Precision medicine in type 1 diabetes: comparing metabolic outcomes of Control-IQ and MiniMed 780G according to patient characteristics

Diabetes Obes Metab. 2024 Dec 17. doi: 10.1111/dom.16118. Online ahead of print.

Abstract

Aims: This study aimed to compare 12-month metabolic outcomes in patients with type 1 diabetes (T1D) treated with either MiniMed 780G (Guardian 4) or Control-IQ (Dexcom G6) automated insulin delivery (AID) systems and identify interaction with patient characteristics.

Materials and methods: We conducted a single-centre, retrospective study including all patients (aged ≥16) with T1D who were started on either MiniMed 780G or Control-IQ between January 2021 and October 2022 and continued for ≥12 months. We used propensity score matching to compare the average marginal effects between MiniMed 780G and Control-IQ regarding the primary outcome (time in range [TIR]) and secondary outcomes (time below range [TBR], glucose monitoring indicator [GMI] and coefficient of variation [CV]) after 12 months. We tested for interaction effects between baseline characteristics (age, sex, socio-professional background, body mass index, insulin daily dose, carbohydrate counting practice) and treatment effect.

Results: We included 245 patients (58% women): 178 treated with Control-IQ and 67 with MiniMed 780G. The mean ± SD age and haemoglobin A1c were 39 ± 15 years and 8.7 ± 1.8% (72 ± 20 mmol/mol) respectively. In the propensity score-matched sample (n = 221), we observed significant differences in 12-month TIR (MiniMed 780G minus Control-IQ [95% CI]: 6.4 [3.4;9.5]), GMI (-0.42 [-0.59; -0.25]) and CV (-2.12 [-3.68; -0.55]), while TBR showed no significant difference (-0.04 [-0.47; +0.40]). The 12-month TIR difference was consistent across subgroups, including baseline carbohydrate counting characteristics.

Conclusion: MiniMed 780G is associated with moderate metabolic superiority compared to Control-IQ, without interaction with patient characteristics. These results suggest that neither model is more appropriate for certain populations, particularly patients without carbohydrate counting practice.

Keywords: automated insulin delivery; carbohydrate counting; precision medicine; type 1 diabetes.