title: An evaluation of the potential cost-effectiveness of non-invasive testing strategies in the diagnosis of significant liver fibrosis.
abstract: OBJECTIVE
  To assess the clinical and economic outcomes of non-invasive testing strategies in the diagnosis of significant liver fibrosis (Metavir score >or= 2) compared with liver biopsy.
  
  
  METHODS
  We developed a decision analytic model of non-invasive testing strategies in a hypothetical patient population with genotype 1 hepatitis C virus infection, with no contraindications to liver biopsy. The testing strategies included a testing algorithm using the Fibrosure test, a non-invasive measure of fibrosis, followed by liver biopsy for patients with indeterminate results, Fibrospect II, and Fibroscan. The primary outcomes were sensitivity, specificity, diagnostic accuracy (true positive + true negatives/total patients), and costs, evaluated from the health-care payer perspective.
  
  
  RESULTS
  The testing algorithm using Fibrosure was the most accurate non-invasive strategy with a sensitivity, specificity, and overall accuracy of 84%, 87%, and 86%, respectively. In comparison with liver biopsy alone, there was a cost savings of approximately $770/person with the Fibrosure testing algorithm, but a net decrease in accuracy of 14%. Fibrospect II and Fibroscan had poorer accuracy (decreases of 12% and 4%, respectively) and lower costs (-$138 and -$357, respectively) compared with the Fibrosure algorithm. In uncertainty analyses in which biopsy sampling error was considered, the Fibrosure algorithm remained consistently less accurate (5-14% decrease).
  
  
  CONCLUSIONS
  The results of our study suggest that compared with liver biopsy, non-invasive testing algorithms can result in short-term cost savings, but the consequences of misdiagnosis in terms of health outcomes and treatment costs might outweigh the short-term gains in cost and convenience.
authors.affiliation: Institute for Public Health Genetics, School of Public Health and Community Medicine, University of Washington, Washington 98195, USA.
authors.forename: Josh J
authors.initials: JJ
authors.lastname: Carlson
authors.forename: Kris V
authors.initials: KV
authors.lastname: Kowdley
authors.forename: Sean D
authors.initials: SD
authors.lastname: Sullivan
authors.forename: Scott D
authors.initials: SD
authors.lastname: Ramsey
authors.forename: David L
authors.initials: DL
authors.lastname: Veenstra
mesh_terms: D000465:Algorithms; D015415:Biomarkers / Q000097:blood*; D001706:Biopsy / Q000191:economics*; D001774:Blood Chemical Analysis / Q000191:economics*; D017046:Cost Savings; D003362:Cost-Benefit Analysis; D020000:Decision Support Systems, Clinical / Q000191:economics*; D003951:Diagnostic Errors / Q000191:economics; D005838:Genotype; D017048:Health Care Costs; D016174:Hepacivirus / Q000235:genetics; D019698:Hepatitis C, Chronic / Q000097:blood / Q000150:complications* / Q000473:pathology; D006801:Humans; D008103:Liver Cirrhosis / Q000097:blood / Q000175:diagnosis* / Q000473:pathology / Q000821:virology; D018803:Models, Economic; D011237:Predictive Value of Tests; D012680:Sensitivity and Specificity; D012720:Severity of Illness Index
chemical_list: D015415:Biomarkers