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Enhanced liver fibrosis test can predict clinical outcomes in patients with chronic liver disease
  1. Julie Parkes1,
  2. Paul Roderick1,
  3. Scott Harris1,
  4. Christopher Day2,
  5. David Mutimer3,
  6. Jane Collier4,
  7. Martin Lombard5,
  8. Graeme Alexander6,
  9. John Ramage7,
  10. Geoffrey Dusheiko8,
  11. Mark Wheatley1,
  12. Carol Gough9,
  13. Alastair Burt2,
  14. William Rosenberg10
  1. 1Public Health Sciences and Medical Statistics, University of Southampton, Southampton, UK
  2. 2Institute of Cellular Medicine, Newcastle University, Newcastle, UK
  3. 3Department of Hepatology, Queen Elizabeth Hospital, Birmingham, UK
  4. 4Department of Gastroenterology John Radcliffe Hospital, Oxford, UK
  5. 5Department of Gastroenterology Royal Liverpool University Hospital, Liverpool, UK
  6. 6Department of Hepatology, Cambridge University Hospitals, NHS Foundation Trust, Cambridge, UK
  7. 7Department Gastroenterology, North Hampshire Hospital, Basingstoke, UK
  8. 8Centre for Hepatology of the Royal Free and University College School of Medicine, Royal Free Hospital, London, UK
  9. 9Wellcome Trust Clinical Research Facility Southampton University Hospitals Trust, Southampton, UK
  10. 10Centre for Hepatology, University College, London, UK
  1. Correspondence to Dr Julie Parkes, Public Health Sciences and Medical Statistics (MP805) South Academic Block Southampton General Hospital, Southampton SO53 1ER, UK; jules{at}soton.ac.uk

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.

  • Liver disease
  • non-invasive test
  • clinical outcome
  • ELF test
  • chronic liver disease
  • Revised 1 April 2010
  • Accepted 8 April 2010

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Footnotes

  • Linked articles 214932.

  • Funding Medical Research Council UK provided the salary costs for JPs via a training fellowship. Siemens Healthcare Diagnostics provided financial support for travel and subsistence for researchers collecting data from each centre.

  • Competing interests Professor William Rosenberg has received research support from Bayer and financial support for lecturing from Siemens Diagnostics.

  • Ethics approval This study was conducted with the approval of the South West Multi-centre Research Ethics Committee. Study reference: MREC/98/6/08.

  • Provenance and peer review Not commissioned; externally peer reviewed.

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