American Diabetes Association 74th Scientific Sessions

June 13-17, 2014; San Francisco, CA Day #3 Highlights - Draft

Executive Highlights

First of all, a very happy belated Father’s Day to all of the dads at the conference! The Moscone Center was teeming with activity from the early morning on ADA 2014’s third day of sessions. A special congratulations to those of you who made it out to the 6:30 AM 5K and kept your energy up throughout the day – including our very own Jenny Lee!

We were thrilled to see the esteemed Dr. Daniel Drucker (Lunenfeld-Tanenbaum Research Institute, Toronto, Canada) accept this year’s Banting Award – his tales of his work on incretin therapies set an uplifting tone for the rest of the day. Late-breaking posters enjoyed their debut, and oh boy was there a lot to see. For the first time, we saw phase 3 data on DPP-4 inhibitor/SGLT-2 inhibitor combinations from AZ and Lilly/BI, with some of the strongest efficacy we’ve seen out of oral drugs (along with a few surprises). We also saw new clinical data on ultra-long-acting basal insulin, SGLT-1/2 dual inhibition, novel liquid glucagon receptor agonists, and Intarcia’s exenatide mini-pump.  

Sunday was ADA 2014’s big artificial pancreas day – in the words of the JDRF’s Dr. Aaron Kowalski, “we’re on the cusp.” On CGM, Dexcom’s new accuracy data on the G4AP stole the show, while Medtronic’s poster on the OpT2mise trial provided hope for better insulin delivery in type 2 diabetes.

Featured below are our top ten tech highlights, top five drug highlights, and a few other tidbits we knew you would want to have. Also included below are detailed reports on some of the day’s most important posters and presentations. If you are in town and are having trouble picking what sessions to attend on Monday, look no further than our conference preview. And of course, please come on Monday evening to our TCOYD / the diaTribe Foundation ADA gathering at 6:30 pm at the St. Francis Hotel – we can’t wait to see you!

Top 10 Technology Highlights

1. In the afternoon artificial pancreas orals, Dr. Steven Russell (MGH, Boston, MA) shared topline results from the bionic pancreas Summer Camp and Beacon Hill studies, which were simultaneously published online in the New England Journal of Medicine (“Outpatient Glycemic Control with a Bionic Pancreas in Type 1 Diabetes”). Though his topline results presentation was similar to those given at ATTD 2014, it was terrific to see the excitement in the room among fellow researchers – said the renowned Dr. Roman Hovorka to Dr. Russell, in his inimitable, gracious style,  “Congrats on the publication; it’s brilliant for the field and for you as well.” In his talk, Dr. Russell emphasized the impressive average level of glucose control during closed loop (133 vs. 159 mg/dl in adults; 138 vs. 157 mg/dl in adolescents), which was simultaneously achieved with no increase/significant reduction in hypoglycemia (4% vs. 7% in adults; 6% vs. 8% in adolescents). Dr. Russell emphasized the challenging circumstances of these studies (strong usual care control in the camp environment; 45% of the Beacon Hill adults wore their own CGM during usual care) and the robustness of the control algorithm (adaptable over time; initializes based on weight). The team’s first home use study will begin tomorrow (!) – these randomized, crossover experiments in adults with type 1 diabetes will compare 11 days with the Bionic Pancreas to 11 days of usual care. The multicenter study will take place at MGH, UNC, Stanford, and UMass, with 12 subjects expected per site. Patients must either work or go to school at the institutions, and their home must be within 30 minutes of the center. Notably, they are allowed to travel as far as 60 minutes driving time away. Remote monitoring will be quite minimal. This study is certainly one of the more ambitious and real-world outpatient studies to date, and we cannot wait to see hear the results assessed.

2. We covered three notable technology posters today, two on novel CGM and one on insulin delivery in type 2 diabetes:

  • Dexcom's exciting late-breaking poster #75 shared clinical data from 51 patients that wore a version of the G4 Platinum with an improved algorithm (called “G4AP” in previous Dexcom presentations). Overall G4AP MARD vs. YSI was an impressive 9.0%, compared to the Contour USB’s MARD of 5.6% vs. YSI. Notably, G4AP and the Contour USB had a similar mean absolute difference (MAD) in hypoglycemia vs. YSI: 6.4 mg/dl and 4.2 mg/dl, respectively. In addition, the Clarke Error Grid data vs. YSI suggested G4 AP is indeed approaching the clinical accuracy of fingersticks– A+B Zone data was nearly identical (99.5% with G4AP vs. 99.6% with the Contour USB) and A-Zone accuracy was quite similar (92% vs. 99%).
  • Medtronic's late-breaking poster #102 presented the long-awaited results from the randomized, six-month Opt2mise trial, comparing insulin pump therapy (n=168) to MDI (n=163) in type 2 patients in poor control. From a baseline of 9.0%, A1c declined by 1.1% in those in the pump group vs. a 0.4% decline in the MDI group (p<0.001) after 27 weeks; 55% of the pump group achieved an A1c <8% vs. 28% of the MDI group. CGM data (baseline vs. six months) revealed no significant increase in hypoglycemia. Meanwhile, importantly, the group on pumps used 20% less insulin than those on MDI (p<0.001). The insulin usage data is very important since we surmise it would be possible to show a higher ROI stemming from type 2 patients on insulin using a pump, since it would cost fewer funds due to less expensive insulin.
  • In poster #846, Roche shared comparison data on its novel CGM vs. the Dexcom G4 Platinum. The G4 had numerically higher MARD than the Roche prototype in every category of glycemic rate of change assessed.

3. A who’s who of closed-loop researchers, industry, non-profit organizations, and patient advocates gathered at the annual JDRF/NIH Closed-Loop Research Meeting. This engaging evening featured a presentation from JDRF’s Dr. Aaron Kowalski on the past year of closed-loop research, followed by three industry perspectives (Medtronic, Animas, Dose Safety), and a closing panel that included Drs. Stacey Anderson, Bruce Buckingham, Roman Hovorka, Moshe Phillip, and patients Ms. Kelly Close, Tia Geri, and Willa Spalter. Dr. Kowalski summarized the state of the field quite well in his talk, “We’re right on the cusp. People are wearing closed loop at home, and it is safer than what we’re doing right now. We’ve got to drive towards commercialization. JDRF is working with industry, working with the FDA, and already working with payers, to drive closed loop systems into commercial embodiments.” The latter was addressed in three short presentations from industry reps Mr. Lane Desborough (Medtronic), Dr. Ramakrishna Venugopalan (Animas), and Mr. Bob Kircher (Dose Safety, an artificial pancreas software startup). The tone of their presentations was somewhat negative, centering on all the challenges around safety, robustness, and everything that can go wrong. This contrasted with the second panel, which featured off-the-charts enthusiasm from patients and closed-loop researchers. We especially appreciated the last question, from Tidepool’s Mr. Brandon Arbiter:

Q: Based on your most recent trial experience and what actually went wrong, would you be comfortable commercializing the closed-loop device you used?

Dr. Moshe Phillip: I think we are ready to commercialize the night. No question about it. It prevents hypoglycemia, provides tighter control, and influences the entire day. The night is ready. Waiting to solve the challenges of the day before seeking approval is wrong.

Dr. Bruce Buckingham: We would be ready if the connectivity was ready. If it was, I would go for 24-hour closed-loop control. We aren’t aiming for perfection during the day, but a treat-to-range system would be good.

Dr. Roman Hovorka: We are ready now. It doesn’t mean it will happen soon, because there are other considerations.

Ms. Kelly Close: We have made amazing progress – I would advocate for conditional approval or make people sign something!

Ms. Willa Spalter: Nothing is perfect, but I definitely would sign up. It’s much better than what everybody else is wearing now.

Ms. Tia Geri: Things go wrong with what we use every day. So why not give people the best things that we have?

4. In one of the most exciting artificial-pancreas talks we’ve seen all year, Dr. Hood Thabit (University of Cambridge, Cambridge, United Kingdom) shared data from a four-week, home-use study of overnight closed-loop control in adults with type 1 diabetes who used pump therapy (n=24). Overnight closed-loop control, compared to open-loop CGM/pump therapy, led to statistically significantly more overnight time in target 70-144 mg/dl (53% vs. 39%), lower overnight mean glucose (148 mg/dl vs. 162 mg/dl), lower mean glucose at 7 am (130 vs 158 mg/dl), and more 24-hour time in target (66% vs. 59%). Rates of nocturnal hypoglycemia <70 mg/dl were low (1.8% vs. 2.1%) and not significantly different between groups, due to optimization of open-loop therapy. The only notable side effects were two severe hypoglycemic episodes that occurred during overnight during interruptions of closed-loop connectivity. Both patients recovered fully, but Dr. Thabit suggested system connectivity as the main factor that needs improvement: communication to the insulin pump was interrupted on roughly 20% of closed-loop nights. See below for details.

5. Dr. Lalantha Leelarathna, MD (University of Cambridge, Cambridge, UK) shared exciting results from a feasibility study of a closed loop system under free-living home conditions for seven days and nights in adults with type 1 diabetes (n=17). Patients in the closed loop arm spent significantly more time in the target range (defined as 70-180 mg/dl) compared to patients on sensor augment pump therapy (75% vs. 62%). The closed loop system also outperformed sensor augmented pump therapy on multiple secondary outcomes, including mean glucose and standard deviation of glucose, without any significant difference in time spent in hypoglycemia. Ultimately, this study validated the feasibility of closed loop under free-living home conditions and supported the initiation of the AP@home04 study, which includes three months of days and nights in 30 adults (clinicaltrials.gov currently indicates an anticipated completion date in the second half of 2015). See below for full details on this presentation.

6. Dr. Stuart Weinzimer, MD (Yale University School of Medicine, New Haven, CT) provided an in-depth review of recent advances in artificial pancreas research over the past two years, focusing on predictive low glucose suspend, hybrid closed loop, and full closed loop. While he spent most of the time reviewing early data from closed loop feasibility trials, Dr. Weinzimer emphasized that these trials will provide preliminary safety and effectiveness information that will lay the groundwork for more rigorous transitional (and eventually pivotal) clinical trials. Given the pace of research over the past few years, Dr. Weinzimer was encouraged and optimistic that the “future will show great promise” for closed loop. See below for full details on this presentation.

7. Dr. David Klonoff (Mills Peninsula Medical Center, Burlingame, CA) presented the new Surveillance Error Grid (SEG), published online today in the Journal of Diabetes Science and Technology. Although we have heard the methodology behind the development of the error grid, Dr. Klonoff provided additional granularity on the development rationale – namely that the diabetes treatment and BGM accuracy have changed in the last twenty years, requiring a new grid for measuring accuracy. Specifically, Dr. Klonoff noted that at the time that the Clarke Error Grid (CEG) and Parkes Error Grid (PEG) were being developed and coming out, DCCT data, analog insulins, and hypoglycemia were all relatively uncharted territory. Comparing the three grids, Dr. Klonoff showed data demonstrating that there was only ~0.3 correlation between the SEG and both the PEG and CEG, while the PEG and CEG had a 0.6 correlation. Thus, with just enough correlation to show the grid is measuring the same metric, but not too much correlation to not provide any new information, the SEG is at the hypothetical “sweet spot” in innovation. Moreover, the SEG maintains high standards for BGM accuracy, which Dr. Klonoff demonstrated using BGM data from Freckmann et al. (Journal of Diabetes Science and Technology 2010). We were also impressed with the second publication presented, “Computing the Surveillance Error Grid Analysis” (also published today in the Journal of Diabetes Science and Technology), which demonstrated that when greater than 3.2% of values are in the at-risk zone, this likely corresponds to more than 5% of values falling outside the ISO 2013 Standards. The software is available for free download here, allowing people to evaluate their own meters. For background, the SEG does not have distinct boundaries between risks and has a tie dye look, fading from combinations of green to orange to yellow to red based on averaged risk across survey takers (see our Diabetes Technology Meeting Day #1 report for more details).

