4.3 Article

Choosing the duration of continuous glucose monitoring for reliable assessment of time in range: A new analytical approach to overcome the limitations of correlation-based methods

Journal

DIABETIC MEDICINE
Volume 39, Issue 5, Pages -

Publisher

WILEY
DOI: 10.1111/dme.14758

Keywords

continuous glucose monitoring; correlation; estimation error; time-in-ranges; trial design

Funding

  1. Diabetes UK
  2. Innovative Medicines Initiative 2 [777460]
  3. European Union
  4. EFPIA
  5. T1D Exchange
  6. JDRF
  7. International Diabetes Federation (IDF)
  8. Leona M. and Harry B. Helmsley Charitable Trust

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This study compares correlation-based and equation-based approaches for reliable estimation of time spent in different glycaemic ranges. Results show that the equation-based approach is more robust and consistent, suggesting specific monitoring durations based on population characteristics to achieve desired precision in time-in-ranges estimates.
Aims: Reliable estimation of the time spent in different glycaemic ranges (time-in-ranges) requires sufficiently long continuous glucose monitoring. In a 2019 paper (Battelino et al., Clinical targets for continuous glucose monitoring data interpretation: recommendations from the international consensus on time in range. Diabetes Care. 2019;42:1593-1603), an international panel of experts suggested using a correlation-based approach to obtain the minimum number of days for reliable time-in-ranges estimates. More recently (in Camerlingo et al., Design of clinical trials to assess diabetes treatment: minimum duration of continuous glucose monitoring data to estimate time-in-ranges with the desired precision. Diabetes Obes Metab. 2021;23:2446-2454) we presented a mathematical equation linking the number of monitoring days to the uncertainty around time-in-ranges estimates. In this work, we compare these two approaches, mainly focusing on time spent in (70-180) mg/dL range (TIR). Methods: The first 100 and 150 days of data were extracted from study A (148 subjects, similar to 180 days), and the first 100, 150, 200, 250 and 300 days of data from study B (45 subjects, similar to 365 days). For each of these data windows, the minimum monitoring duration was computed using correlation-based and equation-based approaches. The suggestions were compared for the windows of different durations extracted from the same study, and for the windows of equal duration extracted from different studies. Results: When changing the dataset duration, the correlation-based approach produces inconsistent results, ranging from 23 to 64 days, for TIR. The equation-based approach was found to be robust versus this issue, as it is affected only by the characteristics of the population being monitored. Indeed, to grant a confidence interval of 5% around TIR, it suggests 18 days for windows from study A, and 17 days for windows from study B. Similar considerations hold for other time-in-ranges. Conclusions: The equation-based approach offers advantages for the design of clinical trials having time-in-ranges as final end points, with focus on trial duration.

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