74-OR: ADA Presidents' Select Abstract: CGM Metrics from Five Studies Identify Participants at High Risk of Imminent Type 1 Diabetes (T1D) Development

Introduction & Objective: We assessed if continuous glucose monitoring (CGM) metrics accurately identify imminent stage 3 T1D diagnosis in those with islet autoantibody (IAb) positivity.

Methods: Baseline CGM data were collected from participants with ≥1 positive IAb type from five studies: ASK (N=79), BDR (N=22), DAISY (N=18), DIPP (N=8), and TrialNet (N=91). Median follow-up time was 2.6 y (IQR: 1.5 to 3.6 y). A CGM and baseline factor model and a baseline-only model were compared. CGM model classified participants as low (N=97), medium (N=74), or high (N=47) risk of stage 3 T1D based on <10%, 10-<30%, and ≥30% probability by year 2.

Results: CGM model found % time >140 mg/dL (TA140), area under the curve 140 mg/dL (AUC140), glucose SD, sex, first degree relative, IA2A, and GADA status were more predictive of T1D progression compared to the baseline-only model (C-statistic: 0.76 vs. 0.62). The probability of developing T1D by 2 years was 4%, 17%, and 51% in the low, medium, and high risk groups (Figure). Compared to low risk participants, high risk participants had higher TA140 (median: 10% vs 2%), AUC140 (mean: 2.9 vs. 1.1 mg/dL), and glucose SD (mean: 24 vs. 18 mg/dL).

Conclusion: CGM metrics can help predict T1D progression and classify participant’s risk of impending T1D diagnosis. CGM can be used to better monitor the risk of T1D progression and define eligibility for potential prevention trials.