title: Prediction of liver fibrosis in human immunodeficiency virus/hepatitis C virus coinfected patients by simple non-invasive indexes.
abstract: BACKGROUND
  Liver biopsy is an invasive technique with associated major complications. There is no information on the validity of five non-invasive indexes based on routinely available parameters, estimated and validated in hepatitis C virus (HCV) monoinfected patients, in human immunodeficiency virus (HIV)/HCV coinfected patients.
  
  
  OBJECTIVE
  To validate these predictive models of liver fibrosis in HIV/HCV coinfected patients.
  
  
  METHODS
  A total of 357 (90%) of 398 patients from five hospitals were investigated, who underwent liver biopsy and who had complete data to validate all of the models considered.
  
  
  METHODS
  The predictive accuracy of the indexes was tested by measuring areas under the receiver operating characteristic curves. Diagnostic accuracy was calculated by estimating sensitivity, specificity, and positive (PPV) and negative (NPV) predictive values.
  
  
  RESULTS
  The models performed better when liver biopsies>or=15 mm were used as reference. In this setting, the Forns and Wai indexes, models aimed at discriminating significant fibrosis, showed PPV of 94% and 87%, respectively. Using these models, 27-34% of patients could benefit from exclusion of liver biopsy. If both models were applied sequentially, 41% of liver biopsies could be spared. The indexes aimed at predicting cirrhosis achieved NPV of up to 100%. However, they showed very low PPV.
  
  
  CONCLUSIONS
  The diagnostic accuracy of these models was lower in HIV/HCV coinfected patients than in the validation studies performed in HCV monoinfected patients. However, simple fibrosis tests may render liver biopsy unnecessary in deciding anti-HCV treatment in over one third of patients with HIV infection and chronic hepatitis C.
authors.affiliation: Unidad de Enfermedades Infecciosas, Hospital Universitario de Valme, Ctra de Cádiz s/n, 41014 Seville, Spain.
authors.forename: J
authors.initials: J
authors.lastname: Macías
authors.forename: J A
authors.initials: JA
authors.lastname: Girón-González
authors.forename: M
authors.initials: M
authors.lastname: González-Serrano
authors.forename: D
authors.initials: D
authors.lastname: Merino
authors.forename: P
authors.initials: P
authors.lastname: Cano
authors.forename: J A
authors.initials: JA
authors.lastname: Mira
authors.forename: A
authors.initials: A
authors.lastname: Arizcorreta-Yarza
authors.forename: J
authors.initials: J
authors.lastname: Ruíz-Morales
authors.forename: J M
authors.initials: JM
authors.lastname: Lomas-Cabeza
authors.forename: J A
authors.initials: JA
authors.lastname: García-García
authors.forename: J E
authors.initials: JE
authors.lastname: Corzo
authors.forename: J A
authors.initials: JA
authors.lastname: Pineda
mesh_terms: D000328:Adult; D000410:Alanine Transaminase / Q000097:blood; D001219:Aspartate Aminotransferases / Q000097:blood; D015415:Biomarkers / Q000097:blood; D004812:Epidemiologic Methods; D005260:Female; D015658:HIV Infections / Q000150:complications*; D019698:Hepatitis C, Chronic / Q000150:complications*; D006801:Humans; D008103:Liver Cirrhosis / Q000175:diagnosis* / Q000188:drug therapy / Q000821:virology*; D008297:Male; D018579:Patient Selection; D010976:Platelet Count
chemical_list: D015415:Biomarkers; D001219:Aspartate Aminotransferases; D000410:Alanine Transaminase