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

• Published in: OncoTargets and therapy Vol. 6; no. default; pp. 1463 - 1469
• Main Authors: Kim, Do Young, Song, Ki Jun, Kim, Seung Up, Yoo, Eun Jin, Park, Jun Yong, Ahn, Sang Hoon, Han, Kwang-Hyub
• Format: Journal Article
• Language: English
• Published: New Zealand Dove Medical Press Limited 01.01.2013; Taylor & Francis Ltd; Dove Press; Dove Medical Press
• Subjects: Complications and side effects; Confidence intervals; Diagnostic imaging; Hepatitis; Hepatitis B; hepatocellular carcinoma; Hepatoma; Interferon; Liver cancer; Methods; Original Research; prediction; Risk factors; transient elastography; prediction; transient elastography; hepatitis B; hepatocellular carcinoma
• ISSN: 1178-6930; 1178-6930
• DOI: 10.2147/OTT.S51986

The purpose of this study was to develop and validate a novel transient elastography-based predictive model for occurrence of hepatocellular carcinoma (HCC). 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. 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). This novel model accurately estimated the risk of HCC occurrence in patients with chronic hepatitis B.