A comparison of two hybrid closed-loop systems in adolescents and young adults with type 1 diabetes (FLAIR): a multicentre, randomised, crossover trial.

BACKGROUND: Management of type 1 diabetes is challenging. We compared outcomes using a commercially available hybrid closed-loop system versus a new investigational system with features potentially useful for adolescents and young adults with type 1 diabetes. METHODS: In this multinational, randomised, crossover trial (Fuzzy Logic Automated Insulin Regulation [FLAIR]), individuals aged 14-29 years old, with a clinical diagnosis of type 1 diabetes with a duration of at least 1 year, using either an insulin pump or multiple daily insulin injections, and glycated haemoglobin (HbA1c) levels of 7·0-11·0% (53-97 mmol/mol) were recruited from seven academic-based endocrinology practices, four in the USA, and one each in Germany, Israel, and Slovenia. After a run-in period to teach participants how to use the study pump and continuous glucose monitor, participants were randomly assigned (1:1) using a computer-generated sequence, with a permuted block design (block sizes of two and four), stratified by baseline HbA1c and use of a personal MiniMed 670G system (Medtronic) at enrolment, to either use of a MiniMed 670G hybrid closed-loop system (670G) or the investigational advanced hybrid closed-loop system (Medtronic) for the first 12-week period, and then participants were crossed over with no washout period, to the other group for use for another 12 weeks. Masking was not possible due to the nature of the systems used. The coprimary outcomes, measured with continuous glucose monitoring, were proportion of time that glucose levels were above 180 mg/dL (>10·0 mmol/L) during 0600 h to 2359 h (ie, daytime), tested for superiority, and proportion of time that glucose levels were below 54 mg/dL (<3·0 mmol/L) calculated over a full 24-h period, tested for non-inferiority (non-inferiority margin 2%). Analysis was by intention to treat. Safety was assessed in all participants randomly assigned to treatment. This trial is registered with ClinicalTrials.gov, NCT03040414, and is now complete. FINDINGS: Between June 3 and Aug 22, 2019, 113 individuals were enrolled into the trial. Mean age was 19 years (SD 4) and 70 (62%) of 113 participants were female. Mean proportion of time with daytime glucose levels above 180 mg/dL (>10·0 mmol/L) was 42% (SD 13) at baseline, 37% (9) during use of the 670G system, and 34% (9) during use of the advanced hybrid closed-loop system (mean difference [advanced hybrid closed-loop system minus 670G system] -3·00% [95% CI -3·97 to -2·04]; p<0·0001). Mean 24-h proportion of time with glucose levels below 54 mg/dL (<3·0 mmol/L) was 0·46% (SD 0·42) at baseline, 0·50% (0·35) during use of the 670G system, and 0·46% (0·33) during use of the advanced hybrid closed-loop system (mean difference [advanced hybrid closed-loop system minus 670G system] -0·06% [95% CI -0·11 to -0·02]; p<0·0001 for non-inferiority). One severe hypoglycaemic event occurred in the advanced hybrid closed-loop system group, determined to be unrelated to study treatment, and none occurred in the 670G group. INTERPRETATION: Hyperglycaemia was reduced without increasing hypoglycaemia in adolescents and young adults with type 1 diabetes using the investigational advanced hybrid closed-loop system compared with the commercially available MiniMed 670G system. Testing an advanced hybrid closed-loop system in populations that are underserved due to socioeconomic factors and testing during pregnancy and in individuals with impaired awareness of hypoglycaemia would advance the effective use of this technology FUNDING: National Institute of Diabetes and Digestive and Kidney Diseases.

Highly selective pressure-dependent (transfer) hydrogenative depolymerization of polybutylene succinate.

Ru-MACHO®-BH is an effective catalyst for controlled depolymerization of polybutylene succinate. Under low pressure hydrogen the catalyst produces gamma-butyrolactone via a novel transfer hydrogenation wherein dehydrogenation and hydrogenation deconstruct the polymer chain. Simply increasing the hydrogen pressure selectively generates 1,4-butanediol.

