M-PAST score is better than MAST score for the diagnosis of active fibrotic nonalcoholic steatohepatitis.

ABSTRACT

BACKGROUND: Clinical trials enroll patients with active fibrotic nonalcoholic steatohepatitis (NASH) (nonalcoholic fatty liver disease [NAFLD] activity score ≥ 4) and significant fibrosis (F ≥ 2); however, screening failure rates are high following biopsy. We developed new scores to identify active fibrotic NASH using FibroScan and magnetic resonance imaging (MRI). METHODS: We undertook prospective primary (n = 176), retrospective validation (n = 169), and University of California San Diego (UCSD; n = 234) studies of liver biopsy-proven NAFLD. Liver stiffness measurement (LSM) using FibroScan or magnetic resonance elastography (MRE), controlled attenuation parameter (CAP), or proton density fat fraction (PDFF), and aspartate aminotransferase (AST) were combined to develop a two-step strategy-FibroScan-based LSM followed by CAP with AST (F-CAST) and MRE-based LSM followed by PDFF with AST (M-PAST)-and compared with FibroScan-AST (FAST) and MRI-AST (MAST) for diagnosing active fibrotic NASH. Each model was categorized using rule-in and rule-out criteria. RESULTS: Areas under receiver operating characteristic curves (AUROCs) of F-CAST (0.826) and M-PAST (0.832) were significantly higher than those of FAST (0.744, p = 0.004) and MAST (0.710, p < 0.001). Following the rule-in criteria, positive predictive values of F-CAST (81.8%) and M-PAST (81.8%) were higher than those of FAST (73.5%) and MAST (70.0%). Following the rule-out criteria, negative predictive values of F-CAST (90.5%) and M-PAST (90.9%) were higher than those of FAST (84.0%) and MAST (73.9%). In the validation and UCSD cohorts, AUROCs did not differ significantly between F-CAST and FAST, but M-PAST had a higher diagnostic performance than MAST. CONCLUSIONS: The two-step strategy, especially M-PAST, showed reliability of rule-in/-out for active fibrotic NASH, with better predictive performance compared with MAST. This study is registered with ClinicalTrials.gov (number, UMIN000012757).