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Level of hepatitis B surface antigen might serve as a new marker to predict hepatocellular carcinoma recurrence following curative resection in patients with low viral load.

ABSTRACT: To investigate the association between preoperative HBsAg (hepatitis B surface antigen) level and risk of HCC (hepatocellular carcinoma) recurrence following curative resection, we enrolled 826 HBV-related HCC patients who underwent curative resection and received long-term follow-up at the Eastern Hepatobiliary Surgery Hospital (Shanghai, China). Multivariate analyses showed that serum HBsAg ? 2000 S/CO, seropositive hepatitis B e antigen (HBeAg), ?-glutamyl transpeptidase > 61 U/L, prothrombin time > 13 s, multinodularity, lager tumor size, and major portal vein invasion were independently associated with a increased risk of HCC recurrence. Compared with HCC patients with HBsAg level < 2000 S/CO, HCC patients with HBsAg level ? 2000 S/CO had a higher prevalence of seropositive HBeAg, antiviral therapy, and cirrhosis; were younger; and had a higher levels of alanine transaminase (ALT), aspartate aminotransferase (AST), and HBV viral load. Multivariable stratified analyses showed HCC patients with HBsAg level < 2000 S/CO tended to have a lower incidence of HCC recurrence in following subgroups of patients, including for noncirrhotic (HR, 0.561; 95% CI, 0.345-0.914), HBV DNA < 2000 IU/mL (HR, 0.604; 95% CI, 0.401-0.912), ALT ? 41 U/L (HR, 0.643; 95% CI, 0.440-0.942), AST ? 37 U/L (HR, 0.672; 95% CI, 0.459-0.983), and seronegative HBeAg (HR, 0.682; 95% CI, 0.486-0.958). When we evaluated HBeAg-negative patients with HBV DNA < 2000 IU/mL, HBsAg level still determined risk of HCC recurrence (p = 0.014), but not HBV DNA (p = 0.550) and ALT (p = 0.186). These results suggest high levels of HBsAg increase risk of HCC recurrence following curative resection. HBsAg level might serve as a new marker to complement HBV DNA level in predicting HCC recurrence, especially in HBeAg-negative patients with low viral load.

SUBMITTER: Zhou HB

PROVIDER: S-EPMC4396049 | biostudies-literature | 2015

REPOSITORIES: biostudies-literature

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Level of hepatitis B surface antigen might serve as a new marker to predict hepatocellular carcinoma recurrence following curative resection in patients with low viral load.

Zhou Hua-Bang HB Li Qiao-Mei QM Zhong Zheng-Rong ZR Hu Jing-Yi JY Jiang Xiao-Lan XL Wang Hao H Wang Hui H Yang Bing B Hu He-Ping HP

American journal of cancer research 20150115 2

To investigate the association between preoperative HBsAg (hepatitis B surface antigen) level and risk of HCC (hepatocellular carcinoma) recurrence following curative resection, we enrolled 826 HBV-related HCC patients who underwent curative resection and received long-term follow-up at the Eastern Hepatobiliary Surgery Hospital (Shanghai, China). Multivariate analyses showed that serum HBsAg ≥ 2000 S/CO, seropositive hepatitis B e antigen (HBeAg), γ-glutamyl transpeptidase > 61 U/L, prothrombin ...[more]

