We aimed to develop a calculator to determine the probability of having HNF1A-MODY (hepatocyte nuclear factor 1 alpha-maturity-onset diabetes of the young) or HNF4A (hepatocyte nuclear factor 4 alpha)-MODY (the commonest forms of MODY) in Asian Indians using clinical and biochemical criteria.
Methods:
We extracted data on individuals with young-onset diabetes aged <30 years (n = 29 191) from electronic records. Genetically confirmed HNF1A- and HNF4A-MODY (n = 55) were selected along with 1000 individuals each of type 1 diabetes (T1D) and type 2 diabetes (T2D). These data sets were used to develop a classification model using logistic regression. The model’s performance was evaluated using receiver operating characteristic (ROC) curves in an internal data set and validated in an external data set.
Results:
Eight predictive models were constructed, beginning with a basic model that included variables, such as age at diagnosis, body mass index (BMI), parental history, and glycated hemoglobin (HbA1c) (models 1 and 5). High-density lipoprotein (HDL) cholesterol was added in models 2 and 6, stimulated C-peptide in models 3 and 7, and all predictors were combined in models 4 and 8. Models 1 to 4, designed to distinguish MODY from T1D, achieved an ROC-area under the curve (AUC) value ranging from 0.884 to 0.957, while models 5 to 8, aimed at differentiating MODY from T2D, achieved an ROC-AUC value ranging from 0.914 to 0.936. All models demonstrated excellent performance in internal validation, with high five-fold cross-validation c-statistics. An online calculator using these models estimates MODY probability that is accessible at https://mdrf-t1d-calculator.shinyapps.io/MODY/.
Conclusion:
We developed an ethnicity-specific calculator to help identify individuals with possible HNF1A-MODY or HNF4A-MODY in Asian Indians. This user-friendly, web-based tool would be helpful to select candidates for genetic testing in this population.
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