Proposal of a Novel Serological Algorithm Combining FIB-4 and Serum M2BPGi for Advanced Fibrosis in Nonalcoholic Fatty Liver Disease
- Author:
Sang Yi MOON
1
;
Yang Hyun BAEK
;
Se Young JANG
;
Dae Won JUN
;
Ki Tae YOON
;
Young Youn CHO
;
Hoon Gil JO
;
Ae Jeong JO
Author Information
- Publication Type:Original Article
- From:Gut and Liver 2024;18(2):283-293
- CountryRepublic of Korea
- Language:EN
-
Abstract:
Background/Aims:Noninvasive methods have become increasingly critical in the diagnosis of fibrosis in chronic liver diseases. Herein, we compared the diagnostic performance of serum Mac2 binding protein glycosylation isomer (M2BPGi) and other serological panels for fibrosis in patients with nonalcoholic fatty liver disease (NAFLD) and proposed an improved two-step diagnostic algorithm for advanced fibrosis.
Methods:We enrolled 231 patients diagnosed with NAFLD who underwent a liver biopsy. We subsequently evaluated the diagnostic performance of serological panels, including serum M2BPGi, a fibrosis index based on four factors (FIB-4), aspartate aminotransferase-to-platelet ratio index (APRI), and NAFLD fibrosis score (NFS), in predicting the stage of liver fibrosis. We then constructed a two-step algorithm to better differentiate advanced fibrosis.
Results:The areas under the receiver operating characteristic curves of serum M2BPGi, FIB-4, APRI, and NFS for advanced fibrosis (≥F3) were 0.823, 0.858, 0.779, and 0.827, respectively. To reduce the performance of unnecessary liver biopsy, we propose a two-step algorithm using FIB-4 as an initial diagnostic tool and serum M2BPGi (≥0.6) as an additional diagnostic method for patients classified as intermediate (23%). Using the proposed algorithm, the sensitivity, specificity, accuracy, positive predictive value, and negative predictive value were 0.812, 0.814, 0.814, 0.600, and 0.927, respectively.
Conclusions:Serum M2BPGi is a simple and effective test for advanced fibrosis in patients with NAFLD. Application of the two-step algorithm based on FIB-4 and M2BPGi proposed here can improve diagnostic performance and reduce unnecessary tests, making diagnosis easily accessible, especially in primary medical centers.
