ArticleScientific reports2024
Development of a clinical calculator to aid the identification of MODY in pediatric patients at the time of diabetes diagnosis.
Article in Scientific reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed.
- Insights into the genetic aetiology of diabetes in Africa.EBioMedicine · 2026Review
- MODY Is Prevalent in Later-Onset Diabetes and Has Potential for Targeted Therapy but Is Challenging to Identify.Diabetes · 2026Article
- Prediction of maturity-onset diabetes of the young subtypes using machine learning.Frontiers in digital health · 2026Article
- Global perspectives on monogenic forms of diabetes.Diabetologia · 2025Review
- Phenotypic and Genetic Diversity in Diabetes Across Populations.The Journal of clinical endocrinology and metabolism · 2025Review
- Genetic variants and characterization of MODY in a single, large pediatric referral center.Journal of clinical & translational endocrinology · 2025Article
- Distinct Roles of Common Genetic Variants and Their Contributions to Diabetes: MODY and Uncontrolled T2DM.Biomolecules · 2025Review
- Revealing Monogenic Diabetes: Clinical and Genetic Features of Pediatric MODY Cases in Türkiye: Single Center Experience.Pediatric diabetes · 2025Article
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Authors and funding
12 authors.
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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.
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