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Multivariate discriminant analysis of biochemical parameters for the differentiation of clinically confounding liver diseases

Clin Chim Acta. 1997 Jan 3;257(1):41-58. doi: 10.1016/s0009-8981(96)06433-9.

Abstract

We describe a series of studies on the contribution of laboratory medicine to the differential diagnosis of clinically confounding diseases in the field of chronic hepatobiliary diseases. Ascitic cholesterol and lactate dehydrogenase (LD), selected by multivariate discriminant analysis (MDA) from a multitude of serum and ascitic analytes, correctly classified 100% of patients with malignant ascites or non-malignant ascites. In addition, ascitic pseudouridine differentiated hepatocarcinoma (HC) from cirrhotic ascites with a diagnostic effectiveness (overall discrimination power) of 90%. A panel of analytes constituted by serum gamma-glutamyltransferase (GGT), the GGT isoenzyme complexed with low- and very low-density lipoprotein, aspartate aminotransferase, copper, hepatic alkaline phosphatase (AP), the LD-5 isoenzyme and alpha-fetoprotein (AFP), selected by the MDA, correctly classified 93% of about 200 cases of cirrhosis or HC. Finally, MDA also identified an equation, based on serum values of the LD-4/LD-5 and carcinoembryonic antigen/AFP ratios, AP and iron that correctly classified 96% of HC or secondary liver neoplasia cases in 100 patients. This approach based on panels of analytes selected by a sophisticated statistical analysis is a rapid and non-invasive contribution to the differential diagnosis of chronic liver disease including neoplasia.

Publication types

  • Research Support, Non-U.S. Gov't
  • Review

MeSH terms

  • Chemistry, Clinical / methods*
  • Chemistry, Clinical / statistics & numerical data*
  • Diagnosis, Differential
  • Discriminant Analysis
  • Humans
  • Liver Diseases / diagnosis*
  • Multivariate Analysis