JMIR Publications

ABSTRACT

Background:

Metabolically associated fatty liver disease (MAFLD) insidiously affects people's health, and many models have been proposed for the evaluation of liver fibrosis. However, there is still a lack of no-invasive and sensitive models for screening MAFLD in high-risk populations.

Objective:

The purpose of this study was to explore a new method for early screening in public, and established a tool for regular self-assessment of MAFLD.

Methods:

Two thousand participants were enrolled in this cross-sectional study. Routine blood, blood biochemistry and FibroScan tests were performed, and body composition was analysed by a body composition instrument. Additionally, multiple factors were also recorded, including disease-related risk factors, the Forns index score, the hepatic steatosis index (HSI) score, the triglyceride glucose index (TyG) score, total body water (TBW), body fat mass (BFM), visceral fat area (VFA), the waist-to-height ratio (WHtR), and the basal metabolic rate (BMR). The new model, named the MAFLD Screening Index (MFSI), was established by binary logistic regression, and body fat mass, the waist-height ratio and total body water were included. A simple rating table, named the MAFLD Rating Table (MRT), was also established by the above indicators.

Results:

The performance of the HSI (area under the curve (AUC): 0.873, specificity 76.8%, sensitivity 81.4%), the WHtR (AUC: 0.866, specificity 79.8%, sensitivity 80.8%), and BFM (AUC: 0.842, specificity 76.9%, sensitivity 76.2%) in discriminating between the MAFLD group and non-fatty liver group was evaluated (P<0.01). The AUC of the combined model including WHtR/HSI/BFM values was 0.900 (specificity: 81.8%, sensitivity: 85.6%, P<0.01). The MFSI was established based on better performance in screening MAFLD patients in the training set (AUC: 0.896, specificity 83.8%, sensitivity 82.1%) and was confirmed in the testing set (AUC: 0.917, specificity 89.8%, sensitivity 84.4%) (P<0.01).

Conclusions:

The new MFSI model had better performance than the other models for early MAFLD screening. The new model showed strong power and stability and shows promise in the area of MAFLD detection and self-assessment. The MRT was practical to assess disease alterations in real time. Clinical Trial: cMetabolic-associated fatty liver disease; Nonalcoholic fatty liver disease; Nonalcoholic steatohepatitis; Body fat mass; Waist-to-height ratio; Basal metabolic rate.