{"doi":"10.1210/clinem/dgae582","title":"A Mathematical Model-Derived Disposition Index Without Insulin Validated in Youth With Obesity","abstract":"CONTEXT: The gold-standard clamp measurements for insulin sensitivity (cSI), β-cell function (cBCF), and disposition index (cDI = cSI × cBCF) are not practical in large-scale studies. OBJECTIVE: We sought to 1) validate a mathematical model-derived DI from oral glucose tolerance tests (OGTT) with insulin (mDI) and without (mDI-woI) against cDI and oral disposition index (oDI) and 2) evaluate the ability of the novel indices to detect prediabetes and type 2 diabetes (T2D). METHODS: We carried out a secondary analysis of previously reported cross-sectional observational studies. The Insulin Sensitivity and Secretion mathematical model for glucose-insulin dynamics was applied to 5-point and 3-point OGTTs synchronized with hyperinsulinemic-euglycemic and hyperglycemic clamps from 130 youth with obesity (68 normal glucose tolerance [NGT], 33 impaired glucose tolerance [IGT], 29 T2D). RESULTS: Model-derived DI correlated well with clamp DI (R = 0.76 [logged]). Between NGT and IGT, mDI and mDI-woI decreased more than oDI and cDI, (60% and 59% vs 29% and 27%), and by receiver operating characteristic analysis were superior at detecting IGT compared with oDI and cDI (area under the curve [AUC] 0.88-0.87 vs 0.68-0.65), as was mean glucose (AUC 0.87). CONCLUSION: mDI-woI is better than oDI or the labor-intensive cDI for detecting dysglycemia in obese youth. Bypassing insulin measurements with mDI-woI from the OGTT provides a cost-effective approach for large-scale epidemiological studies of dysglycemia in youth.","journal":"The Journal of Clinical Endocrinology & Metabolism","year":2024,"id":450542,"datarank":0.0,"base_score":0.0,"endowment":0.0,"self_citation_contribution":0.0,"citation_network_contribution":0.0,"self_endowment_contribution":0.0,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":4,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.9409,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2024-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":681682,"name":"Joon Young Kim","orcid":"0000-0003-0448-1684","position":1,"is_corresponding":false},{"id":697771,"name":"Max Springer","orcid":"0000-0001-9291-6574","position":2,"is_corresponding":false},{"id":1054181,"name":"Aaryan Chhabra","orcid":"0009-0006-6845-2881","position":3,"is_corresponding":false},{"id":566422,"name":"Stephanie T Chung","orcid":"0000-0001-7213-8277","position":4,"is_corresponding":false},{"id":363951,"name":"Anne E. Sumner","orcid":"0000-0001-9640-8999","position":5,"is_corresponding":false},{"id":363949,"name":"Arthur Sherman","orcid":"0000-0002-8372-5941","position":6,"is_corresponding":false},{"id":448934,"name":"Silva Arslanian","orcid":"0000-0002-1528-9324","position":7,"is_corresponding":false},{"id":363948,"name":"Joon Ha","orcid":"0000-0003-4173-2534","position":0,"is_corresponding":true}],"reference_count":39,"raw_metadata":null,"created_at":"2026-07-19T02:02:28.969209Z","pmid":"39172553","pmcid":null,"fwci":null,"citation_percentile":null,"influential_citations":0,"oa_status":null,"license":null,"views":0,"total_file_size_bytes":0,"version_count":0,"fair_f":null,"fair_a":null,"fair_i":null,"fair_r":null,"fair_zscore":null,"fair_rationale":null,"fair_model":null,"fair_agent_version":null,"fair_fulltext_source":null,"fair_has_llm":null,"fair_computed_at":null,"clinical_trials":[],"software_tools":[],"db_accessions":[],"linked_datasets":[],"topics":[]}