MOFI-FL, a novel score for detecting hepatic steatosis and predicting cardiometabolic mortality - Juan Reyes-Barrera; Rosalinda Posadas-Sánchez; Gilberto Vargas-Alarcón; Guillermo C. Cardoso-Saldaña; Paloma Almeda-Valdes; Omar Yaxmehen Bello Chavolla; Luis Ortiz-Hernandez; Neftali Eduardo Antonio-Villa (Scientific Reports)
Abstract Hepatic steatosis (HS) is a common condition linked to increased cardiometabolic risk; however, biopsy and imaging-based methods limit the widespread diagnosis, especially in low-resource settings. Here, we develop the MOFI-FL index, a simplified tool for HS detection, validate its performance against vibration-controlled transient elastography (VCTE), and evaluate its association with all-cause and cause-specific mortality. Using data from the Genetics of Atherosclerotic Disease study as our discovery cohort, we developed MOFI-FL, incorporating ALT, glucose, uric acid, and BMI, with computed tomography (CT) as the gold standard of HS. We used the continuous NHANES (2017–2018 cycles, n = 4,405) to validate against VCTE and compare our index with four previously validated HS indices (FLI, HSI, NAFLD-LFS, and AST/ALT). Finally, we assessed all-cause and cause-specific mortality prediction using the NHANES-III cohort (n = 12,684) using Cox proportional hazards models adjusted for relevant confounders. The MOFI-FL index demonstrated good diagnostic performance in the internal validation cohort against CT (AUROC: 0.78 [95% CI: 0.72–0.83]; accuracy: 75% [70–79]) and against VCTE (NHANES 17–18: AUROC 0.77 [0.68–0.76]; accuracy: 70% [68–71]). It outperformed existing HS indices in the external cohort. Furthermore, a 1% increase in MOFI-FL was positively associated with all-cause mortality (HR = 1.005 [1.004–1.007]), as well as cardiovascular (HR = 1.008 [1.004–1.007]), diabetes-related (HR = 1.034 [1.028–1.040]), and nephrological deaths (HR = 1.012 [1.000–1.024]). MOFI-FL is a novel and simple tool for HS detection. It offers comparable performance to established indices and predictive capacity for cardiometabolic mortality, making it accessible for clinical and epidemiological applications.