PMID: 25973313

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Project description:OBJECTIVE:To construct a prediction model based on peritumoral radiomics signatures from CT images and investigate its efficiency in predicting early recurrence (ER) of hepatocellular carcinoma (HCC) after curative treatment. MATERIALS AND METHODS:In total, 156 patients with primary HCC were randomly divided into the training cohort (109 patients) and the validation cohort (47 patients). From the pretreatment CT images, we extracted 3-phase two-dimensional images from the largest cross-sectional area of the tumor. A region of interest (ROI) was manually delineated around the lesion for tumoral radiomics (T-RO) feature extraction, and another ROI was outlined with an additional 2 cm peritumoral area for peritumoral radiomics (PT-RO) feature extraction. The least absolute shrinkage and selection operator (LASSO) logistic regression model was applied for feature selection and model construction. The T-RO and PT-RO models were constructed. In the validation cohort, the prediction efficiencies of the two models and peritumoral enhancement (PT-E) were evaluated qualitatively by receiver operating characteristic (ROC) curves, calibration curves and decision curves and quantitatively by area under the curve (AUC), the category-free net reclassification index (cfNRI) and integrated discrimination improvement values (IDI). RESULTS:By comparing AUC values, the prediction accuracy in the validation cohort was good for the PT-RO model (0.80 vs. 0.79, P = 0.47) but poor for the T-RO model (0.82 vs. 0.62, P < 0.01), which was significantly overfitted. In the validation cohort, the ROC curves, calibration curves and decision curves indicated that the PT-RO model had better calibration efficiency and provided greater clinical benefits. CfNRI indicated that the PT-RO model correctly reclassified 47% of ER patients and 32% of non-ER patients compared to the T-RO model (P < 0.01); additionally, the PT-RO model correctly reclassified 24% of ER patients and 41% of non-ER patients compared to PT-E (P = 0.02). IDI indicated that the PT-RO model could improve prediction accuracy by 0.22 (P < 0.01) compared to the T-RO model and by 0.20 (P = 0.01) compared to PT-E. CONCLUSION:The CT-based PT-RO model can effectively predict the ER of HCC and is more efficient than the T-RO model and the conventional imaging feature PT-E.

Project description:ImportanceAdrenocortical carcinoma (ACC) is a rare but aggressive endocrine tumor, and the prognostic factors associated with long-term outcomes after surgical resection remain poorly defined.ObjectivesTo define clinicopathological variables associated with recurrence-free survival (RFS) and overall survival (OS) after curative surgical resection of ACC and to propose nomograms for individual risk prediction.Design, setting, and participantsNomograms to predict RFS and OS after surgical resection of ACC were proposed using a multi-institutional cohort of patients who underwent curative-intent surgery for ACC at 13 major institutions in the United States between March 17, 1994, and December 22, 2014. The dates of our study analysis were April 15, 2015, to May 12, 2015.Main outcomes and measuresThe discriminative ability and calibration of the nomograms to predict RFS and OS were tested using C statistics, calibration plots, and Kaplan-Meier curves.ResultsIn total, 148 patients who underwent surgery for ACC were included in the study. The median patient age was 53 years, and 65.5% (97 of 148) of the patients were female. One-third of the patients (35.1% [52 of 148]) had a functional tumor, and the median tumor size was 11.2 cm. Most patients (77.7% [115 of 148]) underwent R0 resection, and 8.8% (13 of 148) of the patients had N1 disease. Using backward stepwise selection of clinically important variables with the Akaike information criterion, the following variables were incorporated in the prediction of RFS: tumor size of at least 12 cm (hazard ratio [HR], 3.00; 95% CI, 1.63-5.70; P < .001), positive nodal status (HR, 4.78; 95% CI, 1.47-15.50; P = .01), stage III/IV (HR, 1.80; 95% CI, 0.95-3.39; P = .07), cortisol-secreting tumor (HR, 2.38; 95% CI, 1.27-4.48; P = .01), and capsular invasion (HR, 1.96; 95% CI, 1.02-3.74; P = .04). Factors selected as predicting OS were tumor size of at least 12 cm (HR, 1.78; 95% CI, 1.00-3.17; P = .05), positive nodal status (HR, 5.89; 95% CI, 2.05-16.87; P = .001), and R1 margin (HR, 2.83; 95% CI, 1.51-5.30; P = .001). The discriminative ability and calibration of the nomograms revealed good predictive ability as indicated by the C statistics (0.74 for RFS and 0.70 for OS).Conclusions and relevanceIndependent predictors of survival and recurrence risk after curative-intent surgery for ACC were selected to create nomograms predicting RFS and OS. The nomograms were able to stratify patients into prognostic groups and performed well on internal validation.

Dataset Information

Level of hepatitis B surface antigen might serve as a new marker to predict hepatocellular carcinoma recurrence following curative resection in patients with low viral load.

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Level of hepatitis B surface antigen might serve as a new marker to predict hepatocellular carcinoma recurrence following curative resection in patients with low viral load.

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