Differential Effects of Type 2 Diabetes Treatment Regimens on Diabetes Distress and Depressive Symptoms in the Glycemia Reduction Approaches in Diabetes: A Comparative Effectiveness Study (GRADE).

OBJECTIVE: We evaluated whether adding basal insulin to metformin in adults with early type 2 diabetes mellitus (T2DM) would increase emotional distress relative to other treatments. RESEARCH DESIGN AND METHODS: The Glycemia Reduction Approaches in Diabetes: A Comparative Effectiveness Study (GRADE) of adults with T2DM of <10 years' duration, HbA1c 6.8-8.5%, and taking metformin monotherapy randomly assigned participants to add insulin glargine U-100, sulfonylurea glimepiride, the glucagon-like peptide-1 receptor agonist liraglutide, or the dipeptidyl peptidase 4 inhibitor sitagliptin. The Emotional Distress Substudy enrolled 1,739 GRADE participants (mean [SD] age 58.0 [10.2] years, 32% female, 56% non-Hispanic White, 18% non-Hispanic Black, 17% Hispanic) and assessed diabetes distress and depressive symptoms every 6 months. Analyses examined differences at 1 year and over the 3-year follow-up. RESULTS: Across treatments, diabetes distress (-0.24, P < 0.0001) and depressive symptoms (-0.67, P < 0.0001) decreased over 1 year. Diabetes distress was lower at 1 year for the glargine group than for the other groups combined (-0.10, P = 0.002). Diabetes distress was also lower for liraglutide than for glimepiride or sitagliptin (-0.10, P = 0.008). Over the 3-year follow-up, there were no significant group differences in total diabetes distress; interpersonal diabetes distress remained lower for those assigned to liraglutide. No significant differences were observed for depressive symptoms. CONCLUSIONS: Contrary to expectations, this randomized trial found no evidence for a deleterious effect of basal insulin on emotional distress. Glargine lowered diabetes distress modestly at 1 year rather than increasing it. Liraglutide also reduced diabetes distress at 1 year. Results can inform treatment decisions for adults with early T2DM.

The Use of Rescue Insulin in the Glycemia Reduction Approaches in Diabetes: A Comparative Effectiveness Study (GRADE).

OBJECTIVE: To describe rescue insulin use and associated factors in the Glycemia Reduction Approaches in Diabetes: A Comparative Effectiveness Study (GRADE). RESEARCH DESIGN AND METHODS: GRADE participants (type 2 diabetes duration <10 years, baseline A1C 6.8%-8.5% on metformin monotherapy, N = 5,047) were randomly assigned to insulin glargine U-100, glimepiride, liraglutide, or sitagliptin and followed quarterly for a mean of 5 years. Rescue insulin (glargine or aspart) was to be started within 6 weeks of A1C >7.5%, confirmed. Reasons for delaying rescue insulin were reported by staff-completed survey. RESULTS: Nearly one-half of GRADE participants (N = 2,387 [47.3%]) met the threshold for rescue insulin. Among participants assigned to glimepiride, liraglutide, or sitagliptin, rescue glargine was added by 69% (39% within 6 weeks). Rescue aspart was added by 44% of glargine-assigned participants (19% within 6 weeks) and by 30% of non-glargine-assigned participants (14% within 6 weeks). Higher A1C values were associated with adding rescue insulin. Intention to change health behaviors (diet/lifestyle, adherence to current treatment) and not wanting to take insulin were among the most common reasons reported for not adding rescue insulin within 6 weeks. CONCLUSIONS: Proportionately, rescue glargine, when required, was more often used than rescue aspart, and higher A1C values were associated with greater rescue insulin use. Wanting to use noninsulin strategies to improve glycemia was commonly reported, although multiple factors likely contributed to not using rescue insulin. These findings highlight the persistent challenge of intensifying type 2 diabetes treatment with insulin, even in a clinical trial.