8. Bringing a primary care physician’s perspective to the discussion of self-monitoring of blood glucose in non-insulin-using patients with type diabetes, Dr. Richard Grant (Kaiser Permanente Northern California, Oakland, CA) argued that SMBG improves glycemic control only in the context of a larger educational effort and as a tool to effect change in self-care or medication. In a review of 12 randomized controlled trials of patients with type 2 diabetes for at least one year, SMBG reduced mean A1c by just 0.26% compared to control treatment (lifestyle and oral), with mixed A1c results in individual studies. Additionally, Dr. Grant provided sobering results from the DISTANCE survey, in which 15% of patients reported that their SMBG results were not used by anyone to make adjustments to diet, exercise or medicine. Notably in Q&A, a PCP from Oregon criticized the DISTANCE study, commenting that the data were cited by the state of Oregon to restrict test strips for people with diabetes not on insulin. Dr. Grant was quick to clarify that he “would never have come to the conclusion that test strips should be restricted for all patients with type 2 diabetes not on insulin.” Rather, he would focus on individualizing care and on prescribing SMBG to patients who will benefit from it. With regard to the Oregon legislation, Dr. Grant even commented, “Using population-based prescriptions to restrict strips doesn’t make any sense... I do not agree with it at all.”

9. We were very excited to attend Biodel’s small luncheon at which management previewed the company’s novel glucagon delivery device and sought feedback from attending diabetes educators and nurse practitioners. Notably, the device design has not been altered since we previously reported on the prototype at ADA 2013, as the rescue product will still use a dual chamber, automatic reconstitution protocol with a half-inch, 27-gauge, thin-wall needle. After seeing the demo and listening to the focus-group conversation, we continue to think that the rescue device offers a significant advantage relative to available options. Attendees were particularly impressed by the compact design and ease of use. Management drew attention to the labeling strategy that incorporates full instructions on the cover of the device itself and which was seen as convenient and critical policy to reassure family and friends of patients – the users of the device – who are often deterred from injecting glucagon for fear of hurting a loved one. Taken together, feedback was very positive from the entirety of the focus group. The main concern among participants was that a small company like Biodel may not have the resources to market and promote the device so that it gains the popularity they hope for. In summary, we especially enjoyed the spirited debate and invite you to read about it in more detail below.

10. Dr. Ling Hinshaw (Mayo Clinic, Rochester, MN) shared new data suggesting that hepatic glucagon sensitivity does not vary based on the prevailing blood glucose concentration. If confirmed, this would be a boon for the artificial pancreas field, since it would mean the device’s glucagon controller would not need to adjust its glucagon dosing based on prevailing glucose concentrations. This study involved 27 people with type 1 diabetes who were randomized to receive either a euglycemic or a hypoglycemic clamp. There was no difference between the two groups in the level of endogenous glucagon produced in response to several doses of glucose, contradicting the original hypothesis that hypoglycemic subjects would be more sensitive to the agent. However, the clearance rate of glucagon ascended linearly with the dose given in both groups. This means that a future artificial pancreas’s glucagon controller would still need to account for this.

Top Five Drug Highlights

1. Dr. Daniel Drucker (Lunenfeld Tanenbaum Research Institute) received this year’s Banting Medal in recognition of his truly prolific work in the realm of gut hormone-related therapeutic innovation. Dr. Drucker has worked on proglucagon-derived peptides from the very beginning, since the first cDNAs and genes had just been cloned and no one knew what any of those peptides did. In the early days, Dr. Drucker and colleagues discovered that one fragment of the GLP-1 peptide was a potent regulator of insulin gene expression, cAMP production and beta cell secretion – it seemed trivial to him at the time, but his mentor Joel Habener filed a patent in 1986, which is the patent that has laid the foundation for GLP-1 as a therapy. Since then, Dr. Drucker and his team have extensively characterized the pharmacologic and physiologic actions of GLP-1, including characterizing GLP-1’s potential beta cell preservation and proliferation effect in mice, GLP-1’s numerous actions outside of glucose regulation, and delineating DPP-4 inhibitors’ mechanism of action. He also touched on the hot topics of pancreatic safety and potential cardioprotective effects. Notably, Dr. Drucker gave reasons not to sound the alarm over GLP-1’s consistently demonstrated effect on increasing pancreas mass – he has evidence from mice that increased pancreas mass is not due to edema, inflammation, or increased cellular proliferation. In fact, he has shown that it is due to increased protein synthesis, possibly reflecting the communication between the gut and the pancreas to increase pancreatic protein synthesis following meal ingestion, however the mechanism is not fully understood. The thousands of audience members gave Dr. Drucker a thunderous standing ovation at the conclusion of his presentation (see below for full details).

2. Collaborators Dr. Stephen Gitelman (UCSF, San Francisco, CA) and Dr. Michael Haller (University of Florida, Gainesville, FL) presented positive results from a phase 2 and a phase 1 trial of two potential type 1 diabetes treatments. Following Saturday’s presentation of positive efficacy but scary safety results for the Brazil Cocktail (aka the Voltarelli Cocktail), Dr. Haller presented positive efficacy data, and more modest side effects, for the “Brazil Lite” combination of low-dose antithymocyte globulin (ATG) and granulocyte colony stimulating factor (GCSF) in patients with recent onset type 1 diabetes. The treatment arm’s two-hour C-peptide level was preserved over the 12 months, contrasting with the significant decline seen in the placebo group. On the safety side, while ATG/GCSF proved to be safer than the Brazil Cocktail, Dr. Haller still seemed disappointed in the rates of adverse events: 14 of the 17 participants in the experimental arm experienced cytokine release syndrome (a side effect of anti-T cell antibody infusions like ATG, producing a systemic inflammatory response) and/or serum sickness. A phase 2 study of ATG/GCSF in people with new onset type 1 diabetes is to be initiated this summer in collaboration with TrialNet. Dr. Gitelman followed Dr. Haller to the podium to detail data from a phase 1 study on the safety and tolerability of UCSF’s autologous T regulatory cell (Treg) immunotherapy for recent-onset type 1 diabetes. The primary goal of the study was to confirm the approach’s basic safety and tolerability, which it accomplished: the Treg infusions were well tolerated, with no infusion site reactions and no significant infectious issues. Notably, NeoStem has licensed the Treg technology from UCSF, and is partnering with UCSF and TrialNet  for phase 2 development.

3. In back-to-back talks, Dr. Stephanie Gustavson (Trans Tech Pharma, High Point, NC) presented trial data for TTP273 and TTP054, Trans Tech’s novel oral GLP-1 analogs. She opened with the results of a dose-ranging study (n=112) of the company’s second-generation candidate, TTP273, noting dose-responsive decreases in fasting plasma glucose and mean daily glucose (39 mg/dl and 42 mg/dl, respectively, at the 75 mg BID dose). In addition, there were very few GI-related adverse events, with only four patients in the entire study exhibiting any nausea – though we note given that this was a dose-ranging study, many patients received low doses of TTP273. Dr. Gustavson’s encore included 12-week trial results for Trans Tech’s first-generation candidate, TTP054, with results indicating placebo-corrected A1c declines of 0.6-1.0% (baseline 8.8-9.1%) across the dose ranges. Weight loss, however, was non-significant across the groups, though with relatively low weights at baseline in the trial. We recently had a very interesting discussion with the clinical development team at Trans Tech; as we understand it, the company’s candidates are small molecules as compared to other large molecules in development, such as Novo Nordisk’s NN9924 – we will be interested to see how this plays out in trials as more data is released for the numerous candidates in development. See below for full details.

4. Drug Posters: Interim six-month data were presented in the late-breaking poster session from a phase 3 trial of Intarcia Therapeutics’ ITCA 650 (continuous subcutaneous exenatide infusion) in 60 type 2 patients with baseline A1c >10% (FREEDOM-1HBL). Very impressive A1c reductions were observed in patients who had completed 13 weeks (-2.5%), 19 weeks (-2.9%), or 26 weeks (-3.2%) of treatment. We also saw the first ever phase 3 data on BI/Lilly’s SGLT-2/DPP-4 inhibitor empagliflozin/linagliptin, full results of the AWARD-6 trial (head-to-head Lilly’s dulaglutide vs. Novo Nordisk’s Victoza), a re-analysis of nocturnal hypoglycemia benefit with Novo Nordisk’s Tresiba, results of the EDITION IV trial for Sanofi’s U300 glargine, a poster on ISIS Pharmaceutical’s glucagon receptor antagonist (ISIS-GCGRRx) showing significant improvements in A1c, GLP-1 levels, and post-prandial C-peptide levels while avoiding many non-specific effects of glucagon inhibition (i.e., the investigators observed no changes in LDL-cholesterol, triglycerides, blood pressure, or body weight), full data from Lexicon’s phase 2 study of LX4211 in patients with renal impairment, a poster on usability of Lilly’s dulaglutide injection device (seems pretty foolproof), and early data on Zealand Pharma’s glucagon analog ZP-GA-1 showing greater solubility and stability compared to native glucagon while exhibiting a similar PK/PD profile.

5. Dr. Stuart Ross, MD (University of Calgary, Alberta, Canada) presented the results of a pre-specified subgroup analysis from a 24-week clinical trial comparing linagliptin+metformin vs. linagliptin alone in newly diagnosed type 2 diabetes patients. This sub-analysis examined A1c reductions in patients with extreme hyperglycemia (≥9.5% A1c at baseline). After 24 weeks, patients on linagliptin+metformin experienced a robust A1c reduction of 3.4%, compared to a 2.5% reduction in the linagliptin alone group (from a high baseline A1c of 10.5%). These A1c reductions translated into 61% of patients achieving a target A1c of <7% in the linagliptin+metformin group, and 40% of patients achieving target in the linaglitpin alone group. Dr. Ross concluded by challenging the notion that insulin initiation is required to achieve target A1c levels in newly diagnosed patients with extreme hyperglycemia. Notably, both the presenter and the chairperson mentioned that the A1c reductions were unexpectedly robust and may relate to newly diagnosed patients being uniquely responsive to glycemic interventions. See below for full details on this presentation.

Also…

1. In a symposium on epidemiology, Dr. Lisa Chow (University of Minnesota Medical School, Minneapolis, MN) and Dr. James Hempe (Louisiana State University, New Orleans, LA) explored two prevailing mysteries of ACCORD: why did some patients never reach A1c targets <6.0% even with intensive treatment, and why were some patients in the intensive arm at increased risk of death? Dr. Chow conducted a nested, case-control study within ACCORD to identify predictors of severe hypoglycemia and inability to achieve glycemic control (A1c <6.0%). She found potential biomarkers that include baseline insulin deficiency and islet autoantibodies. If testing for such biomarkers could predict who will respond to intensification of diabetes treatment, the clinical implications would be significant – especially given that the non-responders to intensive therapy were at increased risk of mortality in ACCORD. On a related topic, Dr. Hempe re-categorized ACCORD patients by whether their A1c was higher, lower, or the same as would be predicted by fasting plasma glucose. He found that in the intensive group, patients with higher-than-predicted A1c (aka high “hemoglobin glycation index”) had higher mortality and less CV benefit. Dr. Hempe has seen a similar pattern in other retrospective analyses, but several questioners were skeptical of his findings, and he himself emphasized that hemoglobin glycation index is not yet ready for clinical use. See below for details.

