in DFS,which was much more accurate than four conventional staging systems(P<0.05).And these results were supported by the external validations(C-index was 0.822 for OS,0.827 for DFS,P<0.05).The calibration graphs of the endpoint showed a favorable agreement between the nomograms’ assessments and actual observations.Conclusion:The two web-based nomograms demonstrated optimal predictive performance in patients with Huge HCC after hepatectomy,providing a practical method in customized treatment deriving from the risk of individual patients.