GAD65Abs Are Not Associated With Beta-Cell Dysfunction in Patients With T2D in the GRADE Study.

Context: Autoantibodies directed against the 65-kilodalton isoform of glutamic acid decarboxylase (GAD65Abs) are markers of autoimmune type 1 diabetes (T1D) but are also present in patients with Latent Autoimmune Diabetes of Adults and autoimmune neuromuscular diseases, and also in healthy individuals. Phenotypic differences between these conditions are reflected in epitope-specific GAD65Abs and anti-idiotypic antibodies (anti-Id) against GAD65Abs. We previously reported that 7.8% of T2D patients in the GRADE study have GAD65Abs but found that GAD65Ab positivity was not correlated with beta-cell function, glycated hemoglobin (HbA1c), or fasting glucose levels. Context: In this study, we aimed to better characterize islet autoantibodies in this T2D cohort. This is an ancillary study to NCT01794143. Methods: We stringently defined GAD65Ab positivity with a competition assay, analyzed GAD65Ab-specific epitopes, and measured GAD65Ab-specific anti-Id in serum. Results: Competition assays confirmed that 5.9% of the patients were GAD65Ab positive, but beta-cell function was not associated with GAD65Ab positivity, GAD65Ab epitope specificity or GAD65Ab-specific anti-Id. GAD65-related autoantibody responses in GRADE T2D patients resemble profiles in healthy individuals (low GAD65Ab titers, presence of a single autoantibody, lack of a distinct epitope pattern, and presence of anti-Id to diabetes-associated GAD65Ab). In this T2D cohort, GAD65Ab positivity is likely unrelated to the pathogenesis of beta-cell dysfunction. Conclusion: Evidence for islet autoimmunity in the pathophysiology of T2D beta-cell dysfunction is growing, but T1D-associated autoantibodies may not accurately reflect the nature of their autoimmune process.

Expert Panel Recommendations for a Standardized Ambulatory Glucose Profile Report for Connected Insulin Pens.

Background: Connected insulin pens capture data on insulin dosing/timing and can integrate with continuous glucose monitoring (CGM) devices with essential insulin and glucose metrics combined into a single platform. Standardization of connected insulin pen reports is desirable to enhance clinical utility with a single report. Methods: An international expert panel was convened to develop a standardized connected insulin pen report incorporating insulin and glucose metrics into a single report containing clinically useful information. An extensive literature review and identification of examples of current connected insulin pen reports were performed serving as the basis for creation of a draft of a standardized connected insulin pen report. The expert panel participated in three virtual standardization meetings and online surveys. Results: The Ambulatory Glucose Profile (AGP) Report: Connected Insulin Pen brings all clinically relevant CGM-derived glucose and connected insulin pen metrics into a single simplified two-page report. The first page contains the time in ranges bar, summary of key insulin and glucose metrics, the AGP curve, and detailed basal (long-acting) insulin assessment. The second page contains the bolus (mealtime and correction) insulin assessment periods with information on meal timing, insulin-to-carbohydrate ratio, average bolus insulin dose, and number of days with bolus doses recorded. The report's second page contains daily glucose profiles with an overlay of the timing and amount of basal and bolus insulin administered. Conclusion: The AGP Report: Connected Insulin Pen is a standardized clinically useful report that should be considered by companies developing connected pen technology as part of their system reporting/output.

Comprehensive Telehealth Model to Support Diabetes Self-Management.