2. Our own team presented a poster on the costs of diabetes in the US (142-LB) – those costs are expected to rise to nearly half a trillion dollars by 2030, and that only counts the direct costs (not including indirect costs such as lost productivity). Between 1996 and 2010, the balance of costs shifted from inpatient hospitalizations towards medications and supplies, a trend that will likely continue. Another poster (59-LB) from our sister market research company dQ&A studied the stigma experienced by diabetes patients. The perception of stigma was high all around, especially among type 1 diabetes patients and insulin-treated type 2 diabetes patients, but the predictors of stigma were not necessarily what one might have predicted. See the appendix below for full details.

Table of Contents 

Detailed Discussion and Commentary

Technology

Oral Presentations: Constructing an Artificial Pancreas

Four Weeks’ Home Use of Overnight Closed-Loop Insulin Delivery in Adults with Type 1 Diabetes: A Multicentre, Randomised, Crossover Study (233-OR)

Hood Thabit, MD (University of Cambridge, Cambridge, United Kingdom)

Dr. Hood Thabit thrilled us with results of a 28-day, crossover, home-use study of overnight closed-loop control in adults with type 1 diabetes (n=24). At baseline patients had mean age 43 years, A1c 8.1%, duration of diabetes 29 years, duration of pump use 6.3 years, BMI 26 kg/m2, insulin dose 0.5 U/kg/day. Overnight closed-loop control, compared to open-loop CGM/pump therapy, led to statistically significantly more overnight time in target 70-144 mg/dl (53% vs. 39%), lower overnight mean glucose (148 mg/dl vs. 162 mg/dl), less overnight time >144 mg/dl (44% vs. 57%), lower mean glucose at 7 am (130 vs 158 mg/dl), lower 24-hour mean glucose (157 mg/dl vs. 167 mg/dl), and more 24-hour time in target (66% vs. 59%). Dr. Thabit explained that the improved glycemic control was due to overnight insulin delivery that was significantly higher-dose (6.4 vs. 4.9 U/night) and more variable (SD 0.6 vs. 0.1 U); however, thanks to better glycemic control at the start of the day, total insulin dose was not significantly higher (34.5 vs. 35.4 U/day). Rates of nocturnal hypoglycemia <70 mg/dl were low (1.8% vs. 2.1%) and not significantly different between groups, due to optimization of open-loop therapy. Closed-loop control was interrupted for technical reasons roughly 20% of nights; the main problem was a loss of connectivity with the pump (81%). Two severe hypoglycemic episodes occurred, both overnight during interruptions of closed-loop connectivity; both patients recovered fully.

Day and Night Home Closed-Loop Insulin Delivery in Adults with Type 1 Diabetes: Three-Centre, Randomised, Crossover Study (235-OR)

Lalantha Leelarathna, MD (University of Cambridge, Cambridge, UK)

Dr. Leelarathna shared exciting results from a feasibility study of a closed loop system under free-living home conditions for seven days and nights in adults with type 1 diabetes (n=17). Patients were randomized to receive either the FlorenceD2 closed loop system or sensor augmented pump therapy. After seven days of treatment, patients in the closed loop arm spent significantly more time in the target range (defined as 70-180 mg/dl) compared to patients on sensor augment pump therapy (75% vs. 62%). The closed loop system also outperformed sensor augmented pump therapy on multiple secondary outcomes, including mean glucose (146 mg/dl vs. 158 mg/dl) and standard deviation of glucose (52 mg/dl vs. 59 mg/dl), without any significant difference in time spent in hypoglycemia. Operationally, however, Dr. Leelarathna emphasized that the portability and connectivity of the closed loop system needs to be improved going forward. Nevertheless, this study validated the feasibility of day and night closed loop and supported the initiation of the AP@home04 study, which includes three months of day and night in 30 adults (clinicaltrials.gov currently indicates an anticipated completion date in the second half of 2015).

  • The objective of this study was to evaluate the feasibility of day and night closed loop system under free-living home conditions for seven days in adults with type 1 diabetes. The trial was conducted under the AP@home consortium and recruited 17 patients from Germany, UK, and Austria. Type 1 diabetes patients were eligible for the study if they were on insulin pump therapy, had an A1c <10%, and did not have any significant comorbidities or hypoglycemia unawareness. Patients were randomized either to the FlorenceD2 closed loop system or an open loop treatment (consisting of insulin pump therapy combined with real-time CGM). The FlorenceD2 system contains three components: the Dana R insulin pump, the Navigator II receiver, and the control algorithm device. Each treatment phase included 23 hours in a clinical research facility followed by seven days at home. After a 1-3 week washout period, patients were crossed-over to receive the other treatment. During the research facility phase of the study, patients were trained on using the closed loop system; however, after the 23-hour inpatient stay, participants went home and used the system without any supervision – they could consume any meals of their own choice. Patients were encouraged to engage in moderate physical activity, but were advised to avoid strenuous activity or driving.
  • The study recruited 17 adult patients with type 1 diabetes. The participants included 10 males and 7 females, with an average age of 34 years and an average duration of diabetes of 19 years. At baseline, patients were reasonably well controlled, with a mean A1c of 7.6%.
  • Patients on closed loop treatment experienced significantly greater time in target range (defined as 70-180 mg/dl [3.9-10 mmol/l])] during the seven day home phase, compared to the open loop arm (75% vs. 62%). When using YSI reference glucose values, the target zone remained consistent (74% vs. 61%). The total daily dose of insulin infusion was lower in the closed loop group, but did not reach statistical significance (total basal insulin was slightly higher with closed loop, but boluses were significantly lower).
  • There were a total of 194 operational interruptions, translating to an interruption event every 12 hours (out of 2,333 total hours of closed loop operation in this study). The two most common reasons for these events were lack of pump connectivity and CGM unavailability. One severe hypoglycemia episode occurred in the closed loop arm because the sensor stopped working and the patient administered two manual boluses. Dr. Leelarathna highlighted this as an opportunity for improvement and mentioned that the next study (AP@home04) has moved to a mobile home platform with wireless communication between devices.

Questions and Answers

Dr. Irl Hirsch (University of Washington, Seattle, WA): Regarding the differences in bolus insulin on closed loop, what can I take away from that? Does that mean we are we doing too much bolus insulin or were patient eating differently on closed loop?

A: One of the reasons was that glucose was more in target on closed loop. Therefore, the correction bolus was lower in patients on closed loop.

Dr. Hirsch: When you say bolus, you’re including the correction as a bolus?

A: Correct.

Dr. Hirsch: I would suggest for reporting in the future, we need to separate bolus from correction from basal.

Arlene Pincus (FDA): Can you confirm if the subjects kept diaries during the study? If so, were you able to trace the glucose excursion on closed loop to specific activities?

A: We did give patients diaries, but unfortunately very few patients followed our advice. So, unfortunately I can’t answer that. Anecdotally, I would say the excursions were due to a miscalculation of carbohydrate bolus or exercise.

Symposium: Closed-Loop Insulin Delivery — One Step at a Time (Sponsored by The Helmsley Charitable Trust)

Proof-of-Concept Trials

Stuart Weinzimer, MD (Yale University School of Medicine, New Haven, CT)

Dr. Stuart Weinzimer provided an in-depth review of recent advances in artificial pancreas research over the past two years, focusing on predictive low glucose suspend, hybrid closed loop, and full closed loop. While he spent most of his time reviewing early feasibility data, he emphasized that these trials will only provide preliminary safety and effectiveness information, but will lay the groundwork for more rigorous transitional (and eventually pivotal) clinical trials. Given the pace of research over the past few years, Dr. Weinzimer was encouraged and optimistic that the “future will show great promise” for closed loop.

  • Dr. Weinzimer began by reviewing the types of closed loop studies and the caveats of comparing data across trials. In general, closed loop studies fall into three categories, starting with small feasibility studies (to demonstrate preliminary safety and effectiveness), followed by transitional studies (with a greater number of patients and/or a greater duration), followed by pivotal studies, which will be designed for regulatory approval. Given the variation in trial design, Dr. Weizimer cautioned against comparisons across trials without taking into account key factors, such as the presence/absence of controls, age of patients, hybrid vs. full closed loop use, size of meals, glycemic targets, and the treatment/definition of hypoglycemia.
  • There has been considerable progress in predictive low glucose suspend. Dr. Weinzimber focused on two major studies published in 2014: Danne et al., Diab Technol Ther 2014 and Maahs et al., Diab Care 2014. The Danne et al., study induced hypoglycemia with an exercise regimen in type 1 diabetes patients (n=16). The system shuts off insulin delivery when hypoglycemia is predicted to occur, a feature that averted actual hypoglycemia in 13 patients. Dr. Weinzimer noted that larger studies of predictive low glucose suspend are currently being planned and conducted. In the second study (Maahs et al., Diab Care 2014), the predictive low glucose suspend was shown to decrease both the percentage of nights with hypoglycemia (across all definitions) as well as the duration of hypoglycemia.
  • Dr. Weinzimer then reviewed overnight closed loop trials, which represent the next level of automation, after the predictive low glucose suspend. The longest duration studies of the closed loop come from the Cambridge group (Hovorka Diab Care 2014), which published last month the results of a three week study in 16 adolescents – this study showed a significant reduction in glucose variability overnight and a significant improvement in glucose levels within target range (70% of glucose levels within range). Dr. Weinzimer also reviewed the results of the DREAM project collaboration, which studied an overnight closed loop in 56 children at a diabetes camp. While he characterized this study as a feasibility study due its short one-night duration, he did note the “impressive” number of patients included in the study. This consortium is moving to in-home studies; recently published data demonstrate improvements in time in target, glucose variability, and exposure to hypoglycemia in the home environment with four consecutive nights (Nimri et al., Pediatr Diab 2014).
  • Finally, Dr. Weinzimer briefly touched on a few recently published studies of fully closed loop systems. In one 24-hour trial (Harvey et al., Diab Technol Ther 2014), a fully closed loop system was studied without manual meal boluses and no announcements to the patient (n=12). Dr. Weinzimer showed patient glucose profiles to demonstrate the slight increase in glucose excursions that would be expected without announcements. He also shared a study from his own group (Weinzimer et al., Diab Care 2012), in which a fully closed loop was tested in eight patients. After 48 hours of use, 71% of glucose levels were in target zone with no incidences of hypoglycemia.

Symposium: Joint ADA/AACC Symposium – Self-Monitoring of Blood glucose – 21st Century Issues

The New Error Grid – Rationale, Development, and End Product

David Klonoff, MD (Mills Peninsula Medical Center, Burlingame, CA)

We had trouble finding seats in the packed lecture hall where Dr. David Klonoff unveiled the new Surveillance Error Grid (SEG), a new alternative to the Clarke Error Grid (CEG) and Parkes Error Grid (PEG). The SEG was published today in the Journal of Diabetes Science and Technology. We’ve been looking forward to this presentation since April when Dr. Klonoff hinted at the error grid during the 2014 Clinical Diabetes Technology Meeting. To start, the SEG looks very different from the CEG and PEG, with a tie-dyed look, fading from combinations of green to orange to yellow to red based on averaged risk across survey takers (see our Diabetes Technology Meeting 2013 Day #1 report for more details). Dr. Klonoff explained the rationale behind developing a new error grid for surveillance, namely that the treatment of diabetes has changed, accuracy standards for BGM have become tighter, and our understanding of hypoglycemia has increased making it necessary to develop a new grid that will incorporate the new treatment and clinical treatment of diabetes care. To support this, Dr. Klonoff noted that, when comparing the attributed risk results between graphs, there was a 0.58 correlation between the CEG and PEG, but only a 0.36 correlation between the CEG and SEG results and a 0.31 correlation between PEG and SEG. Dr. Klonoff concluded from this that the SEG is similar enough to the CEG and PEG to conclude that a similar metric was being used but dissimilar enough to show that the SEG is useful in measuring something different – Dr. Klonoff called this the “sweet spot.” Looking at how this translates to surveillance, Dr. Klonoff noted that BGM standards of accuracy in SEG increased from CEG and PEG. Dr. Klonoff concluded by commenting that the new software accompanying the SEG can be downloaded for free at www.diabetestechnology.org/SEGsoftware, allowing people can take their own reference BGM data points and find out what zone their data lie in.

