Aster K Desouter, Bart Keymeulen, Ursule Van de Velde, Annelien Van Dalem, Bruno Lapauw, Christophe De Block, Pieter Gillard, Nicole Seret, Eric V Balti, Elena R Van Vooren, Willem Staels, Sara Van Aken, Marieke den Brinker, Sylvia Depoorter, Joke Marlier, Hasan Kahya, Frans K Gorus
{"title":"Repeated OGTT Versus Continuous Glucose Monitoring for Predicting Development of Stage 3 Type 1 Diabetes: A Longitudinal Analysis.","authors":"Aster K Desouter, Bart Keymeulen, Ursule Van de Velde, Annelien Van Dalem, Bruno Lapauw, Christophe De Block, Pieter Gillard, Nicole Seret, Eric V Balti, Elena R Van Vooren, Willem Staels, Sara Van Aken, Marieke den Brinker, Sylvia Depoorter, Joke Marlier, Hasan Kahya, Frans K Gorus","doi":"10.2337/dc24-2376","DOIUrl":null,"url":null,"abstract":"<p><strong>Objective: </strong>Evidence for using continuous glucose monitoring (CGM) as an alternative to oral glucose tolerance tests (OGTTs) in presymptomatic type 1 diabetes is primarily cross-sectional. We used longitudinal data to compare the diagnostic performance of repeated CGM, HbA1c, and OGTT metrics to predict progression to stage 3 type 1 diabetes.</p><p><strong>Research design and methods: </strong>Thirty-four multiple autoantibody-positive first-degree relatives (FDRs) (BMI SD score [SDS] <2) were followed in a multicenter study with semiannual 5-day CGM recordings, HbA1c, and OGTT for a median of 3.5 (interquartile range [IQR] 2.0-7.5) years. Longitudinal patterns were compared based on progression status. Prediction of rapid (<3 years) and overall progression to stage 3 was assessed using receiver operating characteristic (ROC) areas under the curve (AUCs), Kaplan-Meier method, baseline Cox proportional hazards models (concordance), and extended Cox proportional hazards models with time-varying covariates in multiple record data (n = 197 OGTTs and concomitant CGM recordings), adjusted for intraindividual correlations (corrected Akaike information criterion [AICc]).</p><p><strong>Results: </strong>After a median of 40 (IQR 20-91) months, 17 of 34 FDRs (baseline median age 16.6 years) developed stage 3 type 1 diabetes. CGM metrics increased close to onset, paralleling changes in OGTT, both with substantial intra- and interindividual variability. Cross-sectionally, the best OGTT and CGM metrics similarly predicted rapid (ROC-AUC = 0.86-0.92) and overall progression (concordance = 0.73-0.78). In longitudinal models, OGTT-derived AUC glucose (AICc = 71) outperformed the best CGM metric (AICc = 75) and HbA1c (AICc = 80) (all P < 0.001). HbA1c complemented repeated CGM metrics (AICc = 68), though OGTT-based multivariable models remained superior (AICc = 59).</p><p><strong>Conclusions: </strong>In longitudinal models, repeated CGM and HbA1c were nearly as effective as OGTT in predicting stage 3 type 1 diabetes and may be more convenient for long-term clinical monitoring.</p>","PeriodicalId":93979,"journal":{"name":"Diabetes care","volume":" ","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2025-02-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Diabetes care","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2337/dc24-2376","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Repeated OGTT Versus Continuous Glucose Monitoring for Predicting Development of Stage 3 Type 1 Diabetes: A Longitudinal Analysis.
Objective: Evidence for using continuous glucose monitoring (CGM) as an alternative to oral glucose tolerance tests (OGTTs) in presymptomatic type 1 diabetes is primarily cross-sectional. We used longitudinal data to compare the diagnostic performance of repeated CGM, HbA1c, and OGTT metrics to predict progression to stage 3 type 1 diabetes.
Research design and methods: Thirty-four multiple autoantibody-positive first-degree relatives (FDRs) (BMI SD score [SDS] <2) were followed in a multicenter study with semiannual 5-day CGM recordings, HbA1c, and OGTT for a median of 3.5 (interquartile range [IQR] 2.0-7.5) years. Longitudinal patterns were compared based on progression status. Prediction of rapid (<3 years) and overall progression to stage 3 was assessed using receiver operating characteristic (ROC) areas under the curve (AUCs), Kaplan-Meier method, baseline Cox proportional hazards models (concordance), and extended Cox proportional hazards models with time-varying covariates in multiple record data (n = 197 OGTTs and concomitant CGM recordings), adjusted for intraindividual correlations (corrected Akaike information criterion [AICc]).
Results: After a median of 40 (IQR 20-91) months, 17 of 34 FDRs (baseline median age 16.6 years) developed stage 3 type 1 diabetes. CGM metrics increased close to onset, paralleling changes in OGTT, both with substantial intra- and interindividual variability. Cross-sectionally, the best OGTT and CGM metrics similarly predicted rapid (ROC-AUC = 0.86-0.92) and overall progression (concordance = 0.73-0.78). In longitudinal models, OGTT-derived AUC glucose (AICc = 71) outperformed the best CGM metric (AICc = 75) and HbA1c (AICc = 80) (all P < 0.001). HbA1c complemented repeated CGM metrics (AICc = 68), though OGTT-based multivariable models remained superior (AICc = 59).
Conclusions: In longitudinal models, repeated CGM and HbA1c were nearly as effective as OGTT in predicting stage 3 type 1 diabetes and may be more convenient for long-term clinical monitoring.
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