Stepwise combination algorithms of non-invasive markers to diagnose significant fibrosis in chronic hepatitis C

J Hepatol. 2006 Apr;44(4):686-93. doi: 10.1016/j.jhep.2006.01.007. Epub 2006 Feb 8.

Abstract

Background/aims: In chronic hepatitis C, biopsy is the gold standard for assessment of liver fibrosis. Non-invasive markers have been proposed but their use is limited by diagnostic accuracy. Our aim was to increase the diagnostic performance of non-invasive markers of liver fibrosis by combining them in sequential algorithms.

Methods: One hundred and ninety patients with chronic hepatitis C were evaluated for AST to platelets ratio (APRI), Forns' index and Fibrotest at the time of liver biopsy and stepwise combination algorithms were developed and validated prospectively in 100 additional patients.

Results: Three algorithms were developed: (1) significant fibrosis (F>or=2 by METAVIR) was identified with high diagnostic performance (>94% accuracy) using APRI as screening test, followed by Fibrotest in APRI non-classified cases and restricting liver biopsy to patients classified F0-F1 by non-invasive tests. (2) A slightly modified algorithm had similar performance when applied to hepatitis C carriers with normal ALT. (3) Identification of cirrhosis (95% accuracy) was achieved using a dedicated algorithm with different cut-off, reducing by 60-70% the liver biopsies needed.

Conclusions: Stepwise combination of non-invasive markers of liver fibrosis improves the diagnostic performance in chronic hepatitis C. Need for liver biopsy is reduced by 50-70% but cannot be completely avoided.

Publication types

  • Comparative Study

MeSH terms

  • Adult
  • Algorithms*
  • Aspartate Aminotransferases / blood
  • Biomarkers
  • Biopsy
  • Blood Platelets / enzymology
  • Female
  • Fibrosis / blood
  • Fibrosis / diagnosis*
  • Fibrosis / etiology*
  • Fibrosis / pathology
  • Hepatitis C, Chronic / blood
  • Hepatitis C, Chronic / complications*
  • Hepatitis C, Chronic / pathology
  • Humans
  • Liver / pathology
  • Male
  • Middle Aged
  • Predictive Value of Tests
  • Sensitivity and Specificity

Substances

  • Biomarkers
  • Aspartate Aminotransferases