  • According to the “Computing the Surveillance Error Grid Analysis” that developed the software mentioned above (and was also published today in the Journal of Diabetes Science and Technology), having more than 3.2% of data points in the at-risk zone (outside of the green), corresponds to more than 5% of data points outside the ISO 2013 standards. While this should not be taken as hard evidence that a meter is not as accurate as it should be, we appreciate Dr. Klonoff’s efforts to put more responsibility into patient hands.
  • Dr. Klonoff explained that the SEG allows for clinician flexibility in how risk is assessed. After HCPs ranked the risk factor for reading vs. reference value on a nine-point, whole number scale, Dr. Klonoff and his team created a finer gradation through implementation of 0.5 risk units, providing 15 points of division (e.g., splitting the “none” risk zone into “slight risk for hypoglycemia,” “lower,” and “none”). Although the FDA advocates for use of this 15 division system (and the paper states, “We expect that for regulatory processes the 15-zone distribution will be used.”), Dr. Klonoff highlighted that the 15-zone distribution could be condensed into eight zones by disregarding directionality of risk, and the original nine zones could be condensed to five zones by similar methods. Additionally, Dr. Klonoff commented that a “pass-fail” model could also be used. For example, a certain distribution percentage points of data need to be above or below a cutoff score.
  • Dr. Klonoff outlined several advantages of SEG over PEG and CEG, including that the latter grids didn’t account for DCCT trial results that came out in 1993, analog insulins that emerged in 1996, new information about hypoglycemia, and raised accuracy standards for meters. For example, the CEG has a 20% error separating the A and B blocks. Additionally, it is unclear who the clinicians were that were surveyed in the development of the PEG; PEG is based off of 100 people surveyed at ADA 1994. He also reviewed the development of CEG and PEG, remarking that while CEG focused only on treatments and PEG only focused on outcomes, SEG blends both treatment and outcomes.
  • Dr. Klonoff briefly touched on the fact that this study supports BGM use in patients with type 2 diabetes not on insulin, since HCPs ranked risks across blood glucose levels the same in this population as in other groups. This is significant given the recent move in some areas (such as Oregon) to restrict strip access to patients on Medicare and Medicaid. We hope that such clinical data continues to be circulated among HCPs, payers, and CMS to demonstrate the HCPs do see the risk in not testing patients with type 2 diabetes.
  • The Surveillance Error Grid” was published on the Journal of Diabetes Science and Technology today. Along with individual authors, Dr. Klonoff also called attention to organizations pivotal in the development of the error grid, including the Diabetes Technology Society, the FDA, the ADA, the Endocrine Society, and the American Association for Advancement of Medical Instrumentation. Additionally, he acknowledged the hard work of error grid panel members, including 25 people in academia and industry such as Medtronic, Dexcom, LifeScan, Abbott, Bayer, Roche, and Sanofi – a strong circle of the leaders in Diabetes Care technology.
  • Notably, Dr. Klonoff added that the FDA has already begun using the SEG as a model to assess other measuring devices. We think that this bodes well for the FDA actually beginning to use the SEG as a post-market surveillance tool for BGM. Currently, the FDA does not conduct post-market surveillance, but assessing and enforcing meter accuracy remains a concern for both patients and providers, particularly in ICU settings where BGM use is still off-label.
  • The SEG was developed by surveying 206 clinicians and 28 non-clinicians asking what actions would be taken for each blood glucose value between 0 mg/dl and 600 mg/dl. The survey takers were then asked to assign risk (from “none” to “extreme”) if a reference value is misread either high or low. From there, all responses were averaged, allowing the SEG developers to impart more granularity on the grid by taking 0.5 risk units (Dr. Klonoff explained it similar to grades – although a student may only be able to get a 3 or 4 in a given class, if their grades are averaged across all classes, then they would be able to have a GPA of 3.5). See our coverage of methodology of developing the SEG in Day #1 of the Diabetes Technology Meeting in October 2013.

Questions and Answers

Q: Could you speak to how looking at the consensus between people responding to the survey translates into figuring out what level of granularity is appropriate for drawing boundaries between risk levels?

A: We had a large number of respondents, so we with mean; each person was his or her own control. We had an extreme idea of what the extreme scenarios would be. Additionally, often people would call blood glucose levels clinical significant when they were not in the “green” zone.

Comment: If you have a mean of 3.5; are most people saying 3 and 4 rather than 2 and 5?

A: Each value had a specific definition associated with it, and participants had to accept those definitions. Once defined, it is easier to chop values into gradations – it is like chopping up grades. It is very mathematically oriented.

Self-Monitoring of Blood Glucose in Non-Insulin Users – What is the Evidence?

Richard Grant, MD, MPH (Kaiser Permanente Northern California, Oakland, CA)

Dr. Richard Grant brought a primary care physician’s perspective to the discussion of self-monitoring of blood glucose. He argued that SMBG in non-insulin-using type 2 diabetes patients improves glycemic control only when prescribed in the context of a larger educational effort and as a tool to effect change in self-care or medication. In a review of 12 randomized controlled trials of patients with type 2 diabetes for at least one year, SMBG reduced mean A1c by just 0.26% compared to control treatment (lifestyle and oral), with mixed A1c results in individual studies. Additionally, Dr. Grant provided sobering results from the DISTANCE survey, in which 15% of patients reported that their SMBG results were not used by anyone to make adjustments to diet, exercise or medicine. Notably in Q&A, a PCP from Oregon criticized the DISTANCE study, commenting that the data were cited by the state of Oregon to restrict test strips for people with diabetes not on insulin. Dr. Grant was quick to clarify that he “would never have come to the conclusion that test strips should be restricted for all patients with type 2 diabetes not on insulin.” Rather, he would focus on individualizing care and on prescribing SMBG to patients who will benefit from it. With regard to the Oregon legislation, Dr. Grant even commented, “Using population-based prescriptions to restrict strips doesn’t make any sense... I do not agree with it at all.”

  • Dr. Grant also cited the well-known STeP study by Dr. William Polonsky et al. that highlighted the benefit a structured testing protocol: 1.2% A1c reduction compared to 0.9% reduction in the control group (Diabetes Care 2011). Patients with type 2 diabetes (n=256) were assigned to a 7-point testing schedule to be completed on the three consecutive days prior to study visit. The seven points included fasting, pre-prandial/2 hr postprandial at each meal, and bedtime tests. Unsurprisingly, this structured SMBG protocol required extensive education and diabetes care team support. The control group received quarterly clinic visits that focused specifically on diabetes-management and were given free blood glucose meters and strips as well as access to an office point-of-care A1c capability (n=227). Dr. Grant noted that though the control patients received good diabetes care, the structured testing still showed benefit.
  • In the DISTANCE Survey of the Kaiser Permanente Northern California diabetes registry, among patients who said that they used SMBG, 15% reported that their SMBG data were not used by anyone to make adjustments to diet, exercise, or medicine. Breaking down results into components, 37% of patients reported that both they and their and provider used data to change care, 34% reported that only they themselves used the data, and 14% reported that only their provider used the data. For providers not to use SMBG data is a “worst-case scenario” in Dr. Grant’s opinion. We found these data demoralizing, especially since they were used by the state of Oregon to justify restrictions on test strips in patients who are not treated with insulin.
  • Dr. Grant noted that most patients with type 2 diabetes not on insulin are being treated in primary care settings where PCPs have an endless list of competing priorities for the 15-minute visits. Primary care physicians have a typical patient panel of 1,500-2,000 patients, and type 2 diabetes prevalence makes up 10-25% of these patients (~200 patients with type 2 diabetes). Given the urgency of behavioral interventions on diet, exercise, smoking, medication adherence, etc., interpreting SMBG may rank at the bottom of PCPs’ priorities. Another challenge is that 80% of patients with type 2 diabetes have concurrent chronic conditions like COPD, heart failure, and obesity. However, Dr. Grant also noted that SMBG data could be used to leverage lifestyle counseling and optimize medication management.
  • Dr. Grant recommended that SMBG prescriptions should be made in the context of a shared-decision making framework to individualize care and ensure SMBG is the most time and cost-effective strategy.

Questions and Answers

Q: I was surprised that you didn’t consider in your review the PRISMA study in Diabetes Care in 2013 that is the largest comparison structure as SMBG in type 2 diabetes patients with more than 1,000 patients and up to one year follow up. The results showed significant reduction of A1c. This was thanks to a higher frequency in changes of medication exactly as you noted. I would emphasize that I wouldn’t consider SMBG useless in these categories of patients. Maybe we could discuss if it is cost-effective, but clinical usefulness in my opinion is clearly demonstrated.

A: I only included those in the original Cochrane comparison. As you said, A1c went down because of medication. I would argue that SMBG isn’t necessary to change medication. Also, I wouldn’t argue that SMBG is useless, but that if it is used, it should be used correctly. You can have excellent A1c control without SMBG.

Comment: I also disagree with your statement because if you have a patient on a sulfonylurea, hypoglycemia is a real danger and SMBG can help prevent this danger as well as improve quality of life.

A: I agree that hypoglycemia is important. There are a great number of patients not at risk for hypoglycemia, though. In these patients SMBG may not be as useful. Part of this discussion is not that it’s a bad thing, but that in larger context there are patients who don’t need it.

Q: I’ve also seen this particular research being used against us. In Oregon, the legislature cited this [DISTANCE study] to restrict strips for Medicare and Medicaid patients not on insulin. Have you looked at broad orals and tiered out non-hypoglycemia agents? I agree in part, but not in whole. We still see sulfonylureas as the number two prescribed medication in Oregon. Your data is currently being leveraged against us, but the data is not one group of people and I think you’d agree. Yes as SMBG may not be effective in primary care but this legislation is restricting SMBG and instead pushing the use of agents like sulfonylureas.

A: In the study I presented, we were really trying to predict the worst-case scenario. It doesn’t matter what they’re on. If you prescribe SMBG, someone should be looking at that data. Back to Oregon, I wouldn’t conclude that we should restrict test strips. We should use strips for certain patients. Using population-based prescriptions to restrict strips doesn’t make any sense. I do not agree with it at all. Some patients would be tremendously motivated. Equally, some patients wouldn’t benefit at all. That is the whole theme of the ADA/EASD recommendation; we need to individualize care to move levers.

