title: Non invasive fibrosis biomarkers reduce but not substitute the need for liver biopsy.
abstract: Chronic liver diseases are very common worldwide, particularly those linked to viral hepatitis and to alcoholic and non-alcoholic fatty liver. Their natural history is variable and long-term evolution differs in individual patients. Optimised clinical management of compensated chronic liver diseases requires precise definition of the stage of liver fibrosis, the main determinant of prognosis and of most therapeutic decisions. Liver biopsy is the gold standard for assessment of hepatic fibrosis. However, it is invasive with possible complications, costly and prone to sampling errors. Many non-invasive markers of liver fibrosis have been recently proposed and assessed in the clinical setting as surrogates of liver biopsy. Direct markers are based on biochemical parameters directly linked to fibrogenesis while indirect markers use simple or more sophisticated parameters that correlate with liver fibrosis stages. Non-invasive markers of liver fibrosis have been tested in different forms of chronic liver disease and showed variable diagnostic performance, but accuracy rarely was above 75%-80%. Better results were obtained when markers were combined. On this line, we have recently proposed a set of algorithms that combine sequentially indirect non-invasive markers of liver fibrosis, reaching 90%-95% diagnostic accuracy with significant reduction in the need for liver biopsy. Based on available evidence, it can be anticipated that non-invasive markers of liver fibrosis and their combined use will soon become a most useful tool in the clinical management of many forms of chronic liver disease. However, their implementation is expected to reduce, but not to completely eliminate, the need for liver biopsy.
authors.affiliation: Department of Clinical and Experimental Medicine, University of Padova, Italy.
authors.forename: Giada
authors.initials: G
authors.lastname: Sebastiani
authors.forename: Alfredo
authors.initials: A
authors.lastname: Alberti
mesh_terms: D000465:Algorithms; D015415:Biomarkers / Q000032:analysis*; D001706:Biopsy / Q000706:statistics & numerical data*; D018450:Disease Progression; D006526:Hepatitis C / Q000150:complications; D006801:Humans; D008099:Liver / Q000737:chemistry* / Q000473:pathology*; D008103:Liver Cirrhosis / Q000175:diagnosis* / Q000235:genetics / Q000473:pathology* / Q000503:physiopathology; D011110:Polymorphism, Genetic; D011379:Prognosis; D012720:Severity of Illness Index
chemical_list: D015415:Biomarkers