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

Lipids in Health and Disease

Research

Haoxuan Zou¹  Xiaopu Ma¹  Yan Xie¹  Fan Zhang² 

[1] Department of Gastroenterology, West China Hospital, Sichuan University, No. 37 Guoxue Alley, 610041, Chengdu, Sichuan, China;Health Management Center, West China Hospital, General Practice Medical Center, Sichuan University, No. 37 Guoxue Alley, 610041, Chengdu, Sichuan, China;

关键词: Metabolic dysfunction-associated fatty liver disease;    External validation of prediction models;    Receiver operating characteristic curve;    Net reclassification index;    Integrated discrimination improvement;    Decision curve analysis;   

DOI  :  10.1186/s12944-023-01902-3

 received in 2023-07-04, accepted in 2023-08-11,  发布年份 2023

来源: Springer

【 摘 要 】

BackgroundThe 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.MethodsThe 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.ResultsA 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.ConclusionsTyG-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.

【 授权许可】

CC BY   
© BioMed Central Ltd., part of Springer Nature 2023

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