Posters

CGM Is Not a Limiting Factor in Artificial Pancreas Systems (75-LB)

Timothy Bailey, Katherine Nakamura, Anna Chang, Mark Christiansen, David Price, Andy Balo

This exciting poster shared in-clinic data from 51 patients that wore a version of the G4 Platinum with an improved algorithm (called “G4AP” in previous Dexcom presentations). The device’s accuracy was compared to YSI and fingerstick values (Bayer Contour USB) on days one, four, and seven. The poster also compared the accuracy of Bayer Contour USB values to YSI – a clear move from Dexcom to demonstrate that its next-gen CGM accuracy is approaching fingersticks. Overall G4AP MARD vs. YSI was an impressive 9.0%, compared to a fingerstick MARD of 5.6% vs. YSI. Notably, G4AP and fingersticks had a similar mean absolute difference (MAD) in hypoglycemia vs. YSI: 6.4 mg/dl and 4.2 mg/dl, respectively. In addition, the Clarke Error Grid data vs. YSI suggested G4 AP is really approaching the clinical accuracy of fingersticks– A+B Zone data was nearly identical (99.5% with G4AP vs. 99.6% with the Contour USB) and A-Zone accuracy was quite similar (92% vs. 99%). Overall, we thought the data were very, very strong and showed highly impressive accuracy using Dexcom’s existing G4 Platinum sensor and an improved algorithm – this hits the “holy grail” bar of a sub-10% MARD for CGM, a level of accuracy that some have called for to safely run tight closed loop control. This poster also underscored how much inherent inaccuracy there is in SMBG, and it makes us even more encouraged about the possibility of an insulin-dosing claim and factory calibration. A presentation later in the day noted that the “Share AP receiver” with the G4AP algorithm will be available for artificial pancreas research use in December 2014 (US) and 1Q15 (EU). We’re not sure if this would be rolled out to consumers, but are optimistic.

  • The poster concludes, “The clinical performance of this CGM is approaching that of current SMBG systems, particularly after the first day of use and in hypoglycemia ranges. The system could be adequate for use in diabetes management decisions without the need for SMBG tests, in particular for reducing hypoglycemia. Accordingly, the CGM accuracy should not limit AP development.” Given how many patients already use their existing G4 Platinum CGMs to dose insulin (technically “off label”), we agree and believe that G4AP surpasses the bar for independent diabetes management decisions.
  • This clinical trial enrolled 51 patients at three US centers. Patients inserted and wore one sensor for seven days and participated in three 12-hour clinic sessions (days one, four, and seven) with YSI every 15 minutes and SMBG capillary tests every 30 minutes. Glucose was manipulated to provide sufficient data in low and high glucose ranges during the clinic session. The CGM was removed at the end of the seven-day wear. The closest matched data point between CGM, SMBG, and YSI were used to assess CGM performance. The fingerstick meter used was a Bayer Contour USB. The CGM calibration scheme was twice daily fingersticks, prospectively calibrated.
  • The science behind the G4AP algorithm was described by Garcia et al., JDST 2013. The G4AP employs the same sensor and transmitter as the G4 Platinum, but contains updated denoising and calibration algorithms for improved accuracy and reliability. The JDST study used a retrospective G4AP algorithm application to the G4 Platinum pivotal study data. This poster reports on the prospective, clinical use of the G4AP algorithm – as we understand it, the G4AP clinical data (overall MARD: 9.0%) is even better than the retrospective data (overall MARD: 11.7%) because the study execution was better.

 

G4AP vs. YSI

SMBG vs. YSI

G4AP vs. SMBG

Matched pairs

2,263

994

2,992

Overall MARD
  On Day 1
  On Day 4
  On Day 7

9.0%
10.7%
8.0%
8.5%

5.6%
5.3%
4.9%
6.6%

11.2%
12.7%
10.9%
9.9%

MAD in Hypoglycemia(<70 mg/dl)

6.4 mg/dl

4.2 mg/dl

7.8 mg/dl

Overall Clarke Error Grid

A+B Zones: 99.5%
A Zone: 92.4%

A+B Zones: 99.6%
A Zone: 98.5%

A+B Zones: 99.6%
A Zone: 98.5%

% within 20%/20 mg/dl

93%

99%

87%

Efficacy and Safety of Insulin Pump Therapy in Type 2 Diabetes: The Opt2mise Study (102-LB)

Yves Reznik, Ohad Cohen, Ignacio Conget, Ronnie Aronson, Sarah Runzis, Javier Castaneda, Simona De Portu, Scott W. Lee, Opt2mise Study Group

This poster presented the long-awaited results from the randomized, six-month Opt2mise trial, comparing insulin pump therapy (n=168) to MDI (n=163) in type 2 patients in poor control (mean A1c: 9.0%). Following a run-in phase, patients were 1:1 randomized to either use a pump or MDI. From a baseline of 9.0%, A1c declined by 1.1% in those on an insulin pump compared to 0.4% in the MDI group (p<0.001) after 27 weeks; 55% of the pump group achieved an A1c <8% vs. 28% of the MDI group. CGM data (baseline vs. six months) revealed no significant increase in hypoglycemia. Meanwhile, the group on pumps used 20% less insulin than those on MDI (p<0.001). HDL cholesterol improved by 8% in the pump group and declined by 7% in the MDI group (p=0.01). One episode of severe hypoglycemia occurred in the MDI group, while none occurred in the pump group. It was valuable to see this positive data from a randomized, controlled, multi-center study of pumps in type 2 diabetes – most importantly, we like that the investigators enrolled a population that could most use easier and more convenient approaches to insulin delivery. Given the high starting A1c of 9.0%, the magnitude of reduction (-1.1%) was perhaps not quite as high as some would have expected although patients may have been very hard to manage. We wonder if insulin titration could have been better, if a simpler device with on-body bolusing (e.g., Valeritas’ V-Go or CeQur’s PaQ) could have helped drive patients even lower, or if this simply underscores what a challenging population this is to manage.

  • Following a three-visit run-in phase to optimize MDI therapy, 331 patients were randomized to six months of either pump therapy (n=168) or MDI (n=163). The objective of the run-in phase was to optimize MDI therapy. All oral medications were replaced by metformin, and insulin therapy was intensified to >0.7 units/kg/day. During the study phase, the pump group initially used the same total daily insulin dose as before; patients randomized to MDI continued titration to target range. After six months, the MDI arm crossed over and switched to the pump. Both groups then spent months six through 12 on the pump during the study’s continuation phase. 
  • Patients had a mean age of 56 years, a mean 15 year duration of diabetes, a mean A1c of 9.0%, a mean BMI of 33 kg/m2, a mean total daily dose of ~109 units per day. The study had a high completion rate – 90% in the pump group vs. 96% in the MDI group.
  • From a baseline of 9.0%, A1c declined by 1.1% in those on an insulin pump compared to 0.4% in the MDI group (p<0.001) after 27 weeks; 55% of the pump group achieved an A1c <8% vs. 28% of the MDI group. As would be expected, patients in the highest tertile of baseline A1c realized the largest improvement in A1c after six months of pump use.

Baseline A1c Tertile

8-8.5%

8.6-9.2%

9.3-11.9%

Difference in A1c Change (MDI-Pump)

-0.3%

-0.5% (p=0.01)

-1.1% (p<0.001)

  • Despite the improved A1c, the group on pumps used 20% less insulin vs. those on MDI (p<0.001) at the end of six months. The MDI group saw total daily insulin dose steadily increase from 106 units per day to ~120 units per day. Meanwhile, the pump group saw total daily insulin dose decline from 112 units to ~100 units per day.
  • CGM data (baseline vs. six months) revealed a significant improvement in 24-hour mean glucose, a significant reduction in hyperglycemia, and no significant increase in hypoglycemia. CGM data was collected over six days at baseline and at the end of the study. We assume the iPro2 was used, though it was not specified.

 

Pump

MDI

Change in 24-hour Mean Glucose

-23 mg/dl*

-6 mg/dl*

Change in time spent >180 mg/dl

-226 minutes per day**

-57 minutes per day

Change in time spent <70 mg/dl

+9 minutes per day

+ 5 minutes per day

*p<0.01; **p<0.001

  • One episode of severe hypoglycemia occurred in the MDI group, while none occurred in the pump group. There no episodes of DKA in either group. Four device-related serious adverse events occurred in the MDI group: two hyperglycemic hospitalizations (not DKA), one episode cellulitis, and one abscess.

Rate-of-Change Dependence of the Performance of Two CGM Systems During Induced Glucose Excursions (846-P)

The authors compared the accuracy of two CGM systems: the Dexcom G4 and a prototype CGM system developed by Roche. This Roche-funded study enrolled 10 patients with type 1 diabetes who each spent about a week wearing four sensors simultaneously (two G4, two prototype). In an interesting wrinkle, the authors compared the performance of the sensors during two induced glucose excursions, which occurred roughly 40 hours and 70 hours after sensor placement. Measurements were compared to reference blood glucose readings drawn every 15 minutes during the excursions. (According to the poster these blood glucose measurements were also used for calibration; we are not sure exactly what this means or how it affected the results.) Notably, the G4 had numerically higher MARD than the prototype in every category of glycemic rate of change assessed, suggesting that the Roche sensor could be more clinically useful while . The mean seven-day MARD was 10.9% for the G4 and 8.6% for the prototype. More than 80% of the prototype sensors had overall MARD below 10%, as compared to 20% of the G4 sensors.

 

Dexcom G4

Roche Prototype

Rate of Change (mg/dl/min)

MARD (%)

SD (%)

n

MARD (%)

SD (%)

n

< -3

24.9

15.6

46

10.6

8.4

44

≥ -3 to < -2

19.2

13.0

75

10.9

9.4

73

≥ -2 to < -1

17.1

12.5

151

9.8

8.4

144

≥ -1 to < 0

12.6

10.1

227

8.2

6.3

217

≥ 0 to < 1

11.3

9.1

88

10.0

10.6

83

≥ 1 to < 2

19.5

12.2

44

10.2

9.7

39

≥ 2 to <3

21.1

14.0

28

12.2

7.4

28

≥ 3

29.6

11.9

44

16.3

12.4

44

Biodel Luncheon

Glucagon Rescue Delivery Device Demonstration

Michael Crick (Biodel, Danbury, CT) and Molly Miller, PhD (Unilife, York, PA)

We had the privilege to attend a small luncheon hosted by Biodel in which the company previewed its novel glucagon delivery device and sought feedback from diabetes educators and nurse practitioners. The device design has not been altered since we previously reported on the prototype at ADA 2013, as it will still use a dual chamber, automatic reconstitution device with a half-inch, 27-gauge, thin-wall needle – pictures of the device can be seen here. The device contains a lyophilized (freeze dried) cake of glucagon, which can be delivered in three steps: 1) Twist to remove the front and back cover, reconstituting the glucagon and unlocking the front needle cover; 2) remove the needle shield; 3) push plunger to give dose (the needle automatically retracts into the barrel following completion of a full dose). The device is expected to have two-year dating and come in 1 mg and 0.5 mg (children) doses. Product development is still on schedule as Biodel’s goal remains an NDA filing by the end of 2015 under the 505(b)(2) regulatory pathway. After seeing the demo and listening to the focus-group conversation, our impression remains that the rescue device offers a significant advantage relative to available options; attendees were particularly impressed by the compact design and ease of use. Management drew attention to the labeling strategy: Biodel would like to include full use instructions on the device’s cover. This approach was seen as a convenient and critical way to reassure the families and friends of patients – the users of the device – who are often deterred from injecting glucagon for fear of hurting a loved one. Overall, the focus group’s feedback was very positive. Members only expressed concern that a small company, like Biodel, might not have the resources to market and promote device so as to drive uptake.

