Comparison of the diagnostic performance of twelve noninvasive scores of metabolic dysfunction-associated fatty liver disease

Abstract

Background The absence of distinct symptoms in the majority of individuals with metabolic dysfunction-associated fatty liver disease (MAFLD) poses challenges in identifying those at high risk, so we need simple, efficient and cost-effective noninvasive scores to aid healthcare professionals in patient identification. While most noninvasive scores were developed for the diagnosis of nonalcoholic fatty liver disease (NAFLD), consequently, the objective of this study was to systematically assess the diagnostic ability of 12 noninvasive scores (METS-IR/TyG/TyG-WC/TyG-BMI/TyG-WtHR/VAI/HSI/FLI/ZJU/FSI/K-NAFLD) for MAFLD. Methods The study recruited eligible participants from two sources: the National Health and Nutrition Examination Survey (NHANES) 2017-2020.3 cycle and the database of the West China Hospital Health Management Center. The performance of the model was assessed using various metrics, including area under the receiver operating characteristic curve (AUC), net reclassification index (NRI), integrated discrimination improvement (IDI), decision curve analysis (DCA), and subgroup analysis. Results A total of 7398 participants from the NHANES cohort and 4880 patients from the Western China cohort were included. TyG-WC had the best predictive power for MAFLD risk in the NHANES cohort (AUC 0.863, 95% CI 0.855–0.871), while TyG-BMI had the best predictive ability in the Western China cohort (AUC 0.903, 95% CI 0.895–0.911), outperforming other models, and in terms of IDI, NRI, DCA, and subgroup analysis combined, TyG-WC remained superior in the NAHANES cohort and TyG-BMI in the Western China cohort. Conclusions TyG-BMI demonstrated satisfactory diagnostic efficacy in identifying individuals at a heightened risk of MAFLD in Western China. Conversely, TyG-WC exhibited the best diagnostic performance for MAFLD risk recognition in the United States population. These findings suggest the necessity of selecting the most suitable predictive models based on regional and ethnic variations.

Lipid-based insulin-resistance markers predict cardiovascular events in metabolic dysfunction associated steatotic liver disease

“…In our study, we utilized the original formula as reported by Simental-Mendía et al [ 42 ]. For this reason, the cut-offs obtained in our study cannot be directly compared with those previously published [ 43 , 44 ]. Although using different formulas, Zou et al [ 44 ] and Guo et al [ 43 ] found similarly consistent AUCs for the TyG index compared to those reported in our analysis (AUC 0.746 [95% CI 0.735–0.757] and AUC 0.761 [95% CI 0.747–0.774], respectively).…”

Diagnostic indicators and lifestyle interventions of metabolic-associated fatty liver disease

“…In contrast, TyG-WC had the best diagnostic performance for identifying MAFLD risk in the US population. These findings suggest the need to select the most appropriate predictive model based on regional and racial differences ( 24 ). A Korean population-based study suggests that TyG-WC, TyG-BMI are positively correlated with MAFLD risk and can be used clinically to rapidly identify patients at risk of MAFLD ( 25 ).…”