title: Improving estimation of liver fibrosis using combination and newer noninvasive biomarker scoring systems in hepatitis C-infected haemophilia patients.
abstract: Non-invasive biomarkers have gained popularity for estimating fibrosis stage. In our hepatitis C-infected haemophilia patients, Fibrotest (FT) correctly identified clinically advanced or minimal liver disease. More accurate tests, like the FibroMeters, have recently been validated. The aim of the study was to improve the estimation of liver fibrosis in hepatitis C-infected haemophiliacs using a combination of biomarkers and FibroMeters. One hundred and thirty-two hepatitis C-infected haemophilia patients (124 male, mean age: 39+/-14 years) were evaluated. The following biomarkers were used: FT, AST-to-platelet ratio index (APRI), Forns index, hyaluronic acid and FibroMeter. We applied a published algorithm suggesting that if FT is in concordance with APRI and/or Forns score, then the FT concurs with liver biopsy for estimation of fibrosis. Concordance of three or more biomarkers was present in 43.2% (57/132) of the patients. This high discordance rate was mainly because of indeterminate scores. Significant fibrosis (F2-F4) was estimated at 34.8% (46/132) and 37.9% (50/132) by the FT and FibroMeter respectively. The discordance rate between the FT and FibroMeter was 16.7% (22/132), (P<0.01 vs. other biomarkers). Using the algorithm, liver histology could be confidently estimated in 69.7% (92/132) of the patients. Concordance between the FT and FibroMeter in those patients who met the terms of the algorithm was 90.2% (83/92). Discordance between biomarkers is significant, and is mainly because of biomarkers with indeterminate results. The concordance rate between FT and FibroMeter is higher compared with the other biomarkers. Practical combination of tests may potentially limit the need of liver biopsy in the majority of haemophilia patients.
authors.affiliation: Department of Gastroenterology and Hepatology, Sheba Medical Center, Tel-Hashomer, Israel. yaakov@sheba.health.gov.il
authors.forename: Y
authors.initials: Y
authors.lastname: Maor
authors.forename: P
authors.initials: P
authors.lastname: Calès
authors.forename: D
authors.initials: D
authors.lastname: Bashari
authors.forename: G
authors.initials: G
authors.lastname: Kenet
authors.forename: A
authors.initials: A
authors.lastname: Lubetsky
authors.forename: J
authors.initials: J
authors.lastname: Luboshitz
authors.forename: J M
authors.initials: JM
authors.lastname: Schapiro
authors.forename: G
authors.initials: G
authors.lastname: Pénaranda
authors.forename: S
authors.initials: S
authors.lastname: Bar-Meir
authors.forename: U
authors.initials: U
authors.lastname: Martinowitz
authors.forename: P
authors.initials: P
authors.lastname: Halfon
mesh_terms: D000328:Adult; D000465:Algorithms; D015415:Biomarkers / Q000032:analysis*; D018450:Disease Progression; D004812:Epidemiologic Methods; D006467:Hemophilia A / Q000150:complications*; D019698:Hepatitis C, Chronic / Q000097:blood*; D006801:Humans; D008103:Liver Cirrhosis / Q000175:diagnosis* / Q000821:virology; D008297:Male; D011237:Predictive Value of Tests; D019562:Viral Load
chemical_list: D015415:Biomarkers