title: Development of a simple noninvasive index to predict significant fibrosis in patients with HIV/HCV coinfection.
abstract: Liver biopsy remains the gold standard in the assessment of severity of liver disease. Noninvasive tests have gained popularity to predict histology in view of the associated risks of biopsy. However, many models include tests not readily available, and there are limited data from patients with HIV/hepatitis C virus (HCV) coinfection. We aimed to develop a model using routine tests to predict liver fibrosis in patients with HIV/HCV coinfection. A retrospective analysis of liver histology was performed in 832 patients. Liver fibrosis was assessed via Ishak score; patients were categorized as 0-1, 2-3, or 4-6 and were randomly assigned to training (n = 555) or validation (n = 277) sets. Multivariate logistic regression analysis revealed that platelet count (PLT), age, AST, and INR were significantly associated with fibrosis. Additional analysis revealed PLT, age, AST, and ALT as an alternative model. Based on this, a simple index (FIB-4) was developed: age ([yr] x AST [U/L]) / ((PLT [10(9)/L]) x (ALT [U/L])(1/2)). The AUROC of the index was 0.765 for differentiation between Ishak stage 0-3 and 4-6. At a cutoff of <1.45 in the validation set, the negative predictive value to exclude advanced fibrosis (stage 4-6) was 90% with a sensitivity of 70%. A cutoff of >3.25 had a positive predictive value of 65% and a specificity of 97%. Using these cutoffs, 87% of the 198 patients with FIB-4 values outside 1.45-3.25 would be correctly classified, and liver biopsy could be avoided in 71% of the validation group. In conclusion, noninvasive tests can accurately predict hepatic fibrosis and may reduce the need for liver biopsy in the majority of HIV/HCV-coinfected patients.
authors.affiliation: Section of Hepatology, Virginia Commonwealth University Health System, Richmond, VA 23298-0341, USA. rksterli@hsc.vcu.edu
authors.forename: Richard K
authors.initials: RK
authors.lastname: Sterling
authors.forename: Eduardo
authors.initials: E
authors.lastname: Lissen
authors.forename: Nathan
authors.initials: N
authors.lastname: Clumeck
authors.forename: Ricard
authors.initials: R
authors.lastname: Sola
authors.forename: Mendes Cassia
authors.initials: MC
authors.lastname: Correa
authors.forename: Julio
authors.initials: J
authors.lastname: Montaner
authors.forename: Mark
authors.initials: M
authors.lastname: S Sulkowski
authors.forename: Francesca J
authors.initials: FJ
authors.lastname: Torriani
authors.forename: Doug T
authors.initials: DT
authors.lastname: Dieterich
authors.forename: David L
authors.initials: DL
authors.lastname: Thomas
authors.forename: Diethelm
authors.initials: D
authors.lastname: Messinger
authors.forename: Mark
authors.initials: M
authors.lastname: Nelson
mesh_terms: D000367:Age Factors; D001707:Biopsy, Needle; D001774:Blood Chemical Analysis; D015331:Cohort Studies; D003955:Diagnostic Tests, Routine / Q000379:methods*; D018450:Disease Progression; D005260:Female; D015658:HIV Infections / Q000175:diagnosis* / Q000453:epidemiology; D019698:Hepatitis C, Chronic / Q000175:diagnosis* / Q000453:epidemiology; D006801:Humans; D007150:Immunohistochemistry; D008103:Liver Cirrhosis / Q000175:diagnosis* / Q000453:epidemiology / Q000821:virology; D008111:Liver Function Tests; D016015:Logistic Models; D008297:Male; D011237:Predictive Value of Tests; D011336:Probability; D011379:Prognosis; D012372:ROC Curve; D015203:Reproducibility of Results; D012189:Retrospective Studies; D018570:Risk Assessment; D012680:Sensitivity and Specificity; D012720:Severity of Illness Index; D012737:Sex Factors