A 24-Week, Randomized, Treat-to-Target Trial Comparing Initiation of Insulin Glargine Once-Daily With Insulin Detemir Twice-Daily in Patients With Type 2 Diabetes Inadequately Controlled on Oral Glucose-Lowering Drugs

OBJECTIVE - To determine whether glargine is noninferior to detemir regarding the percentage of patients reaching A1C <7% without symptomatic hypoglycemia <= 3.1 mmol/l. RESEARCH DESIGN AND METHODS - In this 24-week trial, 973 insulin-naive type 2 diabetic patients on stable oral glucose-lowering drugs with A1CS. 7.0-10.5% were randomized to glargine once daily or detemir twice daily. Insulin doses were systematically titrated. RESULTS - 27.5 and 25.6% of patients reached the primary outcome with glargine and detemir, respectively, demonstrating the noninferiority of glargine. Improvements in A1C were -1.46 +/- 1.09% for glargine and -1.54 +/- 1.11% for detemir (P = 0.149), with similar proportions of patients achieving A1C <7% (P = 0.254) but more detemir-treated patients reaching A1C <6.5% (P = 0.017). Hypoglycemia risk was similar. Weight gain was higher for glargine (difference: 0.77 kg, P <0.001). Glargine doses were lower than detemir doses: 43.5 +/- 129.0 vs. 76.5 +/- 50.5 units/day (P <0.001). CONCLUSIONS - In insulin-naive type 2 diabetic patients, glargine reached similar control as detemir, with more weight gain, but required significantly lower dose

Cost-Effectiveness Analysis of Insulin Detemir Compared to Neutral Protamine Hagedorn (NPH) in Patients with Type 1 and Type 2 Diabetes Mellitus in Spain

Introduction: An Excel® (Microsoft Corporation) model was adapted to estimate the short-term (1-year) cost effectiveness of insulin detemir (IDet) versus neutral protamine Hagedorn (NPH) insulin in patients initiating insulin treatment with type 1 diabetes mellitus (T1DM) and type 2 diabetes mellitus (T2DM) in Spain. Methods: Clinical benefits included the non-severe hypoglycemia rate for T1DM and T2DM, and weight change for T2DM. Three scenarios were included with different hypoglycemia rates estimated on the basis of clinical trials and observational studies. Costs, estimated from perspective of the Spanish Public Healthcare System (Euros 2014), included insulin treatment and non-severe hypoglycemia management costs. Non-severe hypoglycemia, defined as a self-managed event, implied the use of extra glucose testing strips and a general practitioner visit during the week following the event for 25% of patients. An average disutility value was associated to non-severe hypoglycemia events and, for T2DM, to one body mass index unit gain to calculate quality-adjusted life years (QALYs). Results: For the three scenarios a range of 0.025–0.076 QALYs for T1DM and 0.014–0.051 QALYs for T2DM were gained for IDet versus NPH due to non-severe hypoglycemia and weight gain avoidance, in return of an incremental cost of €145–192 for T1DM and €128–206 for T2DM. This resulted in the IDet versus NPH incremental cost-effectiveness ratio (ICER) ranging between €1910/QALY and €7682/QALY for T1DM and €2522/QALY and €15,009/QALY for T2DM. Conclusion: IDet was a cost-effective alternative to NPH insulin in the first year of treatment of patients with T1DM and patients with T2DM in Spain, with ICERs under the threshold value commonly accepted in Spain (€30,000/QALY)

Glycemic control and long-acting insulin analog utilization in patients with type 2 diabetes

Introduction: The objective was to compare glycemic control, insulin utilization, and body weight in patients with type 2 diabetes (T2D) initiated on insulin detemir (IDet) or insulin glargine (IGlar) in a real-life setting in the Netherlands. Methods: Insulin-naïve patients with T2D, starting treatment with IDet or IGlar between January 1, 2004 and June 30, 2008, were selected from the PHARMO data network. Glycemic control (hemoglobin A1c [HbA1c]), target rates (HbA1c <7%), daily insulin dose, and weight gain were analyzed comparing IDet and IGlar for patients with available HbA1c levels both at baseline and at 1-year follow-up. Analysis of all eligible patients (AEP) and a subgroup of patients without treatment changes (WOTC) in the follow-up period were adjusted for patient characteristics, propensity scores, and baseline HbA1c. Results: A total of 127 IDet users and 292 IGlar users were included in the WOTC analyses. The mean HbA1c dropped from 8.4%-8.6% at baseline to 7.4% after 1 year. Patients at HbA1c goal increased from 9% at baseline to 32% for IDet and 11% to 35% for IGlar, which was not significantly different (OR 0.75, 95% CI 0.46, 1.24). Weight gain (n=90) was less among IDet users (+0.4kg) than among IGlar users (+1.1kg), albeit not significant. The AEP analysis (252 IDet

A Glycemia Risk Index (GRI) of Hypoglycemia and Hyperglycemia for Continuous Glucose Monitoring Validated by Clinician Ratings

BackgroundA composite metric for the quality of glycemia from continuous glucose monitor (CGM) tracings could be useful for assisting with basic clinical interpretation of CGM data.MethodsWe assembled a data set of 14-day CGM tracings from 225 insulin-treated adults with diabetes. Using a balanced incomplete block design, 330 clinicians who were highly experienced with CGM analysis and interpretation ranked the CGM tracings from best to worst quality of glycemia. We used principal component analysis and multiple regressions to develop a model to predict the clinician ranking based on seven standard metrics in an Ambulatory Glucose Profile: very low-glucose and low-glucose hypoglycemia; very high-glucose and high-glucose hyperglycemia; time in range; mean glucose; and coefficient of variation.ResultsThe analysis showed that clinician rankings depend on two components, one related to hypoglycemia that gives more weight to very low-glucose than to low-glucose and the other related to hyperglycemia that likewise gives greater weight to very high-glucose than to high-glucose. These two components should be calculated and displayed separately, but they can also be combined into a single Glycemia Risk Index (GRI) that corresponds closely to the clinician rankings of the overall quality of glycemia (r = 0.95). The GRI can be displayed graphically on a GRI Grid with the hypoglycemia component on the horizontal axis and the hyperglycemia component on the vertical axis. Diagonal lines divide the graph into five zones (quintiles) corresponding to the best (0th to 20th percentile) to worst (81st to 100th percentile) overall quality of glycemia. The GRI Grid enables users to track sequential changes within an individual over time and compare groups of individuals.ConclusionThe GRI is a single-number summary of the quality of glycemia. Its hypoglycemia and hyperglycemia components provide actionable scores and a graphical display (the GRI Grid) that can be used by clinicians and researchers to determine the glycemic effects of prescribed and investigational treatments