Pharmacokinetics and Pharmacodynamics of Human Regular U-500 Insulin Administered via Continuous Subcutaneous Insulin Infusion Versus Subcutaneous Injection in Adults With Type 2 Diabetes and High-Dose Insulin Requirements.

INTRODUCTION: Human regular U-500 insulin (U-500R) is approved for subcutaneous (SC) injection in patients with diabetes requiring >200 units/day of insulin. Here, pharmacokinetic and pharmacodynamic (PK/PD) profiles following U-500R administered by continuous subcutaneous insulin infusion (CSII) and SC injection in adults with type 2 diabetes (T2D) on high-dose insulin were studied. METHODS: In this randomized, crossover, euglycemic clamp study, patients received a 100-unit bolus of U-500R via SC injection or CSII with basal infusion using a U-500R specific pump. PK parameters were estimated using non-compartmental methods. PD estimates were derived from the glucose infusion rate during the euglycemic clamp procedure. RESULTS: When corrected for the basal infusion, the PK profiles for the 100-unit bolus of U-500R were similar for CSII and SC injection. Without correction for basal infusion, PK and PD profiles showed a greater insulin concentration and effect when U-500R was administered via CSII compared to SC injection, primarily due to basal insulin infusion for CSII. The ratio of geometric least squares AUC0-tlast means SC:CSII (90% CI) is 0.857 (0.729, 1.01) with correction (mean AUC0-tlast: 5230 pmol*L/h [SC injection] and 6070 pmol*L/h [CSII, with correction]) and 0.424 (0.361, 0.499) without correction (mean AUC0-tlast: 12300 pmol*L/h [CSII, without correction]). Median time-to-peak insulin concentration was six hours (range 0.5-8 hours) via SC injection and five hours (0.5-12 hours) via CSII. CONCLUSIONS: In adults with T2D on high-dose insulin, U-500R PK/PD parameters were similar for a 100-unit bolus when given by SC injection or CSII via a U-500R pump.

Use of Connected Pen as a Diagnostic Tool to Evaluate Missed Bolus Dosing Behavior in People with Type 1 and Type 2 Diabetes.

Objective: This study used connected pen to determine missed bolus dose (MBD) frequency during masked and unmasked continuous glucose monitoring (CGM) periods and examined its link with time-in-range (TIR), time-above-range (TAR), time-below-range (TBR), and key participant characteristics in people with diabetes. Methods: This was a 12-week, single-arm, exploratory, two-period study for people with type 1 diabetes (T1D) or type 2 diabetes (T2D). The primary objective was to estimate the average number of MBD during masked and real-time CGM use. The secondary objective was to estimate the average percent TIR and its relationship to MBD. An exploratory objective was to investigate the participant characteristics that were associated with MBD. Data were analyzed for differences in MBD by diabetes type and other participant characteristics, by CGM period, and by hypoglycemic fear scores. Results: Participants (n = 64; T1D, n = 38; T2D, n = 26) were 48 ± 11.9 years old and 44% were female. From the masked to the unmasked period, MBD, %TAR, %TBR, and glycated hemoglobin decreased significantly (0.74 MBD/day to 0.62 MBD/day, P = 0.008; 53.6%-48.1%, P = 0.004; 4.49%-2.93%, P < 0.001; mean 8.8%-8.4%, P < 0.001, respectively), while %TIR increased significantly (41.9%-49.0%, P < 0.001). MBD/day was negatively associated with TIR (P = 0.016) and positively associated with TAR (P = 0.015) for T1D and positively associated with TBR (P = 0.024) for T2D in the masked period only. MBD was significantly associated with fear of hypoglycemia for T2D, but not T1D. Conclusions: MBD is associated with reduced TIR when CGM is masked and tailored therapeutic approaches are needed for T1D and T2D populations.

Patient-reported outcomes in a study of human regular U-500 insulin delivered by continuous subcutaneous insulin infusion or multiple daily injections in patients with type 2 diabetes.

Human regular U-500 insulin (U-500R) provides both basal and prandial coverage to people with diabetes. As part of the VIVID study, we studied patient-reported outcomes (PRO) of U-500R delivered by multiple daily injections (MDI, n = 211) and continuous subcutaneous infusion using a novel U-500R pump (CSII, n = 209). Treatment-Related Impact Measure for Diabetes (TRIM-D) for Diabetes Device (TRIM-DD) questionnaires were administered at weeks 0, 14 and 26. TRIM scores with effect sizes (ES) for within-group and between-group change were reported. All TRIM-D scores significantly improved from baseline for both groups (P < .001). The Diabetes Management domain had the greatest improvement, 16.3 (ES = 0.85) and 10.6 (ES = 0.51) for CSII and MDI, respectively. At the study end, the CSII group had significantly higher TRIM-D scores than the MDI group (P < .05). Most TRIM-DD scores had small within-group improvements and were not different between groups. People with type 2 diabetes on U-500R by either CSII or MDI reported improvement in PRO, particularly in Diabetes Management, Treatment Burden and Psychological Health domains, with greater improvement in the CSII group. In terms of delivery device and function, the CSII and MDI methods were similarly acceptable.

