{"database":"biostudies-literature","file_versions":[],"scores":null,"additional":{"omics_type":["Unknown"],"volume":["41(6)"],"submitter":["Tsoi STF"],"funding":["Hong Kong Government Health and Medical Research Fund","Hong Kong Research Grants Council"],"pubmed_abstract":["<h4>Aims</h4>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.<h4>Methods</h4>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.<h4>Results</h4>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.<h4>Conclusion</h4>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."],"journal":["Diabetes/metabolism research and reviews"],"pagination":["e70087"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/S-EPMC12445802"],"repository":["biostudies-literature"],"pubmed_title":["Development of a Chinese-Specific Clinical Model to Predict Maturity-Onset Diabetes of the Young."],"pmcid":["PMC12445802"],"pubmed_authors":["Chow E","Ma RCW","So WY","Fan Y","Lau ESH","Kong APS","Fan B","O CK","Chan JCN","Tsoi STF","Lim CKP","Luk AOY"],"additional_accession":[]},"is_claimable":false,"name":"Development of a Chinese-Specific Clinical Model to Predict Maturity-Onset Diabetes of the Young.","description":"<h4>Aims</h4>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.<h4>Methods</h4>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.<h4>Results</h4>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.<h4>Conclusion</h4>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.","dates":{"release":"2025-01-01T00:00:00Z","publication":"2025 Sep","modification":"2026-06-03T14:57:37.259Z","creation":"2026-04-28T03:11:32.416Z"},"accession":"S-EPMC12445802","cross_references":{"pubmed":["40966384"],"doi":["10.1002/dmrr.70087"]}}