Development of a Chinese-Specific Clinical Model to Predict Maturity-Onset Diabetes of the Young

IF 6 2区 医学 Q1 ENDOCRINOLOGY & METABOLISM
Sandra T. F. Tsoi, Cadmon K. P. Lim, Ronald C. W. Ma, Eric S. H. Lau, Baoqi Fan, Chun Kwan O, Yingnan Fan, Elaine Chow, Alice P. S. Kong, Wing-Yee So, Juliana C. N. Chan, Andrea O. Y. Luk
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引用次数: 0

Abstract

Aims

Accurate identification of individuals with maturity-onset diabetes of the young (MODY) can support precision diabetes management. However, diagnosing MODY is challenging due to overlapping clinical features with type 2 diabetes. We aimed to develop a prediction model for identifying Chinese with high likelihood of MODY for further genetic testing.

Methods

We developed a logistic regression model using clinical data from an unselected cohort of 1021 Chinese with young-onset (age at diagnosis ≤ 40) non-type 1 diabetes enrolled in the Hong Kong Diabetes Register, 1.9% (n = 19) of whom had MODY (GCK-, HNF1A-, HNF4A- and HNF1B-MODY) by molecular confirmation. We validated the model in an independent local cohort of 822 Chinese with young-onset non-type 1 diabetes. We compared the performance of the new Chinese-specific MODY prediction model with an existing MODY probability calculator in the validation cohort.

Results

The prediction model comprised the following clinical variables: current age, age at diagnosis, sex, body mass index, systolic blood pressure, HDL-cholesterol, LDL-cholesterol, triglyceride and fasting C-peptide. It demonstrated acceptable discrimination of patients with MODY in the validation dataset, with an area under the curve of 0.813 (95% confidence interval 0.647–0.979). At the probability cut-off of 50%, the model achieved a sensitivity of 72.7% and a specificity of 92.4%. It allows identification of one MODY case in every nine genetic tests conducted.

Conclusion

We developed a comprehensive Chinese-specific MODY prediction model. This model can be used in unselected Chinese with young-onset non-type 1 diabetes to identify high-risk individuals for genetic testing.

Abstract Image

一种预测青少年成熟型糖尿病的中国特异性临床模型的建立
目的:准确识别年轻人的成熟型糖尿病(MODY)可以支持精确的糖尿病管理。然而,由于MODY与2型糖尿病的临床特征重叠,诊断MODY具有挑战性。我们的目的是建立一个预测模型,以识别中国人MODY的高可能性,为进一步的基因检测提供依据。方法:我们建立了一个逻辑回归模型,使用未选择的1021名在香港糖尿病登记册登记的中国年轻发病(诊断时年龄≤40岁)非1型糖尿病患者的临床数据,其中1.9% (n = 19)的患者经分子证实患有MODY (GCK-、HNF1A-、HNF4A-和HNF1B-MODY)。我们在822名中国年轻发病非1型糖尿病患者的独立本地队列中验证了该模型。在验证队列中,我们比较了新的中国特异性MODY预测模型与现有MODY概率计算器的性能。结果:预测模型包含以下临床变量:当前年龄、诊断年龄、性别、体重指数、收缩压、高密度脂蛋白胆固醇、低密度脂蛋白胆固醇、甘油三酯和空腹c肽。验证数据集对MODY患者的鉴别是可以接受的,曲线下面积为0.813(95%可信区间为0.647-0.979)。在50%的概率截止值下,该模型的灵敏度为72.7%,特异性为92.4%。它允许在进行的每九次基因检测中识别一例MODY病例。结论:我们建立了一个全面的中国MODY预测模型。该模型可用于未选择的中国年轻发病非1型糖尿病患者,以确定基因检测的高危个体。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Diabetes/Metabolism Research and Reviews
Diabetes/Metabolism Research and Reviews 医学-内分泌学与代谢
CiteScore
17.20
自引率
2.50%
发文量
84
审稿时长
4-8 weeks
期刊介绍: Diabetes/Metabolism Research and Reviews is a premier endocrinology and metabolism journal esteemed by clinicians and researchers alike. Encompassing a wide spectrum of topics including diabetes, endocrinology, metabolism, and obesity, the journal eagerly accepts submissions ranging from clinical studies to basic and translational research, as well as reviews exploring historical progress, controversial issues, and prominent opinions in the field. Join us in advancing knowledge and understanding in the realm of diabetes and metabolism.
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