title: Enhanced liver fibrosis test can predict clinical outcomes in patients with chronic liver disease.
abstract: BACKGROUND
  Clinicians use fibrosis in a liver biopsy to predict clinical outcomes of chronic liver disease. The performance of non-invasive tests has been evaluated against histological assessment of fibrosis but use of clinical outcomes as the reference standard would be ideal. The enhanced liver fibrosis (ELF) test was derived and validated in a large cohort of patients and shown to have high diagnostic accuracy (area under the curve (AUC)=0.80 95% CI 0.76 to 0.85) in identification of significant fibrosis on biopsy.
  
  
  OBJECTIVE
  To evaluate ELF performance in predicting clinical outcomes by following up the original ELF cohort.
  
  
  METHODS
  Patients recruited to the ELF study at seven English centres were followed up for liver morbidity and mortality by examination of clinical data. Defaulting/discharged patients were followed up by family practitioner questionnaires. Primary outcome measure was liver-related morbidity/liver-related death.
  
  
  RESULTS
  457 patients were followed up (median 7 years), with ascertainment of clinical status in 92%. There were 61 liver-related outcomes (39 deaths). Survival analysis showed that the ELF score predicts liver outcomes, with people having the highest ELF scores being significantly more likely to have clinical outcomes than those in lower-score groups. A Cox proportional hazards model showed fully adjusted HRs of 75 (ELF score 12.52-16.67), 20 (10.426-12.51) and 5 (8.34-10.425) compared with patients with ELF <8.34. A unit change in ELF is associated with a doubling of risk of liver-related outcome.
  
  
  CONCLUSIONS
  An ELF test can predict clinical outcomes in patients with chronic liver disease and may be a useful prognostic tool in clinical practice.
authors.affiliation: Public Health Sciences and Medical Statistics (MP805) South Academic Block Southampton General Hospital, Southampton SO53 1ER, UK. jules@soton.ac.uk
authors.forename: Julie
authors.initials: J
authors.lastname: Parkes
authors.forename: Paul
authors.initials: P
authors.lastname: Roderick
authors.forename: Scott
authors.initials: S
authors.lastname: Harris
authors.forename: Christopher
authors.initials: C
authors.lastname: Day
authors.forename: David
authors.initials: D
authors.lastname: Mutimer
authors.forename: Jane
authors.initials: J
authors.lastname: Collier
authors.forename: Martin
authors.initials: M
authors.lastname: Lombard
authors.forename: Graeme
authors.initials: G
authors.lastname: Alexander
authors.forename: John
authors.initials: J
authors.lastname: Ramage
authors.forename: Geoffrey
authors.initials: G
authors.lastname: Dusheiko
authors.forename: Mark
authors.initials: M
authors.lastname: Wheatley
authors.forename: Carol
authors.initials: C
authors.lastname: Gough
authors.forename: Alastair
authors.initials: A
authors.lastname: Burt
authors.forename: William
authors.initials: W
authors.lastname: Rosenberg
mesh_terms: D000293:Adolescent; D000328:Adult; D000368:Aged; D015415:Biomarkers / Q000097:blood; D001706:Biopsy; D002908:Chronic Disease; D004812:Epidemiologic Methods; D005260:Female; D006801:Humans; D008099:Liver / Q000473:pathology; D008103:Liver Cirrhosis / Q000175:diagnosis* / Q000209:etiology / Q000473:pathology; D008297:Male; D008875:Middle Aged; D017063:Outcome Assessment, Health Care / Q000379:methods; D011379:Prognosis; D055815:Young Adult
chemical_list: D015415:Biomarkers