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A New Model Using Routinely Available Clinical Parameters to Predict Significant Liver Fibrosis in Chronic Hepatitis B

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  • Wai-Kay Seto
  • Chun-Fan Lee
  • Ching-Lung Lai
  • Philip P C Ip
  • Daniel Yee-Tak Fong
  • James Fung
  • Danny Ka-Ho Wong
  • Man-Fung Yuen

Abstract

Objective: We developed a predictive model for significant fibrosis in chronic hepatitis B (CHB) based on routinely available clinical parameters. Methods: 237 treatment-naïve CHB patients [58.4% hepatitis B e antigen (HBeAg)-positive] who had undergone liver biopsy were randomly divided into two cohorts: training group (n = 108) and validation group (n = 129). Liver histology was assessed for fibrosis. All common demographics, viral serology, viral load and liver biochemistry were analyzed. Results: Based on 12 available clinical parameters (age, sex, HBeAg status, HBV DNA, platelet, albumin, bilirubin, ALT, AST, ALP, GGT and AFP), a model to predict significant liver fibrosis (Ishak fibrosis score ≥3) was derived using the five best parameters (age, ALP, AST, AFP and platelet). Using the formula log(index+1) = 0.025+0.0031(age)+0.1483 log(ALP)+0.004 log(AST)+0.0908 log(AFP+1)−0.028 log(platelet), the PAPAS (Platelet/Age/Phosphatase/AFP/AST) index predicts significant fibrosis with an area under the receiving operating characteristics (AUROC) curve of 0.776 [0.797 for patients with ALT

Suggested Citation

  • Wai-Kay Seto & Chun-Fan Lee & Ching-Lung Lai & Philip P C Ip & Daniel Yee-Tak Fong & James Fung & Danny Ka-Ho Wong & Man-Fung Yuen, 2011. "A New Model Using Routinely Available Clinical Parameters to Predict Significant Liver Fibrosis in Chronic Hepatitis B," PLOS ONE, Public Library of Science, vol. 6(8), pages 1-7, August.
    • Handle: RePEc:plo:pone00:0023077
    DOI: 10.1371/journal.pone.0023077
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    References listed on IDEAS

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    1. Mee Young Park & Trevor Hastie, 2007. "L1‐regularization path algorithm for generalized linear models," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 69(4), pages 659-677, September.
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    Cited by:

    1. Xue-Ying Xu & Hong Kong & Rui-Xiang Song & Yu-Han Zhai & Xiao-Fei Wu & Wen-Si Ai & Hong-Bo Liu, 2014. "The Effectiveness of Noninvasive Biomarkers to Predict Hepatitis B-Related Significant Fibrosis and Cirrhosis: A Systematic Review and Meta-Analysis of Diagnostic Test Accuracy," PLOS ONE, Public Library of Science, vol. 9(6), pages 1-16, June.
    2. Ying Wang & Zhicheng Du & Wayne R. Lawrence & Yun Huang & Yu Deng & Yuantao Hao, 2019. "Predicting Hepatitis B Virus Infection Based on Health Examination Data of Community Population," IJERPH, MDPI, vol. 16(23), pages 1-13, December.

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