The association of the metabolic score for insulin resistance and metabolic dysfunction-related steatosis liver disease: a population-based observational study - Haoxuan Zou; Xiaopu Ma; Wen Pan; Yan Xie (European Journal of Medical Research)
Abstract Background Insulin resistance (IR) plays a pivotal role in the pathogenesis and advancement of metabolic dysfunction-related steatosis liver disease (MASLD). Despite the recent proposal of the metabolic score for insulin resistance (METS-IR) as a dependable indirect indicator of IR, limited research has delved into the correlation between METS-IR and MASLD risk. Consequently, the objective of this study was to examine the relationship between METS-IR and MASLD within the U.S. population and evaluate its predictive capacity for MASLD risk. Methods Based on data from the National Health and Nutrition Examination Survey (NHANES), a cross-sectional study was carried out on 2764 participants. The laboratory measurements and clinical data, which are risk factors for MASLD, were analyzed. Results After adjustment for confounders, a significant, stable, and positive association was demonstrated between METS-IR and MASLD risk (Odds ratio (OR) increase of 2.28 per standard deviation (SD)), 95% confidence interval (CI) 1.58 to 3.30, P for trend = 0.001). Consistently, the area under the receiver operating characteristic curve (AUC) showed that METS-IR (AUC (95% CI) 0.823 (0.807–0.838)) better predicted the risk of MASLD than homeostasis model assessment (HOMA-IR), triglyceride glucose index (TyG), triglyceride to high-density lipoprotein cholesterol ratio (TG/HDL), visceral adiposity index (VAI), and hepatic steatosis index (HSI). Not only that, the AUC of METS-IR on the risk of MASLD remained the greatest in the subgroups of sex, age, race, overweight status, hypertension status, and diabetes status. Furthermore, integrated discrimination improvement (IDI), decision curve analysis (DCA), and net reclassification index (NRI) also showed satisfactory predictive power of METS-IR. Conclusions In this dataset, METS-IR was found to be linked to an increased risk of MASLD and can be a useful tool for identifying individuals at high risk of MASLD.