Development of a non‐invasive algorithm with transient elastography (Fibroscan) and serum test formula for advanced liver fibrosis in chronic hepatitis B

• Published in: Alimentary pharmacology & therapeutics Vol. 31; no. 10; pp. 1095 - 1103
• Main Authors: WONG, G. L. H., WONG, V. W. S., CHOI, P. C. L., CHAN, A. W. H., CHAN, H. L. Y.
• Format: Journal Article
• Language: English
• Published: Oxford, UK Blackwell Publishing Ltd 01.05.2010; Blackwell
• Subjects: Adolescent; Adult; Aged; Aged, 80 and over; Alanine Transaminase - blood; Algorithms; Area Under Curve; Biological and medical sciences; Digestive system; Elasticity Imaging Techniques; Female; Gastroenterology. Liver. Pancreas. Abdomen; Hepatitis B, Chronic - pathology; Human viral diseases; Humans; Infectious diseases; Liver Cirrhosis - diagnosis; Liver Cirrhosis - pathology; Liver. Biliary tract. Portal circulation. Exocrine pancreas; Male; Medical sciences; Middle Aged; Other diseases. Semiology; Pharmacology. Drug treatments; Prospective Studies; Sensitivity and Specificity; Viral diseases; Viral hepatitis; Young Adult; Hepatic fibrosis; Biological fluid; Hepatic disease; Algorithm; Infection; Viral hepatitis B; Transient elastography; Viral disease; Non invasive method; Development; Medical imagery; Digestive diseases; Advanced stage; Serum
• ISSN: 0269-2813; 1365-2036; 1365-2036
• DOI: 10.1111/j.1365-2036.2010.04276.x

Aliment Pharmacol Ther 31, 1095–1103 Summary Background  Non‐invasive assessments of liver fibrosis in chronic hepatitis B were well established. Aim  To develop a combined algorithm of liver stiffness measurement (LSM) and serum test formula to predict advanced liver fibrosis in chronic hepatitis B. Methods  We reported an alanine aminotransferase (AST)‐based LSM algorithm for liver fibrosis in 156 chronic hepatitis B patients, which formed the training cohort to evaluate the performance of APRI (AST‐to‐platelet‐ratio‐index), Forns index, FIB‐4 and Fibroindex against liver histology. The best combined LSM‐serum formula algorithm would be validated in another cohort of 82 chronic hepatitis B patients. Results  In the training cohort, LSM has the best performance of diagnosing advanced (≥F3) fibrosis [area under the receiver operating characteristics curve (AUROC) 0.88, 95% confidence interval (CI) 0.85–0.91], while Forns index has the best performance among the various serum test formulae (AUROC 0.70, 95% CI 0.62–0.78). In the combined algorithm, low LSM or low Forns index could be used to exclude advanced fibrosis as both of them had high sensitivity (>90%). To confirm advanced fibrosis, agreement between high LSM and high Forns index could improve the specificity (from 99% to 100% and from 87% to 98% in the training and validation cohorts respectively). Conclusion  A combined LSM–Forns algorithm can improve the accuracy to predict advanced liver fibrosis in chronic hepatitis B.