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Transient elastography-based risk estimation of hepatitis B virus-related occurrence of hepatocellular carcinoma: development and validation of a predictive model

Authors Kim DY, Song KJ, Kim SU, Yoo EJ, Park JY, Ahn SH, Han K

Received 24 July 2013

Accepted for publication 19 September 2013

Published 16 October 2013 Volume 2013:6 Pages 1463—1469

DOI https://doi.org/10.2147/OTT.S51986

Checked for plagiarism Yes

Review by Single anonymous peer review

Peer reviewer comments 3


Do Young Kim,1,2,4,* Ki Jun Song,3,4,* Seung Up Kim,1,2,4 Eun Jin Yoo,1 Jun Yong Park,1,2,4 Sang Hoon Ahn,1,2,4 Kwang-Hyub Han1,2,4

1Department of Internal Medicine, 2Institute of Gastroenterology, 3Department of Biostatistics, Yonsei University College of Medicine, 4Liver Cirrhosis Clinical Research Center, Seoul, Korea

*These authors contributed equally to this work

Background: The purpose of this study was to develop and validate a novel transient elastography-based predictive model for occurrence of hepatocellular carcinoma (HCC).
Methods: A total of 1,250 patients with chronic hepatitis B and baseline liver stiffness values were recruited between May 2005 and December 2007. The predictive model for HCC occurrence was constructed based on a Cox proportional hazards model. We estimated baseline disease-free probabilities at 3 years. Discrimination and calibration were used to validate the model.
Results: HCC occurred in 56 patients during a median follow-up of 30.7 months. Multivariate analysis revealed that age, male gender, and liver stiffness values were independent predictors of HCC (all P<0.05), whereas hepatitis B virus DNA ≥20,000 IU/L showed borderline statistical significance (P=0.0659). We developed a predictive model for HCC using these four variables, which showed good discrimination capability, with an area under the receiver operating characteristic curve (AUROC) of 0.806 (95% confidence interval 0.738–0.874). We used the bootstrap method to assess discrimination. The AUROC remained largely unchanged between iterations, with an average value of 0.802 (95% confidence interval 0.791–0.812). The predicted risk of occurrence of HCC calibrated well with the observed risk, with a correlation coefficient of 0.905 (P<0.001).
Conclusion: This novel model accurately estimated the risk of HCC occurrence in patients with chronic hepatitis B.

Keywords: hepatocellular carcinoma, transient elastography, prediction, hepatitis B

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