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

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 pati...

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Autores principales: Zou, Haoxuan, Ma, Xiaopu, Zhang, Fan, Xie, Yan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10481547/
https://www.ncbi.nlm.nih.gov/pubmed/37674196
http://dx.doi.org/10.1186/s12944-023-01902-3
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author Zou, Haoxuan
Ma, Xiaopu
Zhang, Fan
Xie, Yan
author_facet Zou, Haoxuan
Ma, Xiaopu
Zhang, Fan
Xie, Yan
author_sort Zou, Haoxuan
collection PubMed
description 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. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12944-023-01902-3.
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spelling pubmed-104815472023-09-07 Comparison of the diagnostic performance of twelve noninvasive scores of metabolic dysfunction-associated fatty liver disease Zou, Haoxuan Ma, Xiaopu Zhang, Fan Xie, Yan Lipids Health Dis Research 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. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12944-023-01902-3. BioMed Central 2023-09-06 /pmc/articles/PMC10481547/ /pubmed/37674196 http://dx.doi.org/10.1186/s12944-023-01902-3 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research
Zou, Haoxuan
Ma, Xiaopu
Zhang, Fan
Xie, Yan
Comparison of the diagnostic performance of twelve noninvasive scores of metabolic dysfunction-associated fatty liver disease
title Comparison of the diagnostic performance of twelve noninvasive scores of metabolic dysfunction-associated fatty liver disease
title_full Comparison of the diagnostic performance of twelve noninvasive scores of metabolic dysfunction-associated fatty liver disease
title_fullStr Comparison of the diagnostic performance of twelve noninvasive scores of metabolic dysfunction-associated fatty liver disease
title_full_unstemmed Comparison of the diagnostic performance of twelve noninvasive scores of metabolic dysfunction-associated fatty liver disease
title_short Comparison of the diagnostic performance of twelve noninvasive scores of metabolic dysfunction-associated fatty liver disease
title_sort comparison of the diagnostic performance of twelve noninvasive scores of metabolic dysfunction-associated fatty liver disease
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10481547/
https://www.ncbi.nlm.nih.gov/pubmed/37674196
http://dx.doi.org/10.1186/s12944-023-01902-3
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