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Influence of ethnicity on the accuracy of non-invasive scores predicting non-alcoholic fatty liver disease

Xia, Ming-Feng, Yki-Järvinen, Hannele, Bian, Hua, Lin, Huan-Dong, Yan, Hong-Mei, Chang, Xin-Xia, Zhou, You ORCID: and Gao, Xin 2016. Influence of ethnicity on the accuracy of non-invasive scores predicting non-alcoholic fatty liver disease. PLoS ONE 11 (8) , e0160526. 10.1371/journal.pone.0160526

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Objectives Presence of non-alcoholic fatty liver disease (NAFLD) can predict risks for diabetes, cardiovascular disease and advanced liver disease in the general population. We aimed to establish a non-invasive score for prediction of NAFLD in Han Chinese, the largest ethnic group in the world, and detect whether ethnicity influences the accuracy of such a score. Methods Liver fat content (LFAT) was measured by quantitative ultrasound in 3548 subjects in the Shanghai Changfeng Community and a Chinese score was created using multivariate logistic regression analyses. This new score was internally validated in Chinese and externally in Finns. Its diagnostic performance was compared to the NAFLD liver fat score, fatty liver index (FLI) and hepatic steatosis index (HSI) developed in Finns, Italians and Koreans. We also analyzed how obesity related to LFAT measured by 1H-MRS in 79 Finns and 118 Chinese with type 2 diabetes (T2D). Results The metabolic syndrome and T2D, fasting serum insulin, body mass index (BMI) and AST/ALT ratio were independent predictors of NAFLD in Chinese. The AUROC in the Chinese validation cohort was 0.76 (0.73–0.78) and in Finns 0.73 (0.68–0.78) (p<0.0001). 43%, 27%, 32% and 42% of Chinese had NAFLD when determined by the Chinese score, NAFLD liver fat score (p<0.001 vs. Chinese score), FLI (p<0.001) and HSI (NS). For any given BMI and waist circumference, the Chinese had a markedly higher LFAT than the Finns. Conclusion The predictors of NAFLD in Han Chinese are as in Europids but the Chinese have more LFAT for any given degree of obesity than Europids. Ethnicity needs to be considered when NAFLD is predicted using risk scores.

Item Type: Article
Date Type: Published Online
Status: Published
Schools: Medicine
Systems Immunity Research Institute (SIURI)
Subjects: R Medicine > R Medicine (General)
Publisher: Public Library of Science
ISSN: 1932-6203
Funders: The Orion-Farmos Research Foundation, the Finnish Cultural Foundation, the Clinical Chemistry Research Foundation and the Paulo Foundation
Date of First Compliant Deposit: 9 September 2016
Date of Acceptance: 19 July 2016
Last Modified: 17 May 2023 03:47

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