Abstract

Liver fibrosis is a critical public health concern, necessitating early detection to prevent progression. This study evaluates the recently developed LiverRisk score and steatosis-associated Fibrosis Estimator (SAFE) score against established indices for prognostication and/or fibrosis prediction in 4diverse cohorts, including participants with metabolic dysfunction-associated steatotic liver disease (MASLD). We used data from the Mount Sinai Data Warehouse (32,828 participants without liver disease diagnoses), the Mount Sinai MASLD/MASH Longitudinal Registry (422 participants with MASLD), and National Health and Nutrition Examination Survey 2017-2020 (4133 participants representing the general population) to compare LiverRisk score, FIB-4 index, APRI, and SAFE score. Analyses included Cox proportional hazards regressions, Kaplan-Meier estimates, and classification metrics to evaluate performance in prognostication and fibrosis prediction. In Mount Sinai Data Warehouse, LiverRisk score was significantly associated with future liver-related outcomes but did not significantly outperform FIB-4 or APRI for predicting any of the outcomes. In the general population, LiverRisk score and SAFE score outperformed FIB-4 and APRI in identifying fibrosis, but LiverRisk score underperformed among participants who were non-White or had type 2 diabetes. Among participants with MASLD, SAFE score outperformed FIB-4 and APRI in 1 of 2 cohorts, but there were generally few significant performance differences between all 4 scores. LiverRisk score does not consistently outperform existing predictors in diverse populations, and further validation is needed before adoption in settings with significant differences from the original derivation cohorts. It remains necessary to replicate the ability of these scores to predict liver-specific mortality, as well as to develop diagnostic tools for liver fibrosis that are accessible and substantially better than current scores, especially among patients with MASLD and other chronic liver conditions.

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