  • When the group was asked whether this device would make their practice easier, the answer was a resounding “Yes!” Several educators said that it would be much easier for them to train patients and their loved ones on how to use this device than the current glucagon kit. Attendees specifically praised the easy-to-follow instructions and retractable needle. One former pediatric educator mentioned that it might be easier to train school nurses on how to use this device, which would help achieve the goal of increasing access to emergency glucagon kits in schools.
  • Management indicated that the novel glucagon rescue product would be priced comparably to the current marked kits. This statement leaves hope that pricing of the novel device will be reasonable, though it also provides management with a lot of wiggle room for a premium. Indeed, in holding this luncheon, Biodel was attempting to gather input that would assist them in catering to patients, so it would be unfortunate if pricing undermined this goal.
  • The novel glucagon rescue product features simple instructions and diagrams on the device’s cover in order to make its administration as stress-free as possible. In theory, the instructions are designed as a reminder to a trained individual. Yet  from our examination, the instructions appear clear and concise enough that many novices would be able to understand them and use the product as well. In order to enhance the user-friendly nature of the product, attendees also suggested bright red coloring – the prototype cover is opaque, white plastic – since that is already associated with diabetes. Additionally, attendees recommended using and glow-in-the-dark finish, a clever and functional suggestion, which Biodel management appreciated.
  • A theme throughout the discussion was the lack of patient awareness about the need for glucagon. As one attendee put it, “We have a better mousetrap but people don’t know why they need a mousetrap in the first place.” Another attendee was amazed by how many of her patients were unfamiliar with glucagon or who said they had been trained on it once, but didn’t actually know how to use it. The group attributed some of this problem to the current kit; however, the consensus seemed to be that a serious effort is needed to market this new device to a wider audience.
    • One educator repeatedly stressed the need to communicate that glucagon can be used before a patient loses consciousness. She noted that many people are reluctant to use a glucagon kit, which leads to too many patients going “past the point of no return.”
  • Attendees proposed giving users a mini dosing option, due to concerns that users will only be able to administer the whole 1 mg dose. “If you have glucagon once, you are not keen on having it again,” said one attendee, referring to the prolonged vomiting that occurs as a result of taking a such a large dose. Biodel acknowledged this idea, but stated that the regulatory path of mini dosing is less clear.
  • A mobile app was suggested by attendees to ease the training of friends and family with the device. The attendees highlighted how an app with a training video and instructions would provide an easy means to instruct friends and families on the kit’s use. Attendees think that training in the form of DVDs or videos shown on a TV at the doctor’s office are not very effective. With a mobile app, caregivers do not miss out on important information if they are unable to accompany patients on office visits.
  • At the conclusion of the luncheon, we were excited to hear about “Ha!” (or “Hypoglycemia Awareness”) an organization dedicated to educate the public on how to recognize and respond to a hypoglycemic episode. The group’s goal is to train first responders, such as police officers and flight attendants, to appropriately respond to a hypoglycemic episode in order to help and save the lives of those with diabetes. Ha! is hoping to get funding from the Bloomberg Foundation. We applaud these public health efforts and encourage people to learn about how to take action in response to a hypoglycemic event.

Drugs

Banting Medal for Scientific Achievement Award Lecture

Deciphering Metabolic Messages from the Gut Drives Therapeutic Innovation

Daniel Drucker, MD (Lunenfeld Tanenbaum Research Institute, University of Toronto, Canada)

Dr. Dan Drucker, recipient of this year’s Banting Medal, is a truly unparalleled mind in the realm of gut hormone-related therapeutic innovations. Dr. Drucker opened by noting he was originally supposed to be a thyroid hormone specialist, but serendipitously ended up being assigned to work on the glucagon gene instead. He’s worked on proglucagon-derived peptides from the very beginning, since the first cDNAs and genes had just been cloned and no one knew what any of those peptides did. In the early days, Dr. Drucker and colleagues discovered that one fragment of the GLP-1 peptide was a potent regulator of insulin gene expression, cAMP production and beta cell secretion – it seemed trivial to him at the time, but his mentor Joel Habener filed a patent in 1986, which is the patent that has laid the foundation for GLP-1 as a therapy. Since then, Dr. Drucker and his team have extensively characterized the pharmacologic and physiologic actions of GLP-1, including characterizing GLP-1’s potential beta cell preservation and proliferation effect in mice, GLP-1’s numerous actions outside of glucose regulation, and delineating DPP-4 inhibitors’ mechanism of action. He also touched on the hot topics of pancreatic safety and potential cardioprotective effects. Notably, Dr. Drucker gave reasons not to sound the alarm over GLP-1’s consistently demonstrated effect on increasing pancreas mass – he has evidence from mice that increased pancreas mass is not due to edema, inflammation, or increased cellular proliferation. In fact, he has shown that it is due to increased protein synthesis, possibly reflecting the communication between the gut and the pancreas to increase pancreas protein synthesis following meal ingestion, however the mechanism is not fully understood. The thousands of audience members gave Dr. Drucker a thunderous standing ovation at the conclusion of his presentation.

  • Dr. Drucker described his early work in the 1980s first characterizing peptides derived from the proglucagon gene, which led to the discovery and patenting of GLP-1 as a glucose regulator. From a self-described “unimaginative” experiment that involved “dumping” several glucagon-like peptides on “as many cell cultures as we could,” Dr. Drucker and his colleagues observed that the 7-37 fragment of GLP-1 was a potent regulator of insulin gene expression, cAMP production, and beta cell secretion. At the time Dr. Drucker did not think much of the finding, but his mentor, Joel Habener, filed a patent for the molecule on May 5, 1986, which is the patent that has laid the foundation for GLP-1 agonist therapies. It was at this point, said Dr. Drucker, that he was introduced to the concept of science forming the foundation for new therapeutics, which he has since gone on to do in spades. He noted at the end of his presentation that the proglucagon gene has given rise to more drugs for the treatment of human disease than any other gene in the human genome.
  • Dr. Drucker noted that we’re still interested in new clinical ways to activate the GLP-1 receptor signaling pathway. The well known methods currently used are (i) inhibiting the inhibitor of GLP-1 by using DPP-4 inhibitors, and (ii) pharmacologically activating the GLP-1 receptor using analogs. Ongoing work remains in potentially developing GLP-1 secretagogues or neutraceuticals/functional foods that activate GLP-1 secretion from the gut.
  • In addition to the pharmacological effects of GLP-1, Dr. Drucker has also worked extensively on characterizing the role of endogenous GLP-1 using GLP-1 receptor knockout mice (Glp1r -/-).
    • GLP-1 is not only secreted after meals, but throughout the entire day: Unexpectedly,  Glp1r -/- mice had fasting hyperglycemia in addition to glucose intolerance, which led to the finding that there is not only postprandial secretion of GLP-1, but also some basal level of GLP-1 activation that helps control fasting glucose.
    • Endogenous actions other than stimulating insulin secretion include enhancing beta cell preservation and proliferation: Dr. Drucker and colleagues were also among the first to characterize GLP-1’s potential effect on beta cell preservation and proliferation. In an experiment where mice were treated with exendin-4 (exenatide’s precursor) for seven days, and given STZ to injure their beta cells, then exendin-4 treatment was stopped, three weeks later the animals that had received exendin-4 treatment had higher plasma insulin levels than those who had not and lower blood glucose levels. Dr. Drucker and colleagues were able to demonstrate that GLP-1 receptor activation was inhibiting beta cell apoptosis in mice as a direct effect of GLP-1 receptor activation on the beta cells. Furthermore, as demonstration that this was also an effect of endogenous GLP-1, not just pharmacologic GLP-1, Dr. Drucker has shown that mice with no GLP-1 receptor activity are more sensitive to STZ-induced apoptosis compared to wildtype mice. With regards to proliferation, Dr. Drucker’s lab also demonstrated that incretin receptors are necessary to for increased insulin production in response to high-fat diet-induced insulin resistance.
  • Dr. Drucker remarked that the evidence thus far presented a seeming paradox: GLP-1 could both increase insulin secretion while also preserving beta cell function (whereas other insulin secretagogues seemed to wear down beta cell function). Normally, increased protein production (in this case insulin) would upregulate endoplasmic reticulum (ER) protein synthesis, and at a certain point start causing ER stress. Dr. Drucker’s colleagues reconciled this conundrum by finding that incretin receptors directly engage several arms of the ER stress response, allowing the upregulation of insulin biosynthesis while simultaneously preserving cell survival. Dr. Drucker noted that “incretin secretion is uniquely positioned to enhance insulin secretion and prolong beta cell survival,” in contrast to other insulin secretagogues – of course the positive effect on beta cells has only been convincingly shown in mice, and human data has been sparse to date.
  • Dr. Drucker has also characterized where GLP-1 acts outside of the beta cell, including the brain. Native GLP-1 (which is a relatively small peptide) has direct central nervous system effects, and years ago it was not known whether synthetic high-molecular weight GLP-1 agonists would also be able to interact with the brain (since they would be too large to penetrate the blood-brain barrier). Dr. Drucker’s group compared exendin-4 (small peptide) to albiglutide (large peptide) and found that they produced about the same extent of central nervous system (CNS) activation, and had the same ability to inhibit food intake and reduce gastric emptying. Thus, they learned that GLP-1 does not have to directly penetrate the CNS to activate the classical actions of GLP-1 receptor signaling in the brain – Dr. Drucker noted that this finding informed the decision to move forward with development of high-molecular weight, longer-acting GLP-1 receptor agonists (e.g., Lilly’s dulaglutide and GSK’s albiglutide).
  • Dr. Drucker’s work on glucagon-derived hormones also led to a better characterization of DPP-4 inhibitors’ mechanism of action. With the DPP-4 enzyme’s dozens of substrates, it at first was not clear which ones were truly important for its effect on glucose metabolism. Dr. Drucker’s group showed that both GLP-1 and GIP receptor activation was necessary for DPP-4 inhibitors to exert their effect.
  • In working with GLP-1’s sister peptide, GLP-2, Dr. Drucker also discovered that GLP-2 stimulates small bowel growth, which led to its development as a treatment for small bowel syndrome.
  • Finally, Dr. Drucker explored the clinical relevance of some of the non-glycemic actions of GLP-1 in the intestine, pancreas, and cardiovascular system, highlighting that we still have much to learn.
    • Intestinal safety: Dr. Drucker noted that many have questioned why GLP-1 is made in the distal gut if its role is to stimulate insulin secretion after we eat (nutrients don’t reach the distal gut for several minutes or even hours after food being ingested). However, GLP-1, like GLP-2, is a potent bowel growth factor, and Dr. Drucker’s group has found that GLP-1 activation increases growth of intestinal polyps and tumors when activated in the distal bowel of a rodent cancer model. When GLP-1 receptors are removed in this model, tumor size and number significantly decrease. Dr. Drucker implied that we may need to more closely monitor the potential for inappropriate intestinal growths in treating patients with GLP-1 agonists.
    • Pancreatic safety: GLP-1 has been consistently found to increase the mass of the mouse pancreas by about 10%, but Dr. Drucker gave reasons not to sound the alarm over potential tumor formation – he noted that “what we have failed to address, as a community, is why the pancreas is bigger.” Dr. Drucker’s team has shown that the increased pancreas size is not due to increased inflammation, edema (water and edema actually decreases in mice given exendin-4), or cellular proliferation. The reason he has pinpointed is that it GLP-1 stimulates the pancreas to make more protein in response to meal intake. We believe we heard Dr. Drucker say that his team has identified which proteins are selectively modulated by GLP-1 signaling in the mouse pancreas, but he did not disclose what those were. The takeaway here is increased pancreatic mass on its own is no reason to jump to conclusions about potential for pancreatic cancer – however, he noted that we do not completely understand the mechanisms through which GLP-1 receptor signaling modifies pancreatic protein synthesis.
    • Cardiovascular effects: GLP-1’s cardioprotective effects on mice have been well established, and Dr. Drucker noted that for years we assumed it was due to direct activation of GLP-1 receptors on ventricular cardiomyocytes (which are the cells most directly involved in CV events like heart failure or myocardial infarction). However, Dr. Drucker upended this thinking by showing that the receptor is not actually expressed in the ventricular cardiomyoctyes. Instead, it has been found in the atrium. Dr. Drucker, furthermore, has shown that direct GLP-1 receptor activation in the heart is not even necessary for GLP-1 to exert its cardioprotective effects: a mouse model with no GLP-1 receptor expression in the heart was no different than a wildtype mouse with full GLP-1 receptor expression when responding to ischemia (blood supply shortage). Therefore, Dr. Drucker concluded that GLP-1 does not act directly on the heart to exert its potential cardioprotective effects, but likely acts through some other unknown indirect mechanism. So the obvious next question is why there are GLP-1 receptors in the atria in the first place – Dr. Drucker demonstrated that these receptors were actually important for heart rate regulation rather than playing a role in cardioprotection. Dr. Ducker gave a presentation on this topic at the Keystone Symposium on Diabetes Complications earlier this year.
  • Looking to the future, Dr. Drucker outlined a slew of potential new roles for GLP-1 agonists: as potential treatments for obesity, prediabetes, type 1 diabetes, children with type 2 or type 1 diabetes, neuroprotection and neurodegeneration, anti-inflammation, fatty liver disease, cardiovascular indications, and microvascular disease.

