Objective: Achieving and maintaining recommended glycemic targets, including those for glycated hemoglobin A1c (A1C), is key to improving outcomes in patients with type 2 diabetes (T2D). As fasting plasma glucose and postprandial glucose contribute to overall A1C, targeting both is essential for sustaining glycemic control. Methods: This review examines the complementary mechanisms of action of glucagon-like peptide 1 (GLP-1) receptor agonists and basal insulin; they both enhance glucose-stimulated insulin release and suppress glucagon secretion. GLP-1 receptor agonists also slow gastric emptying and increase satiety. Results: Adding a GLP-1 receptor agonist to therapy with a basal insulin analog has been associated with improved overall glycemic control, with comparable risk of hypoglycemia and no weight gain. Titratable fixed-ratio co-formulations of basal insulin and a GLP-1 receptor agonist have been shown to improve glycemic control, with less complex dosing schedules, possibly increasing treatment adherence. The slow titration of fixed-ratio co-formulations has been shown to reduce the occurrence and severity of gastrointestinal adverse events associated with the use of a separate GLP-1 receptor agonist. Titratable fixed-ratio co-formulations also mitigate insulin-associated weight gain, and show a comparable risk of hypoglycemia to basal insulin use alone. Conclusions: The efficacy and safety of titratable fixed-ratio co-formulations have been demonstrated for insulin degludec/liraglutide and insulin glargine/lixisenatide in the DUAL and LixiLan trials, respectively, in both insulin-naive and -experienced patients. Titratable fixed-ratio co-formulations represent an attractive treatment option for many patients with T2D. ARTICLE HISTORY

AimsTo explore the treatment outcomes in adult patients with type 2 diabetes (T2D) enrolled in the GetGoal trials of lixisenatide (LIXI), and the predictive effects of baseline characteristics on outcomes.MethodsThis study was a pooled analysis of patient‐level data from the LIXI GetGoal studies comparing LIXI and placebo. Patients were divided into baseline therapy groups: those receiving oral antidiabetes drugs (OADs) at baseline (n = 2760) or those receiving basal insulin at baseline (n = 1198).ResultsCompared with placebo, LIXI treatment led to significantly greater reductions in glycated haemoglobin (HbA1c), and greater achievement of the composite endpoint of HbA1c <7.0% (53 mmol/mol) with no symptomatic hypoglycaemia and no weight gain in either the OAD (34% vs 18%; P < .0001) or the basal insulin groups (19% vs 10%; P < .0001). Treatment with LIXI was associated with a greater percentage of patients experiencing a symptomatic hypoglycaemic event compared with placebo in both the OAD (5% vs 3%; P = .0098) and basal insulin groups (27% vs 17%; P < .0001). In assessing baseline factors that were predictors of treatment outcomes, only baseline HbA1c and LIXI treatment were strong predictors of outcomes in both the OAD and basal insulin groups. No other baseline characteristic had such a large or consistent clinically relevant predictive effect across treatment outcomes.ConclusionsThe results from this study show that irrespective of baseline characteristics, LIXI treatment, as an add‐on to OAD or basal insulin therapy, is effective in reducing HbA1c and achieving composite endpoints.

■ ABSTRACTObjective. Many patients with type 2 diabetes do not reach glycemic goals despite basal insulin treatment. This study assessed the achievement of a target A1C <7.0% (<53 mmol/mol) after initiation of basal insulin in two settings.Methods. This was a retrospective analysis of pooled randomized controlled trial (RCT) data, from 11 24-week studies of patients initiating basal insulin performed between 2000 and 2005 and of outpatient electronic medical record (EMR) data from the General Electric Centricity database for insulin-naive patients initiating basal insulin between 2005 and 2012. Baseline characteristics stratified by target A1C and fasting plasma glucose (FPG) attainment were compared descriptively.Results. In the RCT dataset, 49.0% of patients failed to achieve the target A1C at 6 months versus 72.4% and 72.9% at 6 and 12 months in the EMR dataset, respectively. Despite this, in the RCT dataset, 79.4% of patients achieved the target A1C and/or an FPG <130 mg/dL. In the EMR dataset, only 47.6% and 47.3% of patients achieved an A1C <7.0% and/or FPG <130 mg/dL at 6 and 12 months, respectively. Overall, patients with an A1C >7.0% had a longer diabetes duration and were more likely to be female, nonwhite, and self-funding or covered by Medicaid. Among patients with an A1C >7.0%, more RCT patients (58.0%) had an FPG <130 mg/dL than EMR patients at 6 months (27.8%) and 12 months (27.7%).Conclusion. Unmet needs remain after basal insulin initiation, particularly in real-world settings, where many patients require further insulin titration. In both populations, patients failing to achieve the target A1C despite attaining an FPG <130 mg/dL require interventions to improve postprandial control.

Background Diabetes is present in 10.5% of the US population and accounts for 14.3% of all office-based physician visits made by adults. Despite this established office-based approach, the disease and its adverse outcomes including glycemic control and clinical events tend to worsen over time. Available home technology now provides accurate, reliable data that can be transmitted directly to the electronic medical record. Objective This study aims to evaluate the impact of a virtual, home-based diabetes management program on clinical measures of diabetes control compared to usual care. Methods We evaluated glycemic control and other diabetes-related measures after 1 year in 763 patients with type 2 diabetes enrolled into a home-based digital medicine diabetes program and compared them to 794 patients matched for age, sex, race, BMI, hemoglobin A1c (HbA1c), creatinine, estimated glomerular filtration rate, and insulin use in a usual care group after 1 year. Digital medicine patients completed questionnaires online, received medication management and lifestyle recommendations from a clinical pharmacist or advanced practice provider and a health coach, and were asked to submit blood glucose readings using a commercially available Bluetooth-enabled glucose meter that transmitted data directly to the electronic medical record. Results After 1 year, usual care patients demonstrated no significant changes in HbA1c (mean 7.3, SE 1.7 to mean 7.3, SE 1.6; P=.41) or changes in the proportion of patients with HbA1c≥9.0 (n=117, 15% to n=113, 14%; P=.51). Digital medicine patients demonstrated improvements in HbA1c (mean 7.3, SE 1.5 to mean 6.9, SE 1.2; P<.001) and significant changes in the proportion of patients with HbA1c≥9.0 (n=107, 14% to n=49, 6%; P<.001), diabetes distress (n=198, 26% to n=122, 16%; P<.001), and hypoglycemic episodes (n=313, 41.1% to n=91, 11.9%; P<.001). Conclusions A digital diabetes program is associated with significant improvement in glycemic control and other diabetes measures. The use of a virtual health intervention using connected devices was widely accepted across a broad range of ethnic diversity, ages, and levels of health literacy.

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