Glucose Variability in a 26-Week Randomized Comparison of Mealtime Treatment With Rapid-Acting Insulin Versus GLP-1 Agonist in Participants With Type 2 Diabetes at High Cardiovascular Risk

Abstract

OBJECTIVEA1C is associated with diabetes complications but does not reflect glycemic variability (GV), which may worsen outcomes by inducing inflammation, oxidative stress, and cardiac arrhythmias. We tested whether a glucagon-like peptide 1 agonist-based regimen can reduce GV and cardiometabolic risk markers while maintaining similar A1C levels in people with insulin-requiring type 2 diabetes and high cardiovascular risk. RESEARCH DESIGN AND METHODSAfter run-in on metformin and basal-bolus insulin (BBI), 102 participants continued metformin and basal insulin and were randomized to exenatide dosing before the two largest meals (glucacon-like peptide-1 receptor agonist and insulin [GLIPULIN group]) or continuation of rapid-acting insulin analogs (BBI group). Indices of GV by continuous glucose monitoring (CGM), hypoglycemia, weight, risk markers, and cardiac arrhythmias were assessed. The primary end point was change in glucose coefficients of variation (CV) by CGM from baseline to 26 weeks. RESULTSAt randomization, the median A1C was 7.3% (57 mmol/mol) for GLIPULIN and 7.4% (56.3 mmol/mol) for BBI, and glucose CVs were 30.3 for BBI and 31.9 for GLIPULIN. At 26 weeks, A1C levels were similar (7.1% [54 mmol/mol] vs. 7.2% [55 mmol/mol]), whereas mean CV improved with GLIPULIN (22.4 vs. 0.4, P = 0.047). Other GV indices followed similar nonsignificant patterns of improvement with GLIPULIN. There were no differences in hypoglycemic events during CGM or arrhythmias during electrocardiographic monitoring. On-trial changes in body weight (24.8 kg vs. +0.7 kg, P < 0.001), alanine aminotransferase (P = 0.0002), and serum amyloid A (P = 0.023) favored GLIPULIN. CONCLUSIONSGLIPULIN reduced GV, weight, and some cardiometabolic risk markers while maintaining equivalent A1C levels versus BBI and might improve clinical outcomes in a larger trial.

Exenatide once weekly improved 24‐hour glucose control and reduced glycaemic variability in metformin‐treated participants with type 2 diabetes: a randomized, placebo‐controlled trial

“…The FLAT‐SUGAR (Fluctuation Reduction With Insulin and GLP‐1 Added Together) trial recently examined the effects of twice‐daily exenatide + insulin glargine + metformin versus rapid‐acting insulin + insulin glargine + metformin on glycaemic variability measured using CGM in participants with type 2 diabetes 24. Twice‐daily exenatide significantly reduced the glucose CV and MAGE compared with prandial insulin, while HbA1c was similar in both groups at study end.…”

Minimizing Glycemic Fluctuations in Patients with Type 2 Diabetes: Approaches and Importance

“…FLAT-SUGAR was a 26-week study comparing the effects on glycemic fluctuations (measured using CGM) of the GLP-1RA exenatide twice daily (BID) or rapid-acting insulin as prandial add-on therapy to insulin glargine plus metformin in patients with T2D ( n = 102). 49 While exenatide BID and prandial insulin both target postprandial glucose concentrations, the insulinogenic effects of exenatide BID are glucose dependent, in contrast to insulin ( Table 1 ). After 26 weeks of treatment, HbA 1c levels were comparable in the exenatide BID and rapid-acting insulin groups (7.1% and 7.2%, respectively).…”

Increased glycemic variability in type 2 diabetes patients treated with insulin - a real-life clinical practice, continuous glucose monitoring (CGM) study

“…Glycemic variability refers to swings in blood glucose levels (28) and is associated with increased oxidative stress (29). The initial result of proof-of-concept FLAT-SUGAR trial (Fluctuation Reduction With Insulin and GLP-1 Added Together) showed that at week 26 the %CV, MAGE, weight, alanine transaminase, and serum amyloid were significantly higher in basal-bolus insulin-treated group versus the basal insulin plus exenatide group, but there was no significant difference between groups regarding glycemic control (HbA1c), hypoglycemic episodes, or other biomarkers (interleukin-6, high-sensitivity C-reactive protein, albuminuria or urinary isoprostanes) (30). It is difficult to perform a quantitative measurement of glycemic variability since it is dependent on amplitude and duration of the fluctuations of glycemic values (31).…”