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

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Abstract

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.

Original languageEnglish
Pages (from-to)1463-1469
Number of pages7
JournalOncoTargets and Therapy
Volume6
DOIs
Publication statusPublished - 2013 Oct 28

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Elasticity Imaging Techniques
Hepatitis B virus
Hepatocellular Carcinoma
Chronic Hepatitis B
ROC Curve
Confidence Intervals
Liver
Proportional Hazards Models
Calibration
Multivariate Analysis
DNA

All Science Journal Classification (ASJC) codes

  • Oncology
  • Pharmacology (medical)

Cite this

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title = "Transient elastography-based risk estimation of hepatitis B virus-related occurrence of hepatocellular carcinoma: Development and validation of a predictive model",
abstract = "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.",
author = "Kim, {Do Young} and Song, {Ki Jun} and Kim, {Seung Up} and Yoo, {Eun Jin} and Park, {Jun Yong} and Ahn, {Sang Hoon} and Han, {Kwang Hyub}",
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T1 - Transient elastography-based risk estimation of hepatitis B virus-related occurrence of hepatocellular carcinoma

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AU - Kim, Do Young

AU - Song, Ki Jun

AU - Kim, Seung Up

AU - Yoo, Eun Jin

AU - Park, Jun Yong

AU - Ahn, Sang Hoon

AU - Han, Kwang Hyub

PY - 2013/10/28

Y1 - 2013/10/28

N2 - 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.

AB - 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.

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