Performance Evaluation of a Novel Non-Invasive Test for the Detection of Advanced Liver Fibrosis in Metabolic Dysfunction-Associated Fatty Liver Disease

Abstract

Metabolic dysfunction-associated fatty liver disease (MAFLD) may progress to advanced liver fibrosis (ALF). We evaluated the diagnostic accuracy of a novel Liver Fibrosis Risk Index (LFRI) in MAFLD subjects using transient elastography (TE) as the reference method for liver fibrosis measurement and then the diagnostic performance of a new two-step non-invasive algorithm for the detection of ALF risk in MAFLD, using Fibrosis-4 (FIB-4) followed by LFRI and comparing it to the reference algorithm based on FIB-4 and TE. We conducted a prospective study on 104 MAFLD European adult subjects. All consenting subjects underwent TE and measurements of FIB-4 and LFRI. For FIB-4 and TE, validated cut-offs were used. An ROC analysis showed that LFRI diagnosed severe fibrosis with moderate accuracy in MAFLD subjects with a negative predictive value above 90%. Using the new algorithm with LFRI thresholds recommended by the manufacturer, the number of subjects classified into ALF risk groups (low, intermediate, or high) differed significantly when compared with the reference algorithm (p = 0.001), with moderate agreement between them (weighted kappa (95% CI) = 0.59 (0.41–0.77)). To improve the performance of the LFRI-based algorithm, we modified cut-off points based on ROC curves obtained by dividing the study population according to the reference algorithm and observed no difference between algorithms (p = 0.054) in categorizing ALF risk, with a slight increase in the total agreement (weighted kappa (95% CI) = 0.63 (0.44–0.82)). Our findings suggest that using the novel LFRI as a second-line test may represent a potential alternative for liver fibrosis risk stratification in MAFLD patients; however, modified cut-offs are needed to optimize its performance.

Keywords

• metabolic dysfunction-associated fatty liver disease
• non-invasive algorithms
• liver fibrosis