列线图预测中国老年人2型糖尿病患病风险
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R587.1

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邯郸市科学技术研究与发展计划项目:22422083010ZC


Study on nomograph predicting the risk of type 2 diabetes mellitus in China adults
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    摘要:

    为了建立国内老年人2型糖尿病(type 2 diabetes mellitus, T2DM)患病风险的预测模型并加以验证。基于中国一个健康筛查项目的数据库,纳入了24,804名基线检查时无T2DM的老年人,随访时间为3年和5年。以7:3的比例分成训练集和验证集,单变量和多变量Cox回归分析用于确定独立危险因素,构建列线图预测中国老年人T2DM的3年和5年的发病率。C指数、校准图、临床决策曲线(Decision Curve Analysis, DCA)用于评估列线图在验证集中的准确性。最终发现年龄、空腹血糖(Fasting Plasma Glucose, FPG)、体重指数 (body mass index, BMI)、收缩压(systolic blood pressure, SBP)、甘油三酯(triglyceride, TG)、谷丙转氨酶(Alanine aminotransferase, ALT)和尿素氮(urea nitrogen, UN)是T2DM的独立危险因素,并将其纳入列线图。在训练集和验证集中,C指数分别为0.8278 (95% CI:0.8125-0.8432)和0.8414(95% CI:0.8195-0.8632)。校准图表明,估计概率与实际观测率之间具有良好的一致性。DCA表明,按照此列线图对高危人群早期干预,可以获得净获益。通过该模型,早期识别高危人群有助于及时干预,降低T2DM的发病率。

    Abstract:

    Development and validation of a prediction model for the risk of type 2 diabetes (T2DM) in the elderly in China was attempted. Based on the database of a health examination project in China, 24,804 elderly people without T2DM at baseline were included, and the follow-up time was 3 and 5 years. Divided into training set and validation set at a ratio of 7:3, univariate and multivariate Cox regression analysis was used to determine independent risk factors, and a nomogram was constructed to predict the 3-year and 5-year incidence rate of T2DM in the elderly in China. C index, calibration chart and clinical decision curve analysis (DCA) are used to evaluate the accuracy of nomogram in the validation set. Finally, age, fasting plasma glucose (FPG), body mass index (BMI), systolic blood pressure (SBP), triglyceride (TG), alanine aminotransferase (ALT) and urea nitrogen (UN) were found to be independent risk factors for T2DM, and were included in the nomogram. In the training set and validation set, the C index was 0.8278 (95% CI: 0.8125-0.8432) and 0.8414 (95% CI: 0.8195-0.8632), respectively. The calibration diagram shows that there is good consistency between the estimated probability and the actual observation rate. DCA shows that early intervention in high-risk groups according to this nomogram can obtain net benefits. Through this model, early identification of high-risk groups is helpful to timely intervention and reduce the incidence rate of T2DM.

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雷庆华,李军华,霍燕飞,等. 列线图预测中国老年人2型糖尿病患病风险[J]. 科学技术与工程, 2023, 23(13): 5493-5499.
Lei Qinghua, Li Junhua, Huo Yanfei, et al. Study on nomograph predicting the risk of type 2 diabetes mellitus in China adults[J]. Science Technology and Engineering,2023,23(13):5493-5499.

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  • 收稿日期:2022-09-07
  • 最后修改日期:2023-03-10
  • 录用日期:2023-03-15
  • 在线发布日期: 2023-05-29
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