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Statistically Adjusting for Wear Time in Randomized Trials of Continuous Glucose Monitors as a Complement to Intent-to-Treat and As-Treated Analyses: Application and Evaluation in Two Trials.

Department of Health Policy and Management, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA. Division of General Medicine and Clinical Epidemiology, Department of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA. AdventHealth Translational Research Institute, Orlando, Florida, USA. Department of Biostatistics, and Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA. Department of Nutrition, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA. Center for Aging and Health, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA. Division of Endocrinology and Metabolism, Department of Medicine, University of North Carolina School of Medicine, Chapel Hill, North Carolina, USA.

Diabetes technology & therapeutics. 2023;(7):457-466
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Abstract

Background: Randomized trials of continuous glucose monitoring (CGM) often estimate treatment effects using standard intent-to-treat (ITT) analyses. We explored how adjusting for CGM-measured wear time could complement existing analyses by estimating the effect of receiving and using CGM 100% of the time. Methods: We analyzed data from two 6-month CGM trials spanning diverse ages, the Wireless Innovation for Seniors with Diabetes Mellitus (WISDM) and CGM Intervention in Teens and Young Adults with Type 1 Diabetes (CITY) Studies. To adjust the ITT estimates for CGM use, as measured by wear time, we used an instrumental variable (IV) approach with the treatment assignment as an instrument. Outcomes included (1) time in range ([TIR] 70-180 mg/dL), time below range ([TBR] ≤70 mg/dL), and time above range ([TAR] ≥250 mg/dL). We estimated outcomes based on CGM use in the last 28 days of the trial and the full trial. Findings: In the WISDM study, the wear time rates over the 28-day window and full trial period were 93.1% (standard deviation [SD]: 20.4) and 94.5% (SD: 11.9), respectively. In the CITY study, the wear time rates over the 28-day window and full trial period were 82.2% (SD: 26.5) and 83.1% (SD: 21.5), respectively. IV-based estimates for the effect of CGM on TIR, TBR, and TAR suggested greater improvements in glycemic management than the ITT counterparts. The magnitude of the differences was proportional to the level of wear time observed in the trials. Interpretation: In trials of CGM use, the effect of variable wear time is non-negligible. By providing adherence-adjusted estimates, the IV approach may have additional utility for individual clinical decision-making.