Importance: As the number of patients with diabetes continues to increase in the United States, novel approaches to clinical care access should be considered to meet the care needs for this population, including support for diabetes-related technology. Objective: To evaluate a virtual clinic to facilitate comprehensive diabetes care, support continuous glucose monitoring (CGM) integration into diabetes self-management, and provide behavioral health support for diabetes-related issues. Design, Setting, and Participants: This cohort study was a prospective, single-arm, remote study involving adult participants with type 1 or type 2 diabetes who were referred through community resources. The study was conducted virtually from August 24, 2020, to May 26, 2022; analysis was conducted at the clinical coordinating center. Intervention: Training and education led by a Certified Diabetes Care and Education Specialist for CGM use through a virtual endocrinology clinic structure, which included endocrinologists and behavioral health team members. Main Outcomes and Measures: Main outcomes included CGM-measured mean glucose level, coefficient of variation, and time in range (TIR) of 70 to 180 mg/dL, time with values greater than 180 mg/dL or 250 mg/dL, and time with values less than 70 mg/dL or 54 mg/dL. Hemoglobin A1c was measured at baseline and at 12 and 24 weeks. Results: Among the 234 participants, 160 had type 1 diabetes and 74 had type 2 diabetes. The mean (SD) age was 47 (14) years, 123 (53%) were female, and median diabetes duration was 20 years. Median (IQR) CGM use over 6 months was 96% (91%-98%) for participants with type 1 diabetes and 94% (85%-97%) for those with type 2 diabetes. Mean (SD) hemoglobin A1c (HbA1c) in those with type 1 diabetes decreased from 7.8% (1.6%) at baseline to 7.1% (1.0%) at 3 months and 7.1% (1.0%) at 6 months (mean change from baseline to 6 months, -0.6%, 95% CI, -0.8% to -0.5%; P < .001), with an 11% mean TIR increase over 6 months (95% CI, 9% to 14%; P < .001). Mean HbA1c in participants with type 2 diabetes decreased from 8.1% (1.7%) at baseline to 7.1% (1.0%) at 3 months and 7.1% (0.9%) at 6 months (mean change from baseline to 6 months, -1.0%; 95% CI, -1.4% to -0.7%; P < .001), with an 18% TIR increase over 6 months (95% CI, 13% to 24%; P < .001). In participants with type 1 diabetes, mean percentage of time with values less than 70 mg/dL and less than 54 mg/dL decreased over 6 months by 0.8% (95% CI, -1.2% to -0.4%; P = .001) and by 0.3% (95% CI, -0.5% to -0.2%, P < .001), respectively. In the type 2 diabetes group, hypoglycemia was rare (mean [SD] percentage of time <70 mg/dL, 0.5% [0.6%]; and <54 mg/dL, 0.07% [0.14%], over 6 months). Conclusions and Relevance: Results from this cohort study demonstrated clinical benefits associated with implementation of a comprehensive care model that included diabetes education. This model of care has potential to reach a large portion of patients with diabetes, facilitate diabetes technology adoption, and improve glucose control.

Randomized comparison of self-monitored blood glucose (BGM) versus continuous glucose monitoring (CGM) data to optimize glucose control in type 2 diabetes.

AIMS: Evaluate whether structured BGM testing (BGM) or real-time CGM (CGM) lead to improved glucose control (A1c). Determine which approach optimized glucose control more effectively. METHODS-MULTI-ARM PARALLEL: trial of three type 2 diabetes (T2D) therapies ± metformin: (1) sulfonylurea (SU), (2) incretin (DPP4 inhibitor or GLP-1 agonist), or (3) insulin. After a baseline CGM, 114 adult subjects were randomized to either BGM (4 times daily) or CGM (24/7) for 16 weeks with therapies adjusted every 4 weeks. RESULTS: A1c means decreased from 8.19 to 7.07 (1.12% difference) with CGM (n = 59) and 7.85 to 7.03 (0.82% difference) with BGM (n = 55) (p < 0.001). BGM and CGM groups showed significant improvements in time in range and glucose variability-with no significant difference between the two groups. Clinically important hypoglycemia (<50 mg/dL) was significantly reduced for the CGM group compared with BGM (p < 0.01), particularly in subjects taking insulin or therapies with higher hypoglycemic risk (SU). CONCLUSION: In T2D, structured, consistent use of glucose data regardless of device (structured BGM or CGM) leads to improvements in A1c control. CGM is more effective than BGM in minimizing hypoglycemia particularly for those using higher hypoglycemic risk therapies.

