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开发一个临床计算器,以帮助在糖尿病诊断时识别儿科患者中的 MODY。

Development of a clinical calculator to aid the identification of MODY in pediatric patients at the time of diabetes diagnosis.

机构信息

The Department of Clinical and Biomedical Sciences, Faculty of Health and Life Sciences, University of Exeter, Exeter, UK.

Skånes University Hospital, Lund, Sweden.

出版信息

Sci Rep. 2024 May 8;14(1):10589. doi: 10.1038/s41598-024-60160-0.

Abstract

Maturity Onset Diabetes of the Young (MODY) is a young-onset, monogenic form of diabetes without needing insulin treatment. Diagnostic testing is expensive. To aid decisions on who to test, we aimed to develop a MODY probability calculator for paediatric cases at the time of diabetes diagnosis, when the existing "MODY calculator" cannot be used. Firth logistic regression models were developed on data from 3541 paediatric patients from the Swedish 'Better Diabetes Diagnosis' (BDD) population study (n = 46 (1.3%) MODY (HNF1A, HNF4A, GCK)). Model performance was compared to using islet autoantibody testing. HbA1c, parent with diabetes, and absence of polyuria were significant independent predictors of MODY. The model showed excellent discrimination (c-statistic = 0.963) and calibrated well (Brier score = 0.01). MODY probability > 1.3% (ie. above background prevalence) had similar performance to being negative for all 3 antibodies (positive predictive value (PPV) = 10% v 11% respectively i.e. ~ 1 in 10 positive test rate). Probability > 1.3% and negative for 3 islet autoantibodies narrowed down to 4% of the cohort, and detected 96% of MODY cases (PPV = 31%). This MODY calculator for paediatric patients at time of diabetes diagnosis will help target genetic testing to those most likely to benefit, to get the right diagnosis.

摘要

青少年起病的成年型糖尿病(MODY)是一种早发、单基因糖尿病,无需胰岛素治疗。诊断检测费用昂贵。为了帮助决定对哪些人进行检测,我们旨在为糖尿病诊断时的儿科病例开发一种 MODY 可能性计算器,此时无法使用现有的“MODY 计算器”。我们在来自瑞典“改善糖尿病诊断”(BDD)人群研究的 3541 名儿科患者的数据上(n=46(1.3%)MODY(HNF1A、HNF4A、GCK))开发了费希尔逻辑回归模型。将模型性能与胰岛自身抗体检测进行了比较。HbA1c、有糖尿病的父母和无多尿是 MODY 的独立显著预测因子。该模型显示出优异的区分度(c 统计量=0.963)和良好的校准度(Brier 评分=0.01)。MODY 可能性>1.3%(即高于背景患病率)与所有 3 种抗体均为阴性的性能相似(阳性预测值(PPV)分别为 10%和 11%,即阳性检测率约为 1/10)。可能性>1.3%且 3 种胰岛自身抗体阴性的可能性缩小到队列的 4%,并检测到 96%的 MODY 病例(PPV=31%)。这种用于糖尿病诊断时儿科患者的 MODY 计算器将有助于将基因检测靶向最有可能受益的人群,以获得正确的诊断。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4c7c/11079008/0f0483a7f7be/41598_2024_60160_Fig1_HTML.jpg

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