Glucose Variability and Time in Range in Type 2 Diabetes Treated with U-500R by Pump or Injection: CGM Findings from the VIVID Study.

Background: The EValuating U-500R Infusion Versus Injection in Type 2 Diabetes Mellitus (VIVID) study compared two methods of U-500R insulin delivery, continuous subcutaneous insulin infusion (CSII) and multiple daily injection (MDI), for 26 weeks in people with type 2 diabetes (T2D) requiring high doses of insulin. To assess glycemic variability (GV) and time in range (TIR), a subset of participants performed masked continuous glucose monitoring (CGM). Methods: VIVID participants were adults who had insulin requirements of >200 but ≤600 U/day and A1C 7.5% to 12%. Participants performed masked CGM for seven consecutive days on each of three occasions: before weeks 0 (baseline), 14, and 26. The primary objective was to compare GV between CSII and MDI groups, based on change from baseline of within-day standard deviation (SDw) of CGM glucose. Results: Of 54 participants enrolled, 41 with evaluable data were analyzed (17 and 24 in CSII and MDI groups, respectively). The CSII group had a significantly greater reduction from baseline in mean SDw of glucose (45.0 to 38.2 mg/dL [-8.1 mg/dL]) compared with the MDI group (47.0 to 45.8 [-0.4 mg/dL]; P = 0.047). TIR 70-180 mg/dL glucose increased significantly from baseline in the CSII group only, from 59.8% to 73.1% (change +12.9%, P < 0.05), but was not significantly different between groups. There were no significant between-group differences in the endpoint mean glucose or A1C. Conclusions: In the VIVID CGM substudy of U-500R in people with T2D requiring high doses of insulin, participants using CSII significantly reduced GV compared with MDI. CSII also significantly increased TIR with no difference between groups.

Human regular U-500 insulin via continuous subcutaneous insulin infusion versus multiple daily injections in adults with type 2 diabetes: The VIVID study.

AIM: To compare the safety and efficacy of U500-R delivered by a novel, specifically designed U500-R insulin pump with U-500R delivered by multiple daily injections (MDI). METHODS: The phase 3 VIVID study randomized people with type 2 diabetes to U-500R by continuous subcutaneous insulin infusion (CSII) or MDI. Participants (aged 18-85 years) had HbA1c ≥7.5% and ≤12.0% and a total daily dose of insulin >200 and ≤600 U/day. After a 2-week transition to three times daily injections of U-500R, participants were treated for 24 weeks with U-500R by CSII or MDI. Treatment arms were compared using mixed model repeated measures analysis. RESULTS: The study randomized 420 participants (CSII: 209, MDI: 211) with 365 completers. Mean changes from baseline were: HbA1c, -1.27% (-13.9 mmol/mol) with CSII and -0.85% (-9.3 mmol/mol) with MDI (difference - 0.42% [-4.6 mmol/mol], P <0.001); fasting plasma glucose, -33.9 mg/dL (-1.9 mmol/L) with CSII and 1.7 mg/dL (0.09 mmol/L) with MDI (difference - 35.6 mg/dL [-2.0 mmol/L], P <0.001); total daily dose, 2.8 U with CSII and 51.3 U with MDI (P < 0.001). Weight changes and rates of documented symptomatic and severe hypoglycaemia were similar between groups; the CSII group had a higher rate of nocturnal hypoglycaemia. CONCLUSIONS: In type 2 diabetes requiring high doses of insulin, both methods of U-500R delivery lowered HbA1c. However, the CSII group attained greater HbA1c reduction with significantly less insulin. Individualized dose titration will be important to balance glycaemic control with hypoglycaemia risk.

Reduced medical spending associated with increased use of a remote diabetes management program and lower mean blood glucose values.

