A nomogram of 5-year risk of type 2 diabetes in Chinese population
Objective: The aim of this study was to analyze the risk factors of type 2 diabetes in 5 years in Chinese population, and to construct the prediction model of nomogram and verify its validity. Methods: The physical examination and follow-up data of the participants who received physical examinati...
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doaj-dd278e003f0646318b3207c2e082768e2020-11-25T03:25:26ZengEditorial Board of Journal of Hainan Medical UniversityJournal of Hainan Medical University1007-12371007-12372020-08-0126155458A nomogram of 5-year risk of type 2 diabetes in Chinese populationXin-Tian Cai0Nan-Fang Li1Hypertension Center of the People’s Hospital of Xinjiang Uygur Autonomous Region, National Health Committee Key Laboratory of Hypertension Diagnosis and Treatment Research, Urumqi 830001, ChinaHypertension Center of the People’s Hospital of Xinjiang Uygur Autonomous Region, National Health Committee Key Laboratory of Hypertension Diagnosis and Treatment Research, Urumqi 830001, ChinaObjective: The aim of this study was to analyze the risk factors of type 2 diabetes in 5 years in Chinese population, and to construct the prediction model of nomogram and verify its validity. Methods: The physical examination and follow-up data of the participants who received physical examination at 32 sites in 11 cities in China from 2010 to 2016 were collected from the Dryad digital repository database. Randomly divided into modeling group (n = 22936) and validation group (n = 9830). In the modeling group, the independent risk factors were determined by single factor and multi factor analysis based on Cox regression model, and the nomogram prediction model was constructed by R software. The accuracy and performance of the model were evaluated by AUC value, C-index and calibration curve. Results: The multivariate regression model suggested that fasting blood glucose, triglyceride, smoking history and drinking history were independent risk predictors of 5-year risk of type 2 diabetes in Chinese population. In the modeling group, AUC was 0.776 (95%CI: 0.699-0.849), and C-index was 0.783 (95%CI: 0.706-0.856). Similarly, in the validation group, the AUC value was 0.743 (95%CI:0.665-0.824), and the C-index was 0.764 (95%CI: 0.667-0.846), suggesting that the model had a good discrimination ability. The 5-year adjusted risk curve of type 2 diabetes in Chinese population suggests a good consistency between the predicted value and the actual value. Conclusion: The nomogram model can predict the 5-year risk of type 2 diabetes in Chinese population intuitively and accurately.http://www.hnykdxxb.com/PDF/202015/10.pdfchinese populationtype 2 diabetesrisk factorsnomogram |
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DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Xin-Tian Cai Nan-Fang Li |
spellingShingle |
Xin-Tian Cai Nan-Fang Li A nomogram of 5-year risk of type 2 diabetes in Chinese population Journal of Hainan Medical University chinese population type 2 diabetes risk factors nomogram |
author_facet |
Xin-Tian Cai Nan-Fang Li |
author_sort |
Xin-Tian Cai |
title |
A nomogram of 5-year risk of type 2 diabetes in Chinese population |
title_short |
A nomogram of 5-year risk of type 2 diabetes in Chinese population |
title_full |
A nomogram of 5-year risk of type 2 diabetes in Chinese population |
title_fullStr |
A nomogram of 5-year risk of type 2 diabetes in Chinese population |
title_full_unstemmed |
A nomogram of 5-year risk of type 2 diabetes in Chinese population |
title_sort |
nomogram of 5-year risk of type 2 diabetes in chinese population |
publisher |
Editorial Board of Journal of Hainan Medical University |
series |
Journal of Hainan Medical University |
issn |
1007-1237 1007-1237 |
publishDate |
2020-08-01 |
description |
Objective: The aim of this study was to analyze the risk factors of type 2 diabetes in 5 years in
Chinese population, and to construct the prediction model of nomogram and verify its validity.
Methods: The physical examination and follow-up data of the participants who received
physical examination at 32 sites in 11 cities in China from 2010 to 2016 were collected from
the Dryad digital repository database. Randomly divided into modeling group (n = 22936)
and validation group (n = 9830). In the modeling group, the independent risk factors were
determined by single factor and multi factor analysis based on Cox regression model, and the
nomogram prediction model was constructed by R software. The accuracy and performance
of the model were evaluated by AUC value, C-index and calibration curve. Results: The
multivariate regression model suggested that fasting blood glucose, triglyceride, smoking
history and drinking history were independent risk predictors of 5-year risk of type 2 diabetes
in Chinese population. In the modeling group, AUC was 0.776 (95%CI: 0.699-0.849), and
C-index was 0.783 (95%CI: 0.706-0.856). Similarly, in the validation group, the AUC value
was 0.743 (95%CI:0.665-0.824), and the C-index was 0.764 (95%CI: 0.667-0.846), suggesting
that the model had a good discrimination ability. The 5-year adjusted risk curve of type 2
diabetes in Chinese population suggests a good consistency between the predicted value and
the actual value. Conclusion: The nomogram model can predict the 5-year risk of type 2
diabetes in Chinese population intuitively and accurately. |
topic |
chinese population type 2 diabetes risk factors nomogram |
url |
http://www.hnykdxxb.com/PDF/202015/10.pdf |
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