Metabolic syndrome and related disorders · 2026
A Simple Screening Strategy for Metabolic Dysfunction-Associated Steatotic Liver Disease in General Health Checkups.
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Katahira Masahito, Shirokami Shin-Ichi, Ono Satoko, Moriura Shigeaki
Аннотация
OBJECTIVE: The recent redefinition of nonalcoholic fatty liver disease (NAFLD) as metabolic dysfunction-associated steatotic liver disease (MASLD) has emphasized the need for effective noninvasive diagnostic tools besides imaging. In this study, we developed a scoring system based on demographic and biochemical parameters for estimating steatotic liver disease (SLD) and compared its diagnostic performance with existing indices, including the Fatty Liver Index (FLI), Hepatic Steatosis Index (HSI), and NAFLD ridge score.
METHODS: Data from 21,056 individuals who underwent abdominal ultrasonography (US) and laboratory tests at a health screening center between 2017 and 2019 were retrospectively analyzed. A multivariate logistic regression model was used to identify the predictors of SLD, which resulted in the development of a novel scoring system. Receiver operating characteristic (ROC) curve analysis was performed to identify the optimal cutoff and to assess the comparative performance.
RESULTS: The score was comprised of six variables, including age, body mass index, high-density lipoprotein cholesterol, hemoglobin A1c, alanine aminotransferase, and albumin. It exhibited a higher area under the ROC curve compared with FLI, HSI, and the NAFLD ridge score. It also showed stronger concordance with ultrasonographic diagnosis, particularly among individuals meeting the cardiometabolic risk criteria for MASLD.
CONCLUSIONS: This novel scoring system provides an accurate, useful tool for estimating SLD and may enhance MASLD detection when used in conjunction with US.
METHODS: Data from 21,056 individuals who underwent abdominal ultrasonography (US) and laboratory tests at a health screening center between 2017 and 2019 were retrospectively analyzed. A multivariate logistic regression model was used to identify the predictors of SLD, which resulted in the development of a novel scoring system. Receiver operating characteristic (ROC) curve analysis was performed to identify the optimal cutoff and to assess the comparative performance.
RESULTS: The score was comprised of six variables, including age, body mass index, high-density lipoprotein cholesterol, hemoglobin A1c, alanine aminotransferase, and albumin. It exhibited a higher area under the ROC curve compared with FLI, HSI, and the NAFLD ridge score. It also showed stronger concordance with ultrasonographic diagnosis, particularly among individuals meeting the cardiometabolic risk criteria for MASLD.
CONCLUSIONS: This novel scoring system provides an accurate, useful tool for estimating SLD and may enhance MASLD detection when used in conjunction with US.