Improving detection of cystic fibrosis related liver disease using liver fibrosis assessment tools
Jennifer A. Scott,
Andrew M. Jones,
Elliot Jokl,
Timothy Gordon-Walker,
Peter J. Barry,
Neil A. Hanley,
Karen Piper Hanley,
Varinder S. Athwal
Affiliations
Jennifer A. Scott
Division of Diabetes, Endocrine and Gastroenterology, Faculty of Biology Medicine and Health, University of Manchester, Manchester, UK; Division of Gastroenterology, Manchester University NHS Foundation Trust, Manchester, UK
Andrew M. Jones
Adult Cystic Fibrosis Centre, Wythenshawe Hospital, Manchester University NHS Foundation Trust, Manchester, UK; Division of Infection, Immunity and Respiratory Medicine, School of Biological Sciences, Faculty of Biology Medicine and Health, University of Manchester, Manchester, UK
Elliot Jokl
Division of Diabetes, Endocrine and Gastroenterology, Faculty of Biology Medicine and Health, University of Manchester, Manchester, UK
Timothy Gordon-Walker
Department of Hepatology, Scotland Liver Transplant Unit, Royal Infirmary Edinburgh, Edinburgh, UK
Peter J. Barry
Adult Cystic Fibrosis Centre, Wythenshawe Hospital, Manchester University NHS Foundation Trust, Manchester, UK; Division of Infection, Immunity and Respiratory Medicine, School of Biological Sciences, Faculty of Biology Medicine and Health, University of Manchester, Manchester, UK
Neil A. Hanley
Division of Diabetes, Endocrine and Gastroenterology, Faculty of Biology Medicine and Health, University of Manchester, Manchester, UK; Directorate of Research and Innovation, Manchester University NHS Foundation Trust, Manchester, UK
Karen Piper Hanley
Division of Diabetes, Endocrine and Gastroenterology, Faculty of Biology Medicine and Health, University of Manchester, Manchester, UK; Directorate of Research and Innovation, Manchester University NHS Foundation Trust, Manchester, UK; Wellcome Trust Centre for Cell Matrix Research, Faculty of Biology Medicine and Health, University of Manchester, Manchester, UK
Varinder S. Athwal
Division of Diabetes, Endocrine and Gastroenterology, Faculty of Biology Medicine and Health, University of Manchester, Manchester, UK; Division of Gastroenterology, Manchester University NHS Foundation Trust, Manchester, UK; Directorate of Research and Innovation, Manchester University NHS Foundation Trust, Manchester, UK; Corresponding author. 3.015, 3rd Floor AV Hill Building, Upper Brook Street, University of Manchester, M13 9PT, UK.
Background & aims: Cystic Fibrosis related liver disease (CFLD) is the 3rd largest cause of death in Cystic Fibrosis (CF). As advances in pulmonary therapies have increased life-expectancy, CFLD has become more prevalent. Current guidelines may underdiagnose liver fibrosis, particularly in its early stages. Newer modalities for the assessment of fibrosis may provide a more accurate assessment. FibroScan is validated in assessing fibrosis for several aetiologies including alcohol and fatty liver, the CFLD cohort have an entirely different phenotype so the cut off values are not transferrable. We appraised fibrosis assessment tools to improve diagnosis of CFLD. Methods: A prospective cohort (n = 114) of patients from the Manchester Adult Cystic Fibrosis Centre, UK were identified at annual assessment. Demographic data including co-morbidity, CFTR genotyping, biochemistry and imaging were used alongside current guidelines to group into CFLD and CF without evidence of liver disease. All patients underwent liver stiffness measurement (LSM) and assessment of serum-based fibrosis biomarker panels. A new diagnostic criterion was created and validated in a second, independent cohort. Results: 12 of 114 patient classified as CFLD according to the European Cystic Fibrosis Society best practice guidelines. No specific risk factors for development of CFLD were identified. Liver enzymes were elevated in patients with CFLD. Serum biomarker panels did not improve diagnostic criteria. LSM accurately predicted CFLD. A new diagnostic criterion was proposed and validated in a separate cohort, accurately predicating CFLD in 10 of 32 patients (31 %). Conclusion: We present a cohort of patients with CF assessed for the presence of liver fibrosis using blood biomarkers and LSM based platforms. We propose a new, simplified diagnostic criteria, capable of accurately predicting liver disease in patients with CF.Clinical trials number: NCT04277819
