{"doi":"10.2337/dc22-1960","title":"Refining the Definition of Stage 1 Type 1 Diabetes: An Ontology-Driven Analysis of the Heterogeneity of Multiple Islet Autoimmunity","abstract":"OBJECTIVE: To estimate the risk of progression to stage 3 type 1 diabetes based on varying definitions of multiple islet autoantibody positivity (mIA). RESEARCH DESIGN AND METHODS: Type 1 Diabetes Intelligence (T1DI) is a combined prospective data set of children from Finland, Germany, Sweden, and the U.S. who have an increased genetic risk for type 1 diabetes. Analysis included 16,709 infants-toddlers enrolled by age 2.5 years and comparison between groups using Kaplan-Meier survival analysis. RESULTS: Of 865 (5%) children with mIA, 537 (62%) progressed to type 1 diabetes. The 15-year cumulative incidence of diabetes varied from the most stringent definition (mIA/Persistent/2: two or more islet autoantibodies positive at the same visit with two or more antibodies persistent at next visit; 88% [95% CI 85-92%]) to the least stringent (mIA/Any: positivity for two islet autoantibodies without co-occurring positivity or persistence; 18% [5-40%]). Progression in mIA/Persistent/2 was significantly higher than all other groups (P < 0.0001). Intermediate stringency definitions showed intermediate risk and were significantly different than mIA/Any (P < 0.05); however, differences waned over the 2-year follow-up among those who did not subsequently reach higher stringency. Among mIA/Persistent/2 individuals with three autoantibodies, loss of one autoantibody by the 2-year follow-up was associated with accelerated progression. Age was significantly associated with time from seroconversion to mIA/Persistent/2 status and mIA to stage 3 type 1 diabetes. CONCLUSIONS: The 15-year risk of progression to type 1 diabetes risk varies markedly from 18 to 88% based on the stringency of mIA definition. While initial categorization identifies highest-risk individuals, short-term follow-up over 2 years may help stratify evolving risk, especially for those with less stringent definitions of mIA.","journal":"Diabetes Care","year":2023,"id":338117,"datarank":0.7090767095030087,"base_score":2.8903717578961645,"endowment":2.8903717578961645,"self_citation_contribution":0.4335557636844247,"citation_network_contribution":0.275520945818584,"self_endowment_contribution":0.4335557636844247,"citer_contribution":0.275520945818584,"corpus_percentile":71.77999535855187,"corpus_rank":3649,"citation_count":17,"citer_count":10,"citers_with_citation_signal":9,"citers_with_endowment":9,"datacite_reuse_total":0,"is_dataset":true,"is_dataset_confidence":0.9009,"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":1070492,"name":"Mohamed Ghalwash","orcid":"0000-0002-3169-4346","position":1,"is_corresponding":false},{"id":1070493,"name":"Ying Li","orcid":"0000-0002-2813-9480","position":2,"is_corresponding":false},{"id":493608,"name":"Kenney Ng","orcid":"0000-0003-0792-070X","position":3,"is_corresponding":false},{"id":720830,"name":"Jessica L. 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