A Comparison of Postprandial Glucose Control in the Medtronic Advanced Hybrid Closed-Loop System Versus 670G.

Background: We recently reported that use of an "advanced" hybrid closed-loop system reduced hyperglycemia without increasing hypoglycemia compared to a first-generation system. The aim of this analysis was to evaluate whether this improved performance was specifically related to better mealtime glycemic control. Methods: We conducted a secondary analysis of postprandial glycemic control in an open-label, multinational, randomized crossover trial of 112 participants with type 1 diabetes, aged 14-29, of the Medtronic MiniMed™ 670G hybrid closed-loop system (670G) versus the Medtronic advanced hybrid closed-loop (AHCL) system, for 12 weeks each. We compared glycemic and insulin delivery metrics over a 3 h horizon across all meals to assess system performance and outcomes. Results: Overall meal size and premeal insulin on board were similar during run-in and between 670G and AHCL arms. Compared with 670G arm, premeal, peak, and mean glucose levels were numerically lower in the AHCL arm (167 ± 23, 231 ± 23, and 177 ± 20 mg/dL vs. 175 ± 23, 235 ± 23, and 180 ± 19 mg/dL, respectively), with a trend to lower hyperglycemia level 2 in AHCL arm. Adjusting for premeal glucose level, all postmeal outcomes between 670G and AHCL were statistically similar. Prandial insulin delivery also was similar in both treatment arms (21 ± 9 vs. 23 ± 10 U), with a shift in basal/bolus ratio from 28%/71% in 670G arm to 20%/80% in AHCL arm. Conclusions: Reduced hyperglycemia with AHCL compared to 670G was not related to early postprandial glycemic excursions after adjusting for premeal glucose level (<3 h after meal), but likely to later (>3 h) postprandial or overnight improvements. Further refinements to mealtime bolus algorithms and strategies may more optimally control prandial glycemic excursions.

Comparing Patch vs Pen Bolus Insulin Delivery in Type 2 Diabetes Using Continuous Glucose Monitoring Metrics and Profiles.

OBJECTIVE: CeQur Simplicity™ (CeQur, Marlborough, MA) is a 3-day insulin delivery patch designed to meet mealtime insulin requirements. A recently reported 48-week, randomized, multicenter, interventional trial compared efficacy, safety and self-reported outcomes in 278 adults with type 2 diabetes (T2D) on basal insulin therapy who initiated and managed mealtime insulin therapy with a patch pump versus insulin pen. We assessed changes in key glycemic metrics among a subset of patients who wore a continuous glucose monitoring (CGM) device. METHODS: Study participants (patch, n = 49; pen, n = 48) wore a CGM device in masked setting during the baseline period and prior to week 24. Glycemic control was assessed using international consensus guidelines for percentage of Time In Range (%TIR: >70% at 70-180 mg/dL), Time Below Range (%TBR: <4% at <70 mg/dL; <1% at <54 mg/dL), and Time Above Range (%TAR: <25% at >180 mg/dL; <5% at >250 mg/dL). RESULTS: Both the patch and pen groups achieved recommended targets in %TIR (74.1% ± 18.7%, 75.2 ± 16.1%, respectively) and marked reductions in %TAR >180 mg/dL (21.1% ± 19.9%, 19.7% ± 17.5%, respectively) but with increased %TBR <70 mg/dL (4.7% ± 5.2%, 5.1 ± 5.8, respectively), all P < .0001. No significant between-group differences in glycemic improvements or adverse events were observed. CONCLUSIONS: CGM confirmed that the patch or pen can be used to safely initiate and optimize basal-bolus therapy using a simple insulin adjustment algorithm with SMBG. Preference data suggest that use of the patch vs pen may enhance treatment adherence.

Continuous Glucose Monitoring in Adults With Type 1 Diabetes With 35 Years Duration From the DCCT/EDIC Study.

