{"doi":"10.1101/2023.06.16.545377","title":"Estimating Insulin Sensitivity and Beta-Cell Function from the Oral Glucose Tolerance Test: Validation of a new Insulin Sensitivity and Secretion (ISS) Model","abstract":"Abstract Efficient and accurate methods to estimate insulin sensitivity (S I ) and beta-cell function (BCF) are of great importance for studying the pathogenesis and treatment effectiveness of type 2 diabetes. Many methods exist, ranging in input data and technical requirements. Oral glucose tolerance tests (OGTTs) are preferred because they are simpler and more physiological. However, current analytical methods for OGTT-derived S I and BCF also range in complexity; the oral minimal models require mathematical expertise for deconvolution and fitting differential equations, and simple algebraic models (e.g., Matsuda index, insulinogenic index) may produce unphysiological values. We developed a new ISS (Insulin Secretion and Sensitivity) model for clinical research that provides precise and accurate estimates of SI and BCF from a standard OGTT, focusing on effectiveness, ease of implementation, and pragmatism. The model was developed by fitting a pair of differential equations to glucose and insulin without need of deconvolution or C-peptide data. The model is derived from a published model for longitudinal simulation of T2D progression that represents glucose-insulin homeostasis, including post-challenge suppression of hepatic glucose production and first- and second-phase insulin secretion. The ISS model was evaluated in three diverse cohorts including individuals at high risk of prediabetes (adult women with a wide range of BMI and adolescents with obesity). The new model had strong correlation with gold-standard estimates from intravenous glucose tolerance tests and hyperinsulinemic-euglycemic clamp. The ISS model has broad clinical applicability among diverse populations because it balances performance, fidelity, and complexity to provide a reliable phenotype of T2D risk.","journal":"bioRxiv (Cold Spring Harbor Laboratory)","year":2023,"id":408864,"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":0,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.9551,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2023-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":270254,"name":"Stephanie T. Chung","orcid":"0000-0001-6989-0417","position":1,"is_corresponding":false},{"id":697771,"name":"Max Springer","orcid":"0000-0001-9291-6574","position":2,"is_corresponding":false},{"id":681682,"name":"Joon Young Kim","orcid":"0000-0003-0448-1684","position":3,"is_corresponding":false},{"id":1054684,"name":"Phil Chen","orcid":null,"position":4,"is_corresponding":false},{"id":254440,"name":"Melanie Cree‐Green","orcid":"0000-0003-1593-1695","position":5,"is_corresponding":false},{"id":429825,"name":"Cecilia Diniz Behn","orcid":"0000-0002-8078-5105","position":6,"is_corresponding":false},{"id":363951,"name":"Anne E. Sumner","orcid":"0000-0001-9640-8999","position":7,"is_corresponding":false},{"id":448934,"name":"Silva Arslanian","orcid":"0000-0002-1528-9324","position":8,"is_corresponding":false},{"id":363949,"name":"Arthur Sherman","orcid":"0000-0002-8372-5941","position":9,"is_corresponding":false},{"id":363948,"name":"Joon Ha","orcid":"0000-0003-4173-2534","position":0,"is_corresponding":true}],"reference_count":51,"raw_metadata":null,"created_at":"2026-07-19T01:21:22.368387Z","pmid":"37503271","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":[]}