Predictors of early fibrosis in patients with metabolically associated steatotic liver disease

Aim: To identify predictors for early liver fibrosis in patients with metabolically associated steatotic liver disease (MASLD). Materials and methods: A prospective cohort study included 131 patients with MASLD (77 females, 54 males; mean age 48.5 ± 0.95 years). Fibrosis stages were verified using transient elastography (FibroScan). Patients were divided into two groups: those without fibrosis (F0, n = 91) and those with early fibrosis (F1-F2, n = 40). Statistical analysis was performed using R (v. 4.3.3) with binary logistic regression and ROC analysis. Results: Early fibrosis was identified in 30.1% of the participants. Type 2 diabetes mellitus (OR = 12.0; 95% CI: 3.94-36.53), a positive family history (OR = 7.75), and hyperlipidemia (OR = 5.77) were established as key risk factors. Obesity (BMI > 30 kg/m²) acted as an obligatory prerequisite for the presence of fibrosis. The most significant quantitative predictors were glycemia level (OR = 2.34) and HOMA-IR index (OR = 1.89). According to the ROC analysis, AST (AUC = 0.832, threshold > 48.5 U/L) and glycemia level (AUC = 0.826, threshold > 7.05 mmol/L) showed the highest diagnostic accuracy. The developed predictive model based on metabolic factors demonstrated high accuracy (AUC = 0.902; sensitivity - 82.5%, specificity - 83.5%), significantly outperforming the international NFS (AUC = 0.829) and FIB-4 (AUC = 0.617) indices. Conclusion: The inclusion of metabolic parameters in the developed algorithm allows for high-accuracy prediction of early changes in liver tissue, making the model an effective screening tool for primary healthcare.