OBJECTIVETo examine the incidence of hepatitis B virus (HBV) S gene mutation in recipients with recurrent HBV infection after liver transplantation (LT) and to evaluate the clinical significance of these mutants.

METHODSTwo-hundred-and-ninety-nine patients who received LT for HBV-related liver diseases in single centre were enrolled in the study and followed up. Serum HBV DNA was amplified by fluorescence quantitative polymerase chain reaction, and HBV-S gene mutation was detected by Sanger's enzymatic method.

RESULTSTwelve of the 299 patients developed recurrent HBV after LT, and 2 of these 12 carried a mutant of the HBV-S gene (incidence rate of 16.67%). One of the patients had T126I and G145A mutations, and the other had a M 133L mutation. Cox regression modelling identified the risk factors of HBV recurrence after LT as HBV-YMDD mutants (P =0.01), HBV-S mutants (P =0.03) and compliance decrease (P =0.03).

CONCLUSIONHBV-S mutants may contribute to recurrence of HBV after LT, and the mechanism should be addressed in future studies.

Adult ; DNA, Viral ; genetics ; Female ; Genetic Variation ; Hepatitis B ; virology ; Hepatitis B virus ; genetics ; Humans ; Liver Transplantation ; Male ; Middle Aged ; Mutation ; Postoperative Period ; Recurrence ; Viral Envelope Proteins ; genetics

BACKGROUND/AIMS: Solitary hepatocellular carcinoma (HCC) is a subgroup of HCCs. We aimed to establish nomograms for predicting the survival of solitary HCC patients after hepatectomy. METHODS: A total of 538 solitary HCC patients were randomly classified into training and validation sets. A Cox model was used to identify predictors of overall survival (OS) in the training set. A nomogram was generated based on these predictors and was validated using the validation set. RESULTS: Tumor size, microvascular invasion, and major vascular invasion were significantly associated with OS in the training set. Nomograms were developed based on these predictors in the multivariate analysis. The C-index was 0.75 for the OS nomogram and 0.72 for the recurrence-free survival nomogram. Compared to the index of conventional staging systems for predicting survival (0.71 for Barcelona Clinic Liver Cancer, 0.66 for the seventh American Joint Committee on Cancer, 0.68 for Cancer of the Liver Italian Program, and 0.70 for Hong Kong Liver Cancer), the index of the OS nomogram was significantly higher. Moreover, the calibration curve fitted well between the predicted and observed survival rate. Similarly, in the validation set, the nomogram discrimination was superior to those of the four staging systems (p<0.001). CONCLUSIONS: The nomograms demonstrated good discrimination performance in predicting 3- and 5-year survival rates for solitary HCCs after hepatectomy.
Calibration ; Carcinoma, Hepatocellular* ; Discrimination (Psychology) ; Hepatectomy* ; Hong Kong ; Humans ; Joints ; Liver ; Liver Neoplasms ; Multivariate Analysis ; Nomograms* ; Prognosis ; Survival Rate

BACKGROUND/AIMS: Microvascular invasion (MVI) is an established risk factor for hepatocellular carcinoma (HCC). However, prediction models that specifically focus on the individual prognoses of HCC patients with MVI is lacking. METHODS: A total of 385 HCC patients with MVI were randomly assigned to training and validation cohorts in a 2:1 ratio. The outcomes were disease-free survival (DFS) and overall survival (OS). Prognostic nomograms were established based on the results of multivariate analyses. The concordance index (C-index), calibration plots and Kaplan-Meier curves were employed to evaluate the accuracy, calibration and discriminatory ability of the models. RESULTS: The independent risk factors for both DFS and OS included age, tumor size, tumor number, the presence of gross vascular invasion, and the presence of Glisson's capsule invasion. The platelet-to-lymphocyte ratio was another risk factor for OS. On the basis of these predictors, two nomograms for DFS and OS were constructed. The C-index values of the nomograms for DFS and OS were 0.712 (95% confidence interval [CI], 0.679 to 0.745; p<0.001) and 0.698 (95% CI, 0.657 to 0.739; p<0.001), respectively, in the training cohort and 0.704 (95% CI, 0.650 to 0.708; p<0.001) and 0.673 (95% CI, 0.607 to 0.739; p<0.001), respectively, in the validation cohort. The calibration curves showed optimal agreement between the predicted and observed survival rates. The Kaplan-Meier curves suggested that these two nomograms had satisfactory discriminatory abilities. CONCLUSIONS: These novel predictive models have satisfactory accuracy and discriminatory abilities in predicting the prognosis of HCC patients with MVI after hepatectomy.
Calibration ; Carcinoma, Hepatocellular ; Cohort Studies ; Disease-Free Survival ; Hepatectomy ; Humans ; Multivariate Analysis ; Nomograms ; Prognosis ; Risk Factors ; Survival Rate