OBJECTIVE: We evaluated blinded continuous glucose monitoring (CGM) profiles in a subset of adults with type 1 diabetes from the Diabetes Control and Complications Trial/Epidemiology of Diabetes Interventions and Complications (DCCT/EDIC) study to characterize the frequency of glycemic excursions and contributing factors. RESEARCH DESIGN AND METHODS: CGM-derived metrics were compared for daytime and nighttime periods using blinded CGM for a minimum of 6.5 days (average 11.9 days) and correlated with HbA1c levels, routine use of diabetes devices, and other characteristics in 765 participants. RESULTS: Participants were 58.9 ± 6.5 years of age with diabetes duration 36.8 ± 4.9 years and HbA1c 7.8 ± 1.2%; 58% used insulin pumps, and 27% used personal, unblinded CGM. Compared with daytime, nighttime mean sensor glucose was lower, percent time in range 70-180 mg/dL (TIR) was similar, and hypoglycemia was more common. Over the entire recording period, only 9% of the 765 participants achieved >70% TIR and only 28% achieved <1% of observations of <54 mg/dL. Indeed, participants with the highest percentage of hypoglycemia had the lowest HbA1c levels. However, use of insulin pumps and CGM decreased the percent time at <54 mg/dL. CONCLUSIONS: In adults with long-standing type 1 diabetes, short-term blinded CGM profiles revealed frequent clinically significant hypoglycemia (<54 mg/dL) during the night and more time in hyperglycemia during the day. The small subset of participants using routine CGM and insulin pumps had fewer hypoglycemic and hyperglycemic excursions and lower HbA1c levels. Thus, strategies to lower meal-stimulated hyperglycemia during the day and prevent hypoglycemia at night are relevant clinical goals in older patients with type 1 diabetes.

Islet Autoimmunity is Highly Prevalent and Associated With Diminished ß-Cell Function in Patients With Type 2 Diabetes in the Grade Study.

Islet autoimmunity may contribute to ß-cell dysfunction in type 2 diabetes (T2D). Its prevalence and clinical significance have not been rigorously determined. In this ancillary study to the Glycemia Reduction Approaches in Diabetes-A Comparative Effectiveness (GRADE) Study, we investigated the prevalence of cellular and humoral islet autoimmunity in patients with T2D duration 4·0±3·0 y, HbA1c 7·5±0·5% on metformin alone. We measured T cell autoreactivity against islet proteins, islet autoantibodies against GAD65, IA2, ZnT8, and ß-cell function. Cellular islet autoimmunity was present in 41·3%, humoral islet autoimmunity in 13·5%, and both in 5·3%. ß-cell function calculated as iAUC-CG and ΔC-peptide(0- 30)/Δglucose(0-30) from an oral glucose tolerance test was lower among T cell-positives (T+) than T cell-negatives (T-) using two different adjustments for insulin sensitivity (iAUC-CG: 13·2% [95% CI 0·3, 24·4%] or 11·4% [95% CI 0·4, 21·2%] lower; ΔC-peptide(0-30)/Δglucose(0-30)) 19% [95% CI 3·1, 32·3%] or 17·7% [95% CI 2·6, 30·5%] lower). T+ patients had 17% higher HbA1c (95% CI 0·07, 0·28) and 7·7 mg/dL higher fasting plasma glucose levels (95% CI 0·2,15·3) than T- patients. We conclude that islet autoimmunity is much more prevalent in T2D patients than previously reported. T cell-mediated autoimmunity is associated with diminished ß-cell function and worse glycemic control.

Effect of Professional CGM (pCGM) on Glucose Management in Type 2 Diabetes Patients in Primary Care.

