Davidson (1) postulates that the fasting glucose concentration is a good surrogate for time in range (TIR) 70–180 mg/dL, which, as he notes, has been associated with the risk of chronic vascular complications. He proposes that a high correlation between fasting glucose and daytime TIR would support the therapeutic approach of not adding premeal bolus insulin until the fasting glucose target is achieved. We agree with his premise that the Continuous Glucose Monitoring in T2D Basal Insulin Users: The MOBILE Study (MOBILE) provides a unique opportunity to evaluate this association in adults with type 2 diabetes using basal insulin without bolus insulin (2,3).
We did not collect data on time of breakfast to be able to specifically define the prebreakfast fasting glucose concentration. Instead, we determined the nadir glucose between the hours of 5:00 a.m. and 8:00 a.m. each day for up to 10 days of continuous glucose monitoring (CGM) data at three time points: baseline, 3 months, and 8 months. At each time point, an average fasting glucose and average TIR from 8:00 a.m. to 10:00 p.m. were computed, and Pearson correlation coefficients were calculated separately for the two treatment groups (CGM group using unblinded CGM and control group using blinded CGM).
As can be seen in Fig. 1, there was consistency of results across the three time periods and the two treatment groups, with correlation coefficients ranging from −0.68 to −0.77, indicating a moderately strong negative relationship between estimated fasting glucose and daytime TIR. These results support Davidson’s postulate that the fasting glucose concentration and daytime TIR are correlated.
Now that the MOBILE study has shown CGM to be beneficial for patients with type 2 diabetes using basal insulin, it may be time to reevaluate the standard approach of basing basal insulin titration on fasting glucose and consider the role CGM can play in depicting the entire 24 hours of the day to safely and effectively optimize the basal insulin dose in deciding when and how to advance therapy, including adding bolus insulin.
Funding and Duality of Interest. No funding was provided for the conduct of the analyses in this response. Study funding and study devices were provided by Dexcom, Inc. All authors received grant funding from Dexcom to their institution for the conduct of the submitted study. P.C. is a former Dexcom employee, and his current employer has received consulting payments on his behalf from vTv Therapeutics, Beta Bionics, Dexcom, and Diasome. R.W.B. reports that his institution has received funding on his behalf, including grant funding and study supplies from Tandem Diabetes Care, Beta Bionics, and Dexcom, study supplies from Medtronic, Ascencia, and Roche, consulting fees and study supplies from Eli Lilly and Novo Nordisk, and consulting fees from Insulet, Bigfoot Biomedical, vTv Therapeutics, and Diasome. G.A. reports grants from AstraZeneca, Dexcom, Eli Lilly, Insulet, and Novo Nordisk and personal fees from Dexcom and Insulet. R.M.B. reports that his employer has received funds on his behalf for research support, consulting, or serving on the scientific advisory boards for Abbott Diabetes Care, Ascenia, Bigfoot Biomedical, Dexcom, Hygieia, Johnson & Johnson, Lilly, Medscape, Medtronic, Novo Nordisk, Onduo, Roche, Sanofi, and UnitedHealthCare. No other potential conflicts of interest relevant to this article were reported.