title: Improving noninvasive methods of assessing liver fibrosis in patients with hepatitis C virus/human immunodeficiency virus co-infection.
abstract: OBJECTIVE
  Liver fibrosis is a significant concern for patients with hepatitis C virus/human immunodeficiency virus co-infection. Fibrosis staging by biopsy is accurate, but costly and invasive. Several fibrosis prediction models using noninvasive biomarkers have been developed but are suboptimal in co-infected patients. We compared results from different staging models and ordinal regression with biopsy data.
  
  
  METHODS
  Data from the Adult Acquired Immune Deficiency Syndrome Clinical Trials Group protocol A5178 were used to evaluate 5 models of fibrosis staging; areas under receiver-operator characteristic curves (AUROC) were assessed. Individual covariates were assessed with univariable regression and then entered into an ordinal logistic regression model from which a stage-wise index was developed.
  
  
  RESULTS
  Data from 173 patients were evaluated; 85% were on antiretroviral therapy, 31.2% had severe fibrosis (F3/F4), and 14% had cirrhosis (F4). Differences in CD4+ cell and platelets counts and international normalized ratio values were observed between those with and without F3/F4. Among existing models, the FIB-4 index ([age x AST])/[platelet count x (ALT)(1/2)]) performed best, with 88% specificity for F4 and greater than 86% negative predictive values for F3/F4, although AUROC values were low (0.56 +/- 0.03 for F3/F4). By using patients' demographic, clinical, and laboratory data, the ordinal regression model outperformed others, with an AUROC of 0.85 (standard error, 0.03) for predicting stage F3/F4 and 0.89 (standard error, 0.05) for stage 3 alone.
  
  
  CONCLUSIONS
  Current noninvasive methods of fibrosis assessment have poor discriminatory capacity in hepatitis C virus/human immunodeficiency virus co-infected patients. Ordinal regression analysis outperformed other noninvasive fibrosis prediction models. Longitudinal studies with paired biopsies will assist in refining the Ordinal Regression Index.
authors.affiliation: Infectious Disease Epidemiology, Merck and Co, Inc, North Wales, Pennsylvania 19545-1099, USA. Norah_shire@merck.com
authors.forename: Norah J
authors.initials: NJ
authors.lastname: Shire
authors.forename: Marepalli B
authors.initials: MB
authors.lastname: Rao
authors.forename: Paul
authors.initials: P
authors.lastname: Succop
authors.forename: C Ralph
authors.initials: CR
authors.lastname: Buncher
authors.forename: Janet A
authors.initials: JA
authors.lastname: Andersen
authors.forename: Adeel A
authors.initials: AA
authors.lastname: Butt
authors.forename: Raymond T
authors.initials: RT
authors.lastname: Chung
authors.forename: Kenneth E
authors.initials: KE
authors.lastname: Sherman
mesh_terms: D000328:Adult; D000368:Aged; D044963:Biopsy, Fine-Needle; D003938:Diagnostic Techniques, Digestive System; D005260:Female; D015658:HIV Infections / Q000150:complications*; D019698:Hepatitis C, Chronic / Q000150:complications*; D006801:Humans; D008103:Liver Cirrhosis / Q000175:diagnosis*; D008297:Male; D008875:Middle Aged; D015233:Models, Statistical; D011237:Predictive Value of Tests; D012680:Sensitivity and Specificity; D012720:Severity of Illness Index