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.
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]).
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).
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.
Clinical trial reg. no. NCT01402037, clinicaltrials.gov
This article contains supplementary material online at https://doi.org/10.2337/figshare.28186724.