Improving detection of cystic fibrosis related liver disease using liver fibrosis assessment tools

Abstract

Background & aimsCystic 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. MethodsA 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. Results12 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 %). ConclusionWe 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