Aims: Many new mobile technologies are available to assist people in managing chronic conditions, but data on the association between the use of these technologies and medical spending remains limited. As the available digital technology offerings to aid in diabetes management increase, it is important to understand their impact on medical spending. The aim of this study was to investigate the financial impact of a remote digital diabetes management program using medical claims and real-time blood glucose data. Materials and methods: A retrospective analysis of multivariate difference-in-difference and instrumental variables regression modeling was performed using data collected from a remote digital diabetes management program. All employees with diabetes were invited, in a phased introduction, to join the program. Data included blood glucose (BG) values captured remotely from members via connected BG meters and medical spending claims. Participants included members (those who accepted the invitation, n = 2,261) and non-members (n = 8,741) who received health insurance benefits from three self-insured employers. Medical spending was compared between people with well-controlled (BG ≤ 154 mg/dL) and poorly controlled (BG > 154 mg/dL) diabetes. Results: Program access was associated with a 21.9% (p < 0.01) decrease in medical spending, which translates into a $88 saving per member per month at 1 year. Compared to non-members, members experienced a 10.7% (p < 0.01) reduction in diabetes-related medical spending and a 24.6% (p < 0.01) reduction in spending on office-based services. Well-controlled BG values were associated with 21.4% (p = 0.03) lower medical spending. Limitations and conclusions: Remote digital diabetes management is associated with decreased medical spending at 1 year. Reductions in spending increased with active utilization. It will be beneficial for future studies to analyze the long-term effects of the remote diabetes management program and assess impacts on patient health and well-being.

Simulation-Based Evaluation of Dose-Titration Algorithms for Rapid-Acting Insulin in Subjects with Type 2 Diabetes Mellitus Inadequately Controlled on Basal Insulin and Oral Antihyperglycemic Medications.

BACKGROUND: The purpose of this prospective, model-based simulation approach was to evaluate the impact of various rapid-acting mealtime insulin dose-titration algorithms on glycemic control (hemoglobin A1c [HbA1c]). METHODS: Seven stepwise, glucose-driven insulin dose-titration algorithms were evaluated with a model-based simulation approach by using insulin lispro. Pre-meal blood glucose readings were used to adjust insulin lispro doses. Two control dosing algorithms were included for comparison: no insulin lispro (basal insulin+metformin only) or insulin lispro with fixed doses without titration. RESULTS: Of the seven dosing algorithms assessed, daily adjustment of insulin lispro dose, when glucose targets were met at pre-breakfast, pre-lunch, and pre-dinner, sequentially, demonstrated greater HbA1c reduction at 24 weeks, compared with the other dosing algorithms. Hypoglycemic rates were comparable among the dosing algorithms except for higher rates with the insulin lispro fixed-dose scenario (no titration), as expected. The inferior HbA1c response for the "basal plus metformin only" arm supports the additional glycemic benefit with prandial insulin lispro. CONCLUSIONS: Our model-based simulations support a simplified dosing algorithm that does not include carbohydrate counting, but that includes glucose targets for daily dose adjustment to maintain glycemic control with a low risk of hypoglycemia.

A Patient-Driven Approach to Manage Mealtime Insulin Titration: Tools From the AUTONOMY Study.

PURPOSE: Patient-centric methods to support diabetes management are important to overcome barriers associated with initiating mealtime insulin. This article describes the subject-driven titration tools implemented in the AUTONOMY trial to initiate and adjust mealtime insulin dose and the methods used to apply these tools in clinical practice. CONCLUSIONS: The methods used to initiate and escalate mealtime insulin in the AUTONOMY trial proved to be safe and effective, and the patient-friendly guide to self-adjusting mealtime insulin dose may mitigate the complexities associated with treatment intensification while empowering patients to reach their glycemic goals.

Evaluation of a patient self-directed mealtime insulin titration algorithm: a US payer perspective.

Objective To model the potential economic impact of implementing the AUTONOMY once daily (Q1D) patient self-titration mealtime insulin dosing algorithm vs standard of care (SOC) among a population of patients with Type 2 diabetes living in the US. Methods Three validated models were used in this analysis: The Treatment Transitions Model (TTM) was used to generate the primary results, while both the Archimedes (AM) and IMS Core Diabetes Models (IMS) were used to test the veracity of the primary results produced by TTM. Models used data from a 'real world' representative sample of patients (2012 US National Health and Nutrition Examination Survey) that matched the characteristics of US patients enrolled in the randomized controlled trial 'AUTONOMY' cohort. The base-case time horizon was 10 years. Results The modeling results from TTM demonstrated that total costs in the base-case were reduced by $1732, with savings predicted to occur as early as year 1. Results from the three models were consistent, showing a reduction in total costs for all sensitivity analyses. Limitations Data from short-term clinical trials were used to develop long-term projections. The nature of such extrapolation leads to increased uncertainty. Conclusion The results from all three models indicate that the AUTONOMY Q1D algorithm has the potential to abate total costs as early as the first year.