Oral Presentations: Advances in the Diagnosis and Treatment of Type 1 Diabetes

Combination Low-Dose Antithymocyte Globulin (ATG) And Granulocyte Colony Stimulating Factor (GCSF) Preserves Beta-Cell Function In Patients With Established Type 1 Diabetes (T1D) (173-OR)

Michael Haller, MD (University of Florida, Gainesville, FL)

Dr. Michael Haller presented positive efficacy results for low-dose antithymocyte globulin (ATG) and granulocyte colony stimulating factor (GCSF) in patients with recent onset type 1 diabetes (four months to two years). In the single blinded trial (n=25) people were randomized to either 2:1 ATG-GCSF (2.5 mg/kg ATG over two days and 6 mg GCSF every two weeks for 12 weeks) or placebo, and subsequently followed for 12 months. Dr. Haller noted that the trial was in a later stage of type 1 diabetes, than they normally would have enrolled for such a treatment. This decision was made, because one of the trial’s sponsors, the Helmsley Charitable Trust, wanted to re-enfranchise people who fall outside the new onset window, typically tested (the other sponsor was Sanofi). In light of the trial population, the efficacy results look promising. The treatment arm’s two-hour C-peptide level was preserved over the 12 months at ~2 ng/ml (baseline was 2.14 ng/ml). In contrast, the placebo group experienced a significant C-peptide decline to ~1 ng/ml (p-value for the difference between the two groups = 0.05). Unfortunately, this preservation of C-peptide was not concomitant to either a better A1c or a lower insulin dose, as compared to the placebo group. On the safety side, Dr. Haller seemed disappointed in the rates of adverse events: 14 of the 17 participants in the experimental arm experienced cytokine release syndrome (a side effect of anti-T cell antibody infusions like ATG, producing a systemic inflammatory response) and/or serum sickness. With the presentation of preliminary positive results for both the Brazil cocktail and ATG/GCSF, an emerging question is what level of risk patients (and the FDA) is willing to accept in a potential type 1 diabetes cure. 

  • Dr. Haller called the ATG/GCSF combination “Brazil Lite,” in reference to it being a (less intense) modification of the Brazil Cocktail (aka the Voltarelli Cocktail). The Brazil Cocktail uses high doses of immunosuppressants (cyclophosphamide and antithymoctye globulin [ATG]) to largely wipe out the immune cells. Patients are then “rescued” with an autologous hematopoietic stem cell transplant (AHSCT). The hope is that the immune system will redevelop without islet autoimmunity. Indeed, on Saturday, results were published on this approach showing that it can lead to sustained insulin independence. However, this treatment also have substantial risks – in the study presented on Saturday (n=65), a participant died from sepsis, potentially due to the severe immunosuppression. Thus, researchers have been working to determine which components of the Brazil cocktail are necessary and sufficient for efficacy, and which can be omitted to improve safety. Previously, the phase 2 START trial found that ATG (an anti-T cell antibody infusion) monotherapy failed to significantly delay two-hour C-peptide AUC decline over 12 months in people with recent onset type 1 diabetes, indicating that ATG alone was not sufficient (though the ATG/GCSF trial was already ongoing when these negative results were announced).
  • This trial was single blinded and 2:1 randomized 25 people with recent onset diabetes to ATG-GCSF (2.5 mg/kg ATG over two days and 6 mg GCSF every two weeks for 12 weeks) or placebo. Participants had type 1 diabetes for between four months and two years at baseline. Dr. Haller noted that patient population had a later stage of type 1 diabetes (people had type 1 diabetes for four months to two years, rather under two months as has been more commonly selected in recently trials), than they normally would have enrolled for such a treatment. This decision was made, because one of the trial’s sponsors, the Helmsley Charitable Trust, wanted to re-enfranchise people who fall outside the new onset window, typically tested (the other sponsor was Sanofi).
    • The dose of ATG used in this trial was one of the lowest seen in immunotherapy work, according to Dr. Haller. For comparison, in the START trial the ATG dose was of 6.5 mg/kg. The researchers felt they could use a lower dose of ATG, due to the concomitant administration of GCSF. In rodents, they found that they could reverse diabetes using one-third the successful monotherapy dose, when ATG was given in combination with GCSF.

Characteristic

ATG/GCSF arm (n=17)

Placebo (n=8)

Male (%)

76%

62%

Age (years)

23.64 years

23.55 years

Time from diagnosis (years)

1.04 years

0.93 years

AUC 2-hr C-peptide (ng/ml)

2.14 ng/ml

2.13 ng/ml

A1c

6.69%

6.03%

Daily insulin dose (U/kg)

0.44 U/kg

0.45 U/kg

  • The treatment arm’s two-hour C-peptide level was preserved over the 12 months at ~2 ng/ml (baseline was 2.14 ng/ml). In contrast, the placebo group experienced a significant C-peptide decline to ~1 ng/ml from a baseline of 2.13 ng/ml. At month 12, the p-value for the difference between the two groups was 0.05.
    • At this point, it is unclear why ATG/GCSF successfully preserved C-peptide, while ATG monotherapy did not. One hypothesis for why ATG/GCSF was successful where ATG was not is that ATG/GCSF better preserved levels of regulatory T cells (that are thought to restrain autoimmunity). At the 2014 Rachmiel Levine Diabetes and Obesity Symposium, it was hypothesized that the approach might have failed because it worsened the ratio of regulatory T cells and effector T cells (that are thought to drive autoimmunity). However, with ATG/GCSF it appeared that Treg levels were better preserved. This could potentially be the result of the lower ATG dose (such that fewer Tregs are destroyed), or that GCSF promotes the production of new Tregs.
  • Unfortunately, this preservation of C-peptide was not concomitant to either a better A1c or a lower daily insulin dose, as compared to the placebo group. The experimental group’s mean A1c increased 0.52% from a mean baseline of 6.69%.  This was not statistically significantly different from the placebo group’s mean A1c increase of 0.97% from a mean baseline of 6.03%. The only time point at which the A1c difference significantly differed (in favor of the treatment group) between the two groups was at six months. Likewise, the two groups’ course of insulin use did not significantly differ (baseline insulin doses were 0.44 U/kg and 0.45 U/kg for the treatment and placebo groups, respectively). As an attendee mentioned during Q&A, it would have been interesting to see if time in zone was improved in the treatment arm, even though A1c and insulin dose were not. Though there are many potential explanations for the discrepancy between the C-peptide, A1c, and insulin results, it is possible that the beta cell destruction was already too great at baseline for these measures of glycemic control to appreciably improve (indeed, a C-peptide level of ~2 ng/ml, while potentially clinically beneficial over a lower level, is still quite small). If this is the explanation for these results, we would be interested in seeing if a beta cell regenerative agent could be added to this combination to stimulate the growth of a new beta cells ­– of course, this first requires the identification of such an agent.
    • Participants of this trial are being followed for a total of five years – we are curious whether the C-peptide results are sustained over the long-term, and if significant differences in either A1c or insulin dose arise. All participants will have passed the two year mark in December 2014.
  • Though the rate of adverse events was better in this trial than it was in the START trial (of ATG monotherapy), Dr. Haller seemed disappointed in the relatively high rates ­– 14 of the 17 participants in the experimental arm experienced cytokine release syndrome (a side effect of anti-T cell antibody infusions like ATG, producing a systemic inflammatory response) and/or serum sickness.
  • A trial of ATG/GCSF in people (ages 12-45 years) who have been newly diagnosed with type 1 diabetes is to begin in the summer of 2014. People in this trial will have been diagnosed within 100 days. The trial is being run with TrialNet, and is sponsored by Sanofi, the Helmsley Charitable Trust, Amgen, and the NIH.

Questions and Answers

Q: Congratulations, did you have a chance to look at autoantibodies?

A: So far we have not seen any difference in autoantibody titers.

Q: Do you have CGM data in this trial?

A: I think that is a great idea for the next study. Patients certainly reported that they had less variability.

Phase I Trial Using Ex Vivo Expanded Polyclonal Tregs for Recent-Onset Type 1 Diabetes (174-OR)

Stephen Gitelman, MD (UCSF, San Francisco, CA)

Dr. Stephen Gitelman detailed data from a JDRF-funded phase 1 clinical study on the safety and tolerability of UCSF’s autologous T regulatory cell (Treg) immunotherapy for recent-onset type 1 diabetes. The study enrolled 14 patients between the ages of 18 and 45 (mean of 30 years) with disease duration of three to 24 months (mean of 10 months). The process used to harvest, grow, and purify Tregs for infusion was developed by the renowned Dr. Jeffrey Bluestone (UCSF, San Francisco CA) (Putnam et al., Diabetes 2009). The primary goal of the study was to confirm the approach’s basic safety and tolerability, which it accomplished: the Treg infusions were well tolerated, with no infusion site reactions and no significant infectious issues. The Tregs themselves peaked in circulation during the first week of infusion and diminished from then on, though they remained detectable more than six months after the initial fusion. Full two-year data was only available for the six patients who received the smallest cellular doses. In these groups, C-peptide levels and A1c remained fairly stable over the entire time period, with perhaps a slight upward trend in exogenous insulin usage. The incomplete data from patients who received larger doses of Tregs was more variable, but it was too early to tell, and the study is not sufficiently powered to examine efficacy. Dr. Gitelman believes that the strong safety and tolerability profile demonstrated in this trial (especially relative to harsher immunotherapies therapies out there) sets the stage for phase 2 testing. Notably, NeoStem has licensed the Treg technology from UCSF, and is partnering with UCSF and TrialNet  for phase 2 development.

