Siddharth Singh, Sudhakar K. Venkatesh, Andrew Keaveny, Sharon Adam, Frank H. Miller, Patrick Asbach, Edmund M. Godfrey, Alvin C. Silva, Zhen Wang, Mohammad Hassan Murad, Sumeet K. Asrani, David J. Lomas, Richard L. Ehman
Background and aims. We conducted an individual participant data (IPD) pooled analysis on the diagnostic accuracy of magnetic resonance elastography (MRE) to detect fibrosis stage in liver transplant recipients. Material and methods. Through a systematic literature search, we identified studies on diagnostic performance of MRE for staging liver fibrosis, using liver biopsy as gold standard. We contacted study authors for published and unpublished IPD on age, sex, body mass index, liver stiffness, fibrosis stage, degree of inflammation and interval between MRE and biopsy; from these we limited analysis to patients who had undergone liver transplantation. Through pooled analysis using nonparametric two-stage receiver-operating curve (ROC) regression models, we calculated the cluster-adjusted AUROC, sensitivity and specificity of MRE for any (≥ stage 1), significant (≥ stage 2) and advanced fibrosis(≥ stage 3) and cirrhosis (stage 4). Results. We included 6 cohorts (4 published and 2 unpublished series) reporting on 141 liver transplant recipients (mean age, 57 years; 75.2% male; mean BMI, 27.1 kg/m2). Fibrosis stage distribution stage 0, 1, 2, 3, or 4, was 37.6%, 23.4%, 24.8%, 12% and 2.2%, respectively. Mean AUROC values (and 95% confidence intervals) for diagnosis of any (≥ stage 1), significant (≥ stage 2), or advanced fibrosis (≥ stage 3) and cirrhosis were 0.73 (0.66-0.81), 0.69 (0.62-0.74), 0.83 (0.61-0.88) and 0.96 (0.93-0.98), respectively. Similar diagnostic performance was observed in stratified analysis based on sex, obesity and inflammation grade. Conclusions. In conclusion, MRE has high diagnostic accuracy for detection of advanced fibrosis and cirrhosis in liver transplant recipients, independent of BMI and degree of inflammation.
Key words. Fibrosis, Non-invasive, Elastography, Diagnostic performance, Pooled analysis, Liver transplantation, Biomarker