Evaluation of stochastic adjustment for glucose sensor bias during closed-loop insulin delivery.

BACKGROUND: In outpatient studies of closed-loop insulin delivery systems, it is not typically practical to obtain blood glucose measurements for an outcome measure. Using a continuous glucose monitoring (CGM) device as both part of the intervention and as the outcome in a clinical trial can give a biased estimate of the treatment effect. A stochastic adjustment has been proposed to correct this problem.
MATERIALS AND METHODS: We performed Monte Carlo simulations to assess the performance of the stochastic adjustment in various scenarios where the CGM device was used passively and when it was used to inform insulin delivery. The resulting bias for using CGM to estimate the percentage of glucose values inside a target range was compared with and without the proposed stochastic adjustment.
RESULTS: CGM bias for estimating the percentage of glucose values 70-180 mg/dL ranged from -6% to +4% in the various scenarios studied. In some circumstances, stochastic adjustment did indeed reduce this CGM bias. However, in other circumstances, stochastic adjustment made the bias worse. Stochastic adjustment tended to underestimate the true percentage of glucose values in range for most, but not all, scenarios considered in these simulations.
CONCLUSIONS: Stochastic adjustment is not a general solution to the problem of CGM bias. The proposed adjustment relies on an implicit assumption that usually does not hold. The appropriate level of adjustment depends on how efficacious the closed-loop system is, which is not typically known in practice.