Computation of optimal continuous glucose monitoring duration
Interactive tool implementing the University of Padova approach
BETA Version
Based on the work by N. Camerlingo et al., Scientific Reports, 2020
Design a new clinical trial Evaluate a completed clinical trial
Time-in-ranges are key metrics to evaluate glucose control in clinical trials involving continuous glucose monitoring (CGM) sensors.
In this form you can select:
Time in range, i.e., % of readings and time time spent in 70-180 mg/dL (3.9-10.0 mmol/L);
Time in tight range, i.e., % of readings and time spent in 70-140 mg/dl (3.9-7.77 mmol/L);
Time above range, i.e., % of readings and time spent above 180 mg/dL (>10.0 mmol/L);
Time below range, i.e., % of readings and time spent below 70 mg/dL (< 3.9 mmol/L);
A mathematical formula derived in [1] links the precision of time-in-ranges estimates to the number of CGM days, and was validated using data of
huge heterogeneous studies [2].
The present tool can be used by the diabetes community in two different scenarios. Firstly (see clinical case #1), it can help clinical trial teams to determine a suitable duration
of the study, i.e., the number of days allowing to achieve a desired precision in the final time-in-ranges. Secondly (see clinical case #2), it can help data
analysts to determine the precision around the time-in-ranges estimated in published studies, based on how long the CGM values were collected over.
Clinical case #1:
An investigator is designing a clinical trial involving subjects with type 1 diabetes wearing 5-min CGM sensors. The primary outcome is the TBR.
Based on a previous pilot study, the investigator expects an average TBR of 4.00% in the population. She/he is interested in setting a suitable trial duration and
desires a maximum confidence interval around the final TBR of 1.00%. In this form:
In the initial panel "Operation to be performed", check "Design a new clinical trial".
In the first section of the form, select "time below range" in the "Time-in-range to be considered" menu.
Select the option "5" from the "CGM sensor sampling period" menu.
Enter "4.00" as "Time expected to be spent in the glycemic range" (if this is unknown, do not type anything: it will be set to the values of [2]).
Select the type of uncertainty. In case of absolute uncertainty, type "1.00" in the "Time-in-range to be considered" space. In case of relative
uncertainty, divide this value by the percent time expected to be spent below range (1.00/0.04 = 25).
Press Calculate.
The form suggests a monitoring duration of 44 days. Moreover, the form returns the (absolute or relative) uncertainty around the time-in-ranges.
In case of TBR it will be 4.00% ± 0.98%.
Clinical case #2:
An individual was diagnosed with type 1 diabetes and the investigato perscribed her/him a 14-day CGM monitoring with a 5-minute CGM sensor, to evaluate the overall glycemic
control. At the end of the 2-week period, the TIR observed was 70%. The investigator also needs to know how precise the estimated value is. In this form:
In the initial panel "Operation to be performed", check "Evaluate a completed clinical trial".
In the second section of the form, check "Time in range".
Type "70" as the estimated time in range.
Insert the trial duration (14) in the apposite space.
Select the option "5" from the "CGM sensor sampling rate" menu.
Press Calculate.
The form returns a relative uncertainty of 7.32% and a standard deviation (i.e., absolute uncertainty) of 5.12%, meaning that an estimated time in range of
70% has a confidence interval of 70% ± 5.12%.
References:
N. Camerlingo, M. Vettoretti, A. Facchinetti, J.K. Mader, P. Choudhary, S. Del Favero, "An analytical approach to determine the optimal
duration of continuous glucose monitoring data required to reliably estimate time in hypoglycemia", Scientific Reports, 2021 (doi:
https://www.nature.com/articles/s41598-020-75079-5)
N. Camerlingo, M. Vettoretti, A. Facchinetti, J.K. Mader, P. Choudhary, S. Del Favero, "Design of clinical trials to assess diabetes
treatments: minimal duration of CGM data to estimate time-in-ranges with a desired precision", submitted to Diabetes, Obesity and Metabolism, 2021
