{"doi":"10.1007/s00125-025-06434-2","title":"Type 1 diabetes prediction in autoantibody-positive individuals: performance, time and money matter","abstract":"Abstract Aims/hypothesis Efficient prediction of clinical type 1 diabetes is important for risk stratification and monitoring of autoantibody-positive individuals. In this study, we compared type 1 diabetes predictive models for predictive performance, cost and participant time needed for testing. Methods We developed 1943 predictive models using a Cox model based on a type 1 diabetes genetic risk score (GRS2), autoantibody count and types, BMI, age, self-reported gender and OGTT-derived glucose and C-peptide measures. We trained and validated the models using halves of a dataset comprising autoantibody-positive first-degree relatives of individuals with type 1 diabetes ( n =3967, 49% female, 14.9 ± 12.1 years of age) from the TrialNet Pathway to Prevention study. The median duration of follow-up was 4.7 years (IQR 2.0–8.1), and 1311 participants developed clinical type 1 diabetes. Models were compared for predictive performances, estimated cost and participant time. Results Models that included metabolic measures had best performance, with most exhibiting small performance differences (less than 3% and p >0.05). However, the cost and participant time associated with measuring metabolic variables ranged between US$56 and US$293 and 10–165 min, respectively. The predictive model performance had temporal variability, with the highest GRS2 influence and discriminative power being exhibited in the earliest preclinical stages. OGTT-derived metabolic measures had a similar performance to HbA 1c - or Index 60 -derived models, with an important difference in cost and participant time. Conclusions/interpretation Cost–performance model analyses identified trade-offs between cost and performance models, and identified cost-minimising options to tailor risk-screening strategies. Graphical Abstract","journal":"Diabetologia","year":2025,"id":517387,"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":8,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.9568,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2025-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":1369636,"name":"Erin L. Templeman","orcid":"0009-0007-4306-7909","position":1,"is_corresponding":false},{"id":96015,"name":"Andrea K. Steck","orcid":"0000-0002-5931-9484","position":2,"is_corresponding":false},{"id":5962,"name":"Hemang Parikh","orcid":"0000-0002-9076-6709","position":3,"is_corresponding":false},{"id":787689,"name":"Lu You","orcid":"0000-0002-9400-2060","position":4,"is_corresponding":false},{"id":428049,"name":"Suna Önengüt-Gümüşcü","orcid":"0000-0002-6563-8334","position":5,"is_corresponding":false},{"id":336608,"name":"Peter A. Gottlieb","orcid":"0000-0002-7601-8536","position":6,"is_corresponding":false},{"id":533259,"name":"Taylor M. Triolo","orcid":"0000-0003-4796-6542","position":7,"is_corresponding":false},{"id":11274,"name":"Stephen S. Rich","orcid":"0000-0003-3872-7793","position":8,"is_corresponding":false},{"id":5970,"name":"Jeffrey P. Krischer","orcid":"0000-0003-4526-888X","position":9,"is_corresponding":false},{"id":1383658,"name":"R. Brett McQueen","orcid":"0000-0002-4302-2678","position":10,"is_corresponding":false},{"id":249639,"name":"Richard A. Oram","orcid":"0000-0003-3581-8980","position":11,"is_corresponding":false},{"id":7390,"name":"María J. Redondo","orcid":"0000-0001-5871-4645","position":12,"is_corresponding":false},{"id":1243742,"name":"the Type 1 Diabetes TrialNet Study Group","orcid":null,"position":13,"is_corresponding":false},{"id":25375,"name":"Lauric Ferrat","orcid":"0000-0002-3166-9685","position":0,"is_corresponding":true}],"reference_count":42,"raw_metadata":null,"created_at":"2026-07-19T02:48:59.410472Z","pmid":"40347237","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":[]}