title: Assessing liver fibrosis with serum marker models.
abstract: Chronic liver disease is characterised by liver fibrosis, which may lead to cirrhosis. Conventional serum-based liver function tests do not give information on either the presence or the rate of progress of liver fibrosis. The reference diagnostic test to detect fibrosis is liver biopsy, a procedure subject to various limitations, including risk of patient injury and sampling error. Serum markers have been evaluated for the determination of fibrosis either singly or combined as a panel of markers, however diagnostic accuracy is greatest in studies using a panel together with an algorithm, which generates a predictive score. Serum marker models, especially those targeted at hepatitis C, have multiplied in spectacular fashion over the last five years, with most models regularly achieving a median area under the receiver operating characteristic curve (ROCC) of 0.80 versus liver biopsy. Five years after publication of the first major serum marker model, the first study to document clinical outcomes reported that applying the model to hepatitis C patients improved prediction of decompensated cirrhosis and survival compared to liver biopsy. An obstacle to widespread adoption of serum marker models has been the lack of uniform performance indicators, such as diagnostic odds ratios and likelihood ratios. At present, serum marker models are not considered sufficiently reliable to replace liver biopsy in patients with chronic liver disease. However with continued evaluation in parallel with liver biopsy rapid advances are being made.
authors.affiliation: Department of Clinical Biochemistry, PathWest Laboratory Medicine, Queen Elizabeth II Medical Centre, The University of Western Australia, Nedlands, WA 6009 Australia. ric.rossi@health.wa.gov.au
authors.forename: Enrico
authors.initials: E
authors.lastname: Rossi
authors.forename: Leon A
authors.initials: LA
authors.lastname: Adams
authors.forename: Max
authors.initials: M
authors.lastname: Bulsara
authors.forename: Gary P
authors.initials: GP
authors.lastname: Jeffrey