Exploratory Analysis of Continuous Glucose Monitoring Patterns in First-Degree Relatives with Dysglycemia at Risk of Progression to Stage 3 Type 1 Diabetes.

INTRODUCTION

Continuous glucose monitoring (CGM) can characterize subtle glucose changes in early-stage type 1 diabetes (T1D). We assessed whether CGM metrics predict Stage 3 T1D in first-degree relatives (FDRs) with positive islet autoantibodies (IAbs) and dysglycemia participating in INNODIA.

METHODS

We analyzed IAb-positive FDRs with dysglycemia and available CGM data. CGM metrics were analyzed longitudinally and in a restricted analysis limited to the last assessment before Stage 3 T1D in progressors. CGM metrics were compared using linear mixed models. Predictive performance of single and combined CGM metric models was evaluated using receiver operating characteristic curve analyses.

RESULTS

Data from 27 participants (14 females [52%], median [interquartile range] age: 16.8 [11.9-39.8] years) were analyzed. Nine participants progressed to Stage 3 T1D after a median of 163 [129-244] days from CGM assessment. In the restricted analysis, progressors had higher mean glucose (132 vs. 111 mg/dL, P = 0.001), time >140 mg/dL (36% vs. 10%, P = 0.003), and time >180 mg/dL between 9 PM and 2 AM (8.1% vs. 1.0%, P = 0.005), whereas time <70 mg/dL between 4 and 7 AM was lower (0% vs. 1.2%, P = 0.001). Time >140 mg/dL yielded an area under the curve (AUC) of 0.83 (95% confidence interval [CI] 0.66-1.00). Combining time >140 mg/dL with time-specific percentages >180 and <70 mg/dL increased AUC to 0.93 (95% CI 0.84-1.00). A model incorporating time between 70 and 140 mg/dL, mean glucose, early morning <70 mg/dL, and MAGE achieved 100% sensitivity and 86% specificity.

CONCLUSIONS

CGM may help identify FDRs with IAbs and dysglycemia at higher risk of progressing to Stage 3 T1D. Combining CGM metrics improved prediction compared with time >140 mg/dL alone.