AUTONOMY: the first randomized trial comparing two patient-driven approaches to initiate and titrate prandial insulin lispro in type 2 diabetes.

OBJECTIVE: To compare two self-titration algorithms for initiating and escalating prandial insulin lispro in patients with type 2 diabetes inadequately controlled on basal insulin. RESEARCH DESIGN AND METHODS: The trial was designed as two independent, multinational, parallel, open-label studies (A and B), identical in design, to provide substantial evidence of efficacy and safety in endocrine and generalist settings. Subjects were 18-85 years old (study A: N = 528; study B: N = 578), on basal insulin plus oral antidiabetic drugs for ≥3 months, and had an HbA1c 7.0% to ≤12.0% (>53.0 to ≤107.7 mmol/mol). Once optimized on insulin glargine, subjects were randomized to one of two self-titration algorithm groups adjusting lispro either every day (Q1D) or every 3 days (Q3D) for 24 weeks. The primary outcome was the change in HbA1c from baseline. The primary and secondary objectives were evaluated for the overall population and subjects ≥65 years old. RESULTS: Baseline HbA1c was similar (study A: Q1D 8.3% [67.2 mmol/mol] vs. Q3D 8.4% [68.3 mmol/mol], P = 0.453; study B: Q1D 8.3% [67.2 mmol/mol] vs. Q3D 8.4% [68.3 mmol/mol], P = 0.162). Both algorithms had significant and equivalent reductions in HbA1c from baseline (study A: Q3D -0.96% [-10.49 mmol/mol], Q1D -1.00% [-10.93 mmol/mol], Q3D-Q1D 0.04% [0.44 mmol/mol] [95% CI -0.15 to 0.22 (-1.64 to 2.40)]; study B: Q3D -0.92% [-10.06 mmol/mol], Q1D -0.98% [-10.71 mmol/mol], Q3D-Q1D 0.06% [0.66 mmol/mol] [95% CI -0.12 to 0.24 (-1.31 to 2.62)]). The incidence and rate of hypoglycemia were similar for Q3D and Q1D in both studies. In general, no clinically relevant differences were found between the two algorithms in subjects ≥65 years old in either study. CONCLUSIONS: Prandial insulin lispro can effectively and safely be initiated, by either of two self-titrated algorithms, in a variety of practice settings.

Identifying prediabetes using fasting insulin levels.

OBJECTIVE: To determine whether patients with prediabetes can be accurately and easily identified in clinical settings using a predictive clinical and laboratory model. METHODS: This retrospective study examined demographic and laboratory data from patients who had undergone 2-hour glucose testing for suspected prediabetes or diabetes between 2000 and 2004. Patients who met the diagnostic criteria for diabetes mellitus were excluded. Prediabetes was defined as a fasting glucose concentration > or = 100 mg/dL and < or = 125 mg/dL or a 2-hour postprandial glucose concentration > or = 140 mg/dL and < 200 mg/dL. Multivariate logistic regression was conducted to identify calculated or measured clinical and laboratory attributes that predict the presence of prediabetes, including fasting insulin quartiles, homeostasis model assessment of insulin resistance (HOMA-IR), and quantitative insulin sensitivity check index. RESULTS: Of 965 patients, 287 (29.7%) had prediabetes. The study population primarily consisted of white, obese, female patients. A multivariate model revealed that compared with the referent lowest quartile of fasting insulin (mu = 4.9 [+/-SD] +/-1.2 microIU/mL), subsequent insulin quartiles increased the likelihood of identifying prediabetes (quartile 2: mu = 8.0 +/-0.8 microIU/mL, odds ratio [OR] = 2.076, confidence interval [CI] = 1.241-3.273; quartile 3: mu = 12.2 +/-1.7 microIU/mL, OR = 3.151, CI = 1.981-5.015; quartile 4: mu = 25.9 +/-12.4 microIU/mL, OR = 5.035, CI = 3.122-8.122). Older age and increased diastolic blood pressure also contributed modestly to this model. Further analysis using the area under the curve revealed that at a fasting insulin level > 9.0 microIU/mL, prediabetes would be correctly identified in 80% of affected patients. A second model revealed that increased HOMA-IR index (OR = 1.303, CI = 1.205-1.410) and older age (OR = 1.037, CI = 1.024-1.05) predicted prediabetes. CONCLUSIONS: The most robust model, which used fasting insulin levels, may provide the most utility as a clinical tool because the highest quartiles suggest significantly greater likelihood of identifying prediabetes.