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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Main Authors: Xin-Tian Cai, Nan-Fang Li
Format: Article
Language:English
Published: Editorial Board of Journal of Hainan Medical University 2020-08-01
Series:Journal of Hainan Medical University
Subjects:
Online Access:http://www.hnykdxxb.com/PDF/202015/10.pdf
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spelling 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
collection 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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