  • Dr. Gitelman first provided background on the Treg expansion therapy studied in the trial. The progression of type 1 diabetes is believed to stem from a relative overabundance of effector T cells (Tems) that lead the autoimmune attack and a lack of Tregs, which suppress Tems activity. The idea behind the therapy is that a Treg “boost” could restore immune balance; results in preclinical models have been promising. Dr. Gitelman suggested that this approach could avoid the toxicity and side effects of other T-cell-targeted therapies such as ATG/GCSF and anti-CD3 antibodies.
  • The ability to successfully grow and purify Tregs was a prerequisite to the successful implementation of this therapy. Using a protocol developed by Dr. Bluestone’s group (Putnam et al., Diabetes 2009), Dr. Gitelman’s team was able to achieve over 500x expansion of the cell population in two weeks. The approach uses flow cytometry to sort and purify the sample. 
  • The phase 1 trial set out to establish the basic safety and tolerability of a single dose of the Treg infusion therapy. Enrollment was limited to type 1 diabetes patients who were three to 24 months from diagnosis, age 18 to 45 years, had at least minimal levels of C-peptide (>0.1 pmol/ml following a meal test), and did not have any diabetes complications. The group of 14 patients was divided into four cohorts, each of which was given a different cell dose (ranging from 5x106 to 2.6x109 cells, ordered from cohort #1 through #4 in order of increasing dose). The study is scheduled to last five years, and the results presented yesterday were for two years follow-up (for cohorts 1 & 2) and one year follow-up (for cohorts 3 & 4).
  • The study results confirmed the therapy’s safety across the range of doses. The infusion was well tolerated, with no infusion site reactions. There were no significant infectious issues, and the majority of events were not related to the treatment.
  • The injected Tregs peaked in concentration approximately three to seven days following administration in the two higher dose cohorts, and were still detectable six months following injection (albeit at greatly reduced concentrations). Deuterated glucose was used to track the Tregs. The gradual loss of signal might be due to a decrease in Tregs, which would mean that the therapy would need to be regularly readministered. However, the signal disappearance could also be due to cell division, cell trafficking out of circulation, or another process that might not necessarily lead to a cessation of Treg action.
  • Dr. Gitelman next presented C-peptide data – it was hard to conclude much from this data, as the study size is quite small. In cohorts 1 and 2, C-peptide levels and A1c appeared to remain fairly stable over two years. Overall subjects in these groups were well-controlled, with perhaps a slight uptick in insulin dose. One patient in each of the higher dose cohorts had poor glycemic control, which made it harder to interpret the one-year results from those cohorts, especially given the small sample size and short duration.
  • Cells were isolated and expanded at UCSF then shipped to Yale. This speaks to the stability of the cell population, and could make it both easier to conduct large trials and contribute to the therapy’s commercial viability (if the therapy reaches the market down the road). 
  • The safety data, Dr. Gitelman stated, paves the way for a phase 2 study, which will be a partnered effort with TrialNet and product licenser NeoStem. Dr. Gitelman mentioned in his conclusion that at least one other group (Trzonkowski et al., Diabetes Care 2012, Clin Immunol 2014) has been working on Treg therapy in pediatric type 1 diabetes patients, and has found similarly acceptable tolerability as well as hints of efficacy.

Questions and Answers:

Q: So far, we have been disappointed with findings from cord blood transfusion studies. Why would you think that this would work better, especially if you are not creating space by ablating before you infuse?

A: One limitation of cord blood is the number of Tregs that are infused. We need to think of another way to enrich it before it goes in vivo. We’ve discussed this at UCSF.

Dr. Michael Haller: We are working on expanding studies of Tregs in cord blood now. The hope is to do a pilot study, with results that could be at least as good or even better than these.

Oral Presentations: Oral Incretin-Based Therapies

TTP273, an Orally-Available Glucagon-like Peptide-1 (GLP-1) Agonist, Notably Reduces Glycemia in Subjects with Type 2 Diabetes Mellitus (155-OR)

Stephanie Gustavson, PhD (Trans Tech Pharma, High Point, NC)

Dr. Gustavson presented data from a dose-ranging study of TTP273, Trans Tech’s second-generation oral GLP-1 agonist, in patients with type 2 diabetes (n=112). The objective of this trial was to evaluate the safety, tolerability, and PK/PD profile of TTP273. Dr. Gustavson commented that this second-generation oral GLP-1 agonist demonstrated increased potency compared to Trans Tech’s first-generation oral GLP-1 agonist, TTP054. In terms of efficacy, dose-responsive decreases in fasting plasma glucose and mean daily glucose were observed (39 mg/dl and 42 mg/dl, respectively, at the 75 mg BID dose). In addition, there were very few GI-related adverse events, with only four patients in the entire study exhibiting any nausea. However, given that this was a dose-ranging study and many patients received low doses of TTP273, we look forward to longer-term trials with therapeutic doses of TTP273 to better understand the adverse event profile and GI-related side effects.

  • Trans Tech conducted a 14-day inpatient clinical trial of TTP273 in type 2 diabetes patients on stable doses of metformin. Patients were checked into a clinical research facility for three weeks – arriving five days prior to the first dose and remaining until day 16. The purpose of the inpatient design was to ensure adherence and standardize diets, in order to isolate the glycemic effects of TTP273. The study included a 23-point mean daily glucose assessment and a mixed meal tolerance test (MMTT) on days -1 and 14. The trial investigated a broad range of dosing options, with 10 dose cohorts (25-450 mg QD, 25-150 mg BID, and an alternative dosing of 75 mg QPM).
  • Treatment with TTP273 was associated with dose-responsive decreases in mean daily glucose and fasting glucose. At baseline, the mean A1c was 8.1% (8.5% in placebo and 8.0% in active). TTP273 was quickly absorbed, with a tmax of two hours and a half-life of six hours. The 24-hour glucose profile showed maximal reduction in glycemic control at the 150 mg BID and 450 mg QD doses; however, the BID and QPM regimens resulted in greater glucose lowering compared to the QD regimens. For mean daily glucose, TTP273 resulted in a 42 mg/dl reduction (75 mg BID), which was significantly greater than the 11 mg/dl reduction observed in the placebo group. TTP273 also significantly reduced fasting glucose, with patients in the 75 mg BID arm experiencing a 39 mg/dl reduction in FPG compared to 11 mg/dl in the placebo group.
  • All adverse events were characterized as mild, with diarrhea being the most common GI-related adverse event. There were no serious adverse events or incidences of hypoglycemia. While diarrhea was the most frequent GI adverse event, Dr. Gustavson noted that there was no clear dose response relationship for this adverse event and that it often occurred on meal test days when patients were required to consume meals in a certain period of time.
  • While this study was not designed to assess changes in secondary parameters, there were favorable trends in metabolic and cardiovascular markers. While specific data on secondary markers were not disclosed, Dr. Gustavson commented that there was a trend toward reduced body weight (up to 2 kg) and improvements in triglycerides, systolic blood pressure, and diastolic blood pressure.

Questions and Answers

Q: Could you say more about the chemical that is being administered and how it mimics and acts on GLP-1 receptor?

A: This compound is an allosteric agonist of the receptor. We’ve shown that exendin (9-37) competes with functional activity and we don't activate glucagon or GIP. What’s really interesting is that it may be more physiological in terms of cell signaling and receptor bias activation. Our compound does not activate ERK pathway, unlike current GLP-1 agonists; it just activates the cAMP pathway, so there may be a lower risk of cell proliferation.

Q: So it is acting on a different site on the receptor?

A: Yes.

TTP054, a Novel, Orally-Available Glucagon-like Peptide-1 Agonist, Lowers HbA1c in Subjects with Type 2 Diabetes Mellitus (156-OR)

Stephanie Gustavson, PhD (Trans Tech Pharma, High Point, NC)

In back-to-back presentations, Dr. Gustavson provided results from a 12-week trial of Trans Tech Pharma’s first-generation oral GLP-1 agonist, TTP054. In the trial, subjects with type 2 diabetes on stable metformin were randomized to receive 200 mg QD (n=19), 400 mg QD (n=28), or 800 mg QD (n=35) TTP054 or placebo (n=31) for 12 weeks. Results indicated placebo-corrected A1c declines of 0.9% (baseline 9.1%), 1.0% (baseline 9.0%), and 0.6% (baseline 8.8%) with the 200, 400, and 800 mg dose groups, respectively – similar to the values estimated from phase 1 data at ADA 2013. Weight loss was non-significant across the groups, at 0.1 kg (0.2 lbs), 0.4 kg (0.9 lbs), and 0.7 kg (1.5 lbs) in the 200, 400, and 800 mg dose groups, respectively, though Dr. Gustavson noted weight loss became significant when patients who discontinued sulfonylureas at baseline were excluded from the analysis; she also noted that weights at baseline were relatively low for diabetes trials (82-87 kg; 181-192 lbs). Rates of GI adverse events were 4%, 4%, and 16% in the 200, 400, and 800 mg dose groups, respectively, and 10% in the placebo group. Dr. Gustavson suggested the second-generation agonist, TTP273, has shown increased potency in early studies, though we will be interested to see how this plays out in clinical trials. As a reminder, there has increasing interest in oral formulations of GLP-1 as of late, with numerous candidates in clinical trials, including Novo Nordisk’s NN9924 (phase 2), NN9928, NN9926, and NN9927, Oramed’s ORMD-0901 (phase 2), and Zydus’s ZYOG1 (phase 1).

  • In this double-blind trial, subjects with type 2 diabetes on stable metformin were randomized to receive 200 mg QD (n=19), 400 mg QD (n=28), or 800 mg QD (n=35) TTP054 or placebo (n=31) for 12 weeks. Patients on sulfonylureas at baseline stopped use with a wash out period prior to initiation in the trial. Baseline weights were 83 kg (182 lbs), 82 kg (181 lbs), and 87 kg (192 lbs) in the 200, 400, and 800 mg dose groups, respectively, and 84 kg (185 lbs) in the placebo group.
  • Results indicated placebo-corrected A1c declines of 0.9% (baseline 9.1%), 1.0% (baseline 9.0%), and 0.6% (baseline 8.8%) with the 200, 400, and 800 mg dose groups, respectively, with no clear dose response (p<0.01). Weight loss, however, increased with increased dose, a 0.1 kg (0.2 lbs), 0.4 kg (0.9 lbs), and 0.7 kg (1.5 lbs) in the 200, 400, and 800 mg dose groups, respectively, though results were not significant. Dr. Gustavson noted that when patients who discontinued sulfonylureas at the beginning of the trial were excluded from the analysis, weight loss became significant across the groups. She posited this may gave been due to shifting weights at baseline in this population.
  • Rates of GI adverse events were 4%, 4%, and 16% in the 200, 400, and 800 mg dose groups, respectively, and 10% in the placebo group. There were no episodes of hypoglycemia during the study. Dr. Gustavson indicated that two patients in the 800 mg dose group experienced serious adverse events with regards to elevated liver function test levels, though when scrutinized both occurred with contributing factors and resolved. She suggested this was not a major concern for the company given there was no increase in median liver function tests over the other dose groups and elevated levels were never seen in other clinical studies of the drug.

Questions and Answers

Dr. Zachary Bloomgarden (Mt. Sinai, New York, NY): Is the newer agent more potent for fasting blood glucose when corrected for baseline?

A: We compared earlier studies with this compound. Our second-generation compound does seem to lower more than our leading compound.

Q: Does the drug reach the brain?

A: They do not – we feel it is neural signaling in the gut that acts in the brain.

Q: Did you look at the population that did not respond at all?

A: We did. We were unable to identify why that could be. But I think it’s similar to what we see with the peptides with response rates.

Q: What about heart rate?

A: This wasn’t designed to pick that up. We did see minor fluctuations but didn’t see any major increases in heart rate. I think we need long-range studies to definitively answer that.

Oral Glucose Lowering with Linagliptin Plus Metformin Is a Viable Initial Treatment Strategy in Patients with Newly Diagnosed Type 2 Diabetes and Marked Hyperglycemia (150-OR)

Stuart Ross, MD (University of Calgary, Alberta, Canada)

Dr. Ross presented the results of a pre-specified subgroup analysis from a 24-week clinical trial comparing linagliptin+metformin to linagliptin alone in newly diagnosed type 2 diabetes patients. This sub-analysis examined A1c reductions only in patients with extreme hyperglycemia (9.5% A1c at baseline). After 24 weeks, patients on the linagliptin+metformin combination experienced robust A1c reduction of 3.4%, compared to a 2.5% reduction in the linagliptin alone group (from a high baseline A1c of 10.5%). These A1c reductions translated into 61% of patients achieving a target A1c of <7% in the linagliptin+metformin group, and 40% of patients achieving target A1c in the linaglitpin alone group. Dr. Ross acknowledged he was not expecting such a robust A1c reduction with linagliptin alone or in combination. As a result, he challenged the commonly held belief that insulin