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CGM-derived metrics are superior to HbA1c when assessing therapeutic efficacy

When evaluating the efficacy of an intervention, mean glucose would be the best metric, followed by TAR, TIR and lastly HbA1c.

The present analysis was conducted to assess the performance of three CGM metrics (mean glucose, time in range [TIR] and time above range [TAR]) and HbA1c when evaluating treatment efficacy (in terms of lowering blood glucose) in clinical trials and in real-world practice. Data from 545 people with type 1 diabetes and 98 with type 1 diabetes and pregnancy were analysed.

Mean glucose was used as the reference metric as it is generally believed that the mean glucose level is the primary factor responsible for glycation of haemoglobin and other proteins and serves as an initial step in the pathogenesis of long-term complications. Time below range was not evaluated as it is only weakly correlated with the other four glycaemic metrics.

Mean glucose was most closely correlated with TAR (r=0.98) but had much weaker correlations with HbA1c (r=0.78) and TIR (r=–0.73). Following 6 months of use of real-time CGM, changes in mean glucose were more highly correlated with changes in TAR (r=0.95) than with changes in TIR (r=–0.85) or changes in HbA1c (r=–0.47).

The authors conclude that CGM-derived measures of mean glucose, TAR and TIR are highly correlated among themselves but relatively weakly correlated with HbA1c. When evaluating the efficacy of an intervention, mean glucose would be the best metric, followed by TAR, TIR and lastly HbA1c. However, these metrics of efficacy in terms of lowering average glucose levels need to be supplemented by metrics summarising the risks of hypoglycaemia and/or glycaemic variability.

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