MOFI-FL, a novel score for detecting hepatic steatosis and predicting cardiometabolic mortality
Abstract
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.
Article Details
Authors (8)
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