{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,27]],"date-time":"2026-10-27T05:59:59Z","timestamp":1793080799924,"version":"4.5.0"},"reference-count":44,"publisher":"BMJ","issue":"9","funder":[{"DOI":"10.13039\/501100000659","name":"Research Trainees Coordinating Centre","doi-asserted-by":"publisher","award":["CS-2015-15-018"],"award-info":[{"award-number":["CS-2015-15-018"]}],"id":[{"id":"10.13039\/501100000659","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["bmj.com"],"crossmark-restriction":true},"short-container-title":["BMJ Open"],"accepted":{"date-parts":[[2019,8,21]]},"published-print":{"date-parts":[[2019,9]]},"abstract":"<jats:sec>\n                    <jats:title>Objective<\/jats:title>\n                    <jats:p>To develop and validate multivariable clinical diagnostic models to assist distinguishing between type 1 and type 2 diabetes in adults aged 18\u201350.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Design<\/jats:title>\n                    <jats:p>Multivariable logistic regression analysis was used to develop classification models integrating five pre-specified predictor variables, including clinical features (age of diagnosis, body mass index) and clinical biomarkers (GADA and Islet Antigen 2 islet autoantibodies, Type 1 Diabetes Genetic Risk Score), to identify type 1 diabetes with rapid insulin requirement using data from existing cohorts.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Setting<\/jats:title>\n                    <jats:p>UK cohorts recruited from primary and secondary care.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Participants<\/jats:title>\n                    <jats:p>1352 (model development) and 582 (external validation) participants diagnosed with diabetes between the age of 18 and 50 years of white European origin.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Main outcome measures<\/jats:title>\n                    <jats:p>Type 1 diabetes was defined by rapid insulin requirement (within 3 years of diagnosis) and severe endogenous insulin deficiency (C-peptide &lt;200\u2009pmol\/L). Type 2 diabetes was defined by either a lack of rapid insulin requirement or, where insulin treated within 3 years, retained endogenous insulin secretion (C-peptide &gt;600\u2009pmol\/L at \u22655 years diabetes duration). Model performance was assessed using area under the receiver operating characteristic curve (ROC AUC), and internal and external validation.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>Type 1 diabetes was present in 13% of participants in the development cohort. All five predictor variables were discriminative and independent predictors of type 1 diabetes (p&lt;0.001 for all) with individual ROC AUC ranging from 0.82 to 0.85. Model performance was high: ROC AUC range 0.90 (95% CI 0.88 to 0.93) (clinical features only) to 0.97 (95% CI 0.96 to 0.98) (all predictors) with low prediction error. Results were consistent in external validation (clinical features and GADA ROC AUC 0.93 (0.90 to 0.96)).<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>Clinical diagnostic models integrating clinical features with biomarkers have high accuracy for identifying type 1 diabetes with rapid insulin requirement, and could assist clinicians and researchers in accurately identifying patients with type 1 diabetes.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1136\/bmjopen-2019-031586","type":"journal-article","created":{"date-parts":[[2019,9,27]],"date-time":"2019-09-27T00:35:12Z","timestamp":1569544512000},"page":"e031586","update-policy":"https:\/\/doi.org\/10.1136\/crossmarkpolicy","source":"Crossref","is-referenced-by-count":73,"title":["Development and validation of multivariable clinical diagnostic models to identify type 1 diabetes requiring rapid insulin therapy in adults aged 18\u201350 years"],"prefix":"10.1136","volume":"9","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-7732-0211","authenticated-orcid":false,"given":"Anita","family":"Lynam","sequence":"first","affiliation":[{"name":"The Institute of Biomedical & Clinical Science, University of Exeter Medical School, Exeter, UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Timothy","family":"McDonald","sequence":"additional","affiliation":[{"name":"The Institute of Biomedical & Clinical Science, University of Exeter Medical School, Exeter, UK"},{"name":"Department of Clinical Biochemistry, Royal Devon and Exeter NHS Foundation Trust, Exeter, UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Anita","family":"Hill","sequence":"additional","affiliation":[{"name":"The Institute of Biomedical & Clinical Science, University of Exeter Medical School, Exeter, UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"John","family":"Dennis","sequence":"additional","affiliation":[{"name":"The Institute of Biomedical & Clinical Science, University of Exeter Medical School, Exeter, UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Richard","family":"Oram","sequence":"additional","affiliation":[{"name":"The Institute of Biomedical & Clinical Science, University of Exeter Medical School, Exeter, UK"},{"name":"Kidney Unit, Royal Devon and Exeter NHS Foundation Trust, Exeter, UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ewan","family":"Pearson","sequence":"additional","affiliation":[{"name":"Molecular and Clinical Medicine, University of Dundee, Dundee, UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Michael","family":"Weedon","sequence":"additional","affiliation":[{"name":"The Institute of Biomedical & Clinical Science, University of Exeter Medical School, Exeter, UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Andrew","family":"Hattersley","sequence":"additional","affiliation":[{"name":"The Institute of Biomedical & Clinical Science, University of Exeter Medical School, Exeter, UK"},{"name":"Macleod Diabetes and Endocrine Centre, Royal Devon and Exeter NHS Foundation Trust, Exeter, UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Katharine","family":"Owen","sequence":"additional","affiliation":[{"name":"Oxford Centre for Diabetes Endocrinology and Metabolism, University of Oxford, Oxford, UK"},{"name":"Oxford NIHR Biomedical Research Centre, Oxford University Hospitals Foundation Trust, Oxford, UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Beverley","family":"Shields","sequence":"additional","affiliation":[{"name":"The Institute of Biomedical & Clinical Science, University of Exeter Medical School, Exeter, UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0883-7599","authenticated-orcid":false,"given":"Angus","family":"Jones","sequence":"additional","affiliation":[{"name":"The Institute of Biomedical & Clinical Science, University of Exeter Medical School, Exeter, UK"},{"name":"Macleod Diabetes and Endocrine Centre, Royal Devon and Exeter NHS Foundation Trust, Exeter, UK"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"239","published-online":{"date-parts":[[2019,9,26]]},"reference":[{"key":"2025121508281926000_9.9.e031586.1","doi-asserted-by":"publisher","DOI":"10.2337\/dc18-S002"},{"key":"2025121508281926000_9.9.e031586.2","unstructured":"National Institute for Health and Care Excellence . 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