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Joint analysis of multiple biomarkers for identifying type 2 diabetes in middle-aged and older Chinese: a cross-sectional study

OBJECTIVE: Identifying individuals with high risk of type 2 diabetes is important. To evaluate discriminatory ability of multiple biomarkers for type 2 diabetes in a Chinese population. METHODS: Plasma adiponectin, plasminogen activator inhibitor-1, retinol-binding protein 4, resistin, C-reactive pr...

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Autores principales: Wu, Hongyu, Yu, Zhijie, Qi, Qibin, Li, Huaixing, Sun, Qi, Lin, Xu
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BMJ Group 2011
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3191581/
https://www.ncbi.nlm.nih.gov/pubmed/22021786
http://dx.doi.org/10.1136/bmjopen-2011-000191
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author Wu, Hongyu
Yu, Zhijie
Qi, Qibin
Li, Huaixing
Sun, Qi
Lin, Xu
author_facet Wu, Hongyu
Yu, Zhijie
Qi, Qibin
Li, Huaixing
Sun, Qi
Lin, Xu
author_sort Wu, Hongyu
collection PubMed
description OBJECTIVE: Identifying individuals with high risk of type 2 diabetes is important. To evaluate discriminatory ability of multiple biomarkers for type 2 diabetes in a Chinese population. METHODS: Plasma adiponectin, plasminogen activator inhibitor-1, retinol-binding protein 4, resistin, C-reactive protein, interleukin 6 (IL-6), tumour necrosis factor α receptor 2 and ferritin were measured in a population-based sample of 3189 Chinese (1419 men and 1770 women) aged 50–70 years. A weighted biomarkers risk score (BRS) was developed based on the strength of associations of these biomarkers with type 2 diabetes. The discriminatory ability was tested by the area under receiver operating characteristics curve (AUC). RESULTS: Adiponectin, plasminogen activator inhibitor-1, IL-6 and ferritin were independently associated with the prevalence of type 2 diabetes, and they were used to calculate the biomarkers risk score (BRS). After adjustment for the confounding factors, the ORs for type 2 diabetes and impaired fasting glucose with each point increment of BRS were 1.28 (95% CI 1.22 to 1.34) and 1.16 (1.12 to 1.20), respectively. Compared with those in the lowest quintile of the BRS, the participants in the highest quintile have an OR (95% CI) of 6.67 (4.21 to 10.55) for type 2 diabetes. The area under the curve for the BRS and conventional risk factors alone was 0.73 and 0.76, respectively, and substantially increased to 0.81 after combining both BRS and conventional risk factors (p<0.001). CONCLUSIONS: These data suggest that combining multiple biomarkers and conventional risk factors might substantially enhance the ability to identify individuals with type 2 diabetes. More prospective data are warranted to confirm this observation.
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spelling pubmed-31915812011-10-13 Joint analysis of multiple biomarkers for identifying type 2 diabetes in middle-aged and older Chinese: a cross-sectional study Wu, Hongyu Yu, Zhijie Qi, Qibin Li, Huaixing Sun, Qi Lin, Xu BMJ Open Diabetes and Endocrinology OBJECTIVE: Identifying individuals with high risk of type 2 diabetes is important. To evaluate discriminatory ability of multiple biomarkers for type 2 diabetes in a Chinese population. METHODS: Plasma adiponectin, plasminogen activator inhibitor-1, retinol-binding protein 4, resistin, C-reactive protein, interleukin 6 (IL-6), tumour necrosis factor α receptor 2 and ferritin were measured in a population-based sample of 3189 Chinese (1419 men and 1770 women) aged 50–70 years. A weighted biomarkers risk score (BRS) was developed based on the strength of associations of these biomarkers with type 2 diabetes. The discriminatory ability was tested by the area under receiver operating characteristics curve (AUC). RESULTS: Adiponectin, plasminogen activator inhibitor-1, IL-6 and ferritin were independently associated with the prevalence of type 2 diabetes, and they were used to calculate the biomarkers risk score (BRS). After adjustment for the confounding factors, the ORs for type 2 diabetes and impaired fasting glucose with each point increment of BRS were 1.28 (95% CI 1.22 to 1.34) and 1.16 (1.12 to 1.20), respectively. Compared with those in the lowest quintile of the BRS, the participants in the highest quintile have an OR (95% CI) of 6.67 (4.21 to 10.55) for type 2 diabetes. The area under the curve for the BRS and conventional risk factors alone was 0.73 and 0.76, respectively, and substantially increased to 0.81 after combining both BRS and conventional risk factors (p<0.001). CONCLUSIONS: These data suggest that combining multiple biomarkers and conventional risk factors might substantially enhance the ability to identify individuals with type 2 diabetes. More prospective data are warranted to confirm this observation. BMJ Group 2011-08-27 /pmc/articles/PMC3191581/ /pubmed/22021786 http://dx.doi.org/10.1136/bmjopen-2011-000191 Text en © 2011, Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions. This is an open-access article distributed under the terms of the Creative Commons Attribution Non-commercial License, which permits use, distribution, and reproduction in any medium, provided the original work is properly cited, the use is non commercial and is otherwise in compliance with the license. See: http://creativecommons.org/licenses/by-nc/2.0/ and http://creativecommons.org/licenses/by-nc/2.0/legalcode.
spellingShingle Diabetes and Endocrinology
Wu, Hongyu
Yu, Zhijie
Qi, Qibin
Li, Huaixing
Sun, Qi
Lin, Xu
Joint analysis of multiple biomarkers for identifying type 2 diabetes in middle-aged and older Chinese: a cross-sectional study
title Joint analysis of multiple biomarkers for identifying type 2 diabetes in middle-aged and older Chinese: a cross-sectional study
title_full Joint analysis of multiple biomarkers for identifying type 2 diabetes in middle-aged and older Chinese: a cross-sectional study
title_fullStr Joint analysis of multiple biomarkers for identifying type 2 diabetes in middle-aged and older Chinese: a cross-sectional study
title_full_unstemmed Joint analysis of multiple biomarkers for identifying type 2 diabetes in middle-aged and older Chinese: a cross-sectional study
title_short Joint analysis of multiple biomarkers for identifying type 2 diabetes in middle-aged and older Chinese: a cross-sectional study
title_sort joint analysis of multiple biomarkers for identifying type 2 diabetes in middle-aged and older chinese: a cross-sectional study
topic Diabetes and Endocrinology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3191581/
https://www.ncbi.nlm.nih.gov/pubmed/22021786
http://dx.doi.org/10.1136/bmjopen-2011-000191
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