BACKGROUND: Little data exists regarding the impact of continuous glucose monitoring (CGM) in the primary care management of type 2 diabetes (T2D). We initiated a quality improvement (QI) project in a large healthcare system to determine the effect of professional CGM (pCGM) on glucose management. We evaluated both an MD and RN/Certified Diabetes Care and Education Specialist (CDCES) Care Model. METHODS: Participants with T2D for >1 yr., A1C ≥7.0% to <11.0%, managed with any T2D regimen and willing to use pCGM were included. Baseline A1C was collected and participants wore a pCGM (Libre Pro) for up to 2 weeks, followed by a visit with an MD or RN/CDCES to review CGM data including Ambulatory Glucose Profile (AGP) Report. Shared-decision making was used to modify lifestyle and medications. Clinic follow-up in 3 to 6 months included an A1C and, in a subset, a repeat pCGM. RESULTS: Sixty-eight participants average age 61.6 years, average duration of T2D 15 years, mean A1C 8.8%, were identified. Pre to post pCGM lowered A1C from 8.8% ± 1.2% to 8.2% ± 1.3% (n=68, P=0.006). The time in range (TIR) and time in hyperglycemia improved along with more hypoglycemia in the subset of 37 participants who wore a second pCGM. Glycemic improvement was due to lifestyle counseling (68% of participants) and intensification of therapy (65% of participants), rather than addition of medications. CONCLUSIONS: Using pCGM in primary care, with an MD or RN/CDCES Care Model, is effective at lowering A1C, increasing TIR and reducing time in hyperglycemia without necessarily requiring additional medications.

Key Steps Toward a Promotional Communications Strategy: Collaboration Best Practices for Teams Creating Promotional Materials and Regulatory Colleagues.

A promotional communications strategy is considered early in prescription medical product development by commercial disciplines (e.g., commercial/marketing) and informs promotional materials to key stakeholders such as healthcare providers and patients. Health economics and outcomes research (HEOR) is a scientific discipline that is also responsible for the generation of promotional materials to other key stakeholders such as payors. The overarching promotional strategy benefits from consistent partnerships with regulatory affairs colleagues, culminating in cost savings and patient-centric promotional materials. Yet there is a paucity of published content that details effective collaboration between promotional teams and regulatory colleagues prior to medical/legal/regulatory (MLR) review. The following review aims to showcase such organizational innovation from the perspective of teams developing promotional materials (i.e., commercial and HEOR). Behind-the-scenes marketing activities are described in relation to the following key steps that build the strategy's foundation: insight gathering from key stakeholders; sub-strategy development; tactic identification; and promotional message development. Integration of regulatory colleagues with teams developing promotional materials is imperative to accomplish these key steps prior to any MLR review. Finally, four themes in best practices for collaboration with regulatory colleagues are shared from the perspective of commercial disciplines and HEOR, alongside a real-world example for each: (1) Alignment of Strategies; (2) Shared Process & Tools; (3) Creative Problem-Solving; and (4) Culture of Connecting.

Innovation in Clinical Trial Design and Product Promotion: Evolving the Patient Perspective With Regulatory and Technological Advances.

Clinical trials are evolving to innovative designs and capabilities. Clinical outcomes from pivotal trials are the backbone of good marketing practices. Novel study designs included in product labels and the uptick of innovative technology foreshadow a crescendo of patient empowerment not only in clinical trials, but also in the real-world setting. The following review will initially explore the dynamic relationship between clinical development and commercial teams. How clinical development is evolving to increase patient-focused drug development and regulatory review will then be reviewed via recent legislation; the 21st Century Cures Act is one glimpse at innovative inclusion of the patient perspective via patient experience data, related information, and real-world evidence. Trends in direct-to-consumer technology such as digital health will be also appraised. Predictions are made on how the aforementioned advances may create challenges and opportunities to promotional practices, including crosscollaboration of marketing teams and planning for the next level of patient empowerment. Finally, a hypothetical scenario is provided to illustrate marketing/commercial dynamics when planning for and promoting data from an innovative trial design with real-world evidence.

Diabetes Telehealth Solutions: Improving Self-Management Through Remote Initiation of Continuous Glucose Monitoring.

The purpose of this study was to evaluate feasibility of initiating continuous glucose monitoring (CGM) through telehealth as a means of expanding access. Adults with type 1 diabetes (N = 27) or type 2 diabetes using insulin (N = 7) and interest in starting CGM selected a CGM system (Dexcom G6 or Abbott FreeStyle Libre), which they received by mail. CGM was initiated with a certified diabetes care and education specialist providing instruction via videoconference or phone. The primary outcome was days per week of CGM use during the last 4 weeks. Hemoglobin A1c (HbA1c) was measured at baseline and 12 weeks. Participant self-reported outcome measures were also evaluated. All 34 participants (mean age, 46 ±â€…18 years; 53% female, 85% white) were using CGM at 12 weeks, with 94% using CGM at least 6 days per week during weeks 9 to 12. Mean HbA1c decreased from 8.3 ±â€…1.6 at baseline to 7.2 ±â€…1.3 at 12 weeks (P < .001) and mean time in range (70-180 mg/dL, 3.9-10.0 mmol/L) increased from an estimated 48% ±â€…18% to 59% ±â€…20% (P < .001), an increase of approximately 2.7 hours/day. Substantial benefits of CGM to quality of life were observed, with reduced diabetes distress, increased satisfaction with glucose monitoring, and fewer perceived technology barriers to management. Remote CGM initiation was successful in achieving sustained use and improving glycemic control after 12 weeks as well as improving quality-of-life indicators. If widely implemented, this telehealth approach could substantially increase the adoption of CGM and potentially improve glycemic control for people with diabetes using insulin.

The Relationships Between Time in Range, Hyperglycemia Metrics, and HbA1c.

BACKGROUND: As the use of continuous glucose monitoring (CGM) increases, there is a need to better understand key metrics of time in range 70-180 mg/dL (TIR70-180) and hyperglycemia and how they relate to hemoglobin A1c (A1C). METHODS: Analyses were conducted utilizing datasets from four randomized trials encompassing 545 adults with type 1 diabetes (T1D) who had central-laboratory measurements of A1C. CGM metrics were calculated and compared with each other and A1C cross-sectionally and longitudinally. RESULTS: Correlations among CGM metrics (TIR70-180, time >180 mg/dL, time >250 mg/dL, mean glucose, area under the curve above 180 mg/dL, high blood glucose index, and time in range 70-140 mg/dL) were typically 0.90 or greater. Correlations of each metric with A1C were lower (absolute values 0.66-0.71 at baseline and 0.73-0.78 at month 6). For a given TIR70-180 percentage, there was a wide range of possible A1C levels that could be associated with that TIR70-180 level. On average, a TIR70-180 of 70% and 50% corresponded with an A1C of approximately 7% and 8%, respectively. There also was considerable spread of change in A1C for a given change in TIR70-180, and vice versa. An increase in TIR70-180 of 10% (2.4 hours per day) corresponded to a decrease in A1C of 0.6%, on average. CONCLUSIONS: In T1D, CGM measures reflecting hyperglycemia (including TIR and mean glucose) are highly correlated with each other but only moderately correlated with A1C. For a given TIR or change in TIR there is a wide range of possible corresponding A1C values.

Utilizing the Ambulatory Glucose Profile to Standardize and Implement Continuous Glucose Monitoring in Clinical Practice.

Use of continuous glucose monitoring (CGM) is recognized as a valuable component of diabetes self-management and is increasingly considered a standard of care for individuals with diabetes who are treated with intensive insulin therapy. As the clinical use of CGM technology expands, consistent and standardized glycemic metrics and glucose profile visualization have become increasingly important. A common set of CGM metrics has been proposed by an international expert panel in 2017, including standard definitions of time in ranges, glucose variability, and adequacy of data collection. We describe the core CGM metrics, as well as the standardized glucose profile format consolidating 2 weeks of CGM measurements, referred to as the ambulatory glucose profile (AGP), which was also recommended by the CGM expert panel. We present an updated AGP report featuring the core CGM metrics and a visualization of glucose patterns that need clinical attention. New tools for use by clinicians and patients to interpret AGP data are reviewed. Strategies based on the authors' experience in implementing CGM technology across the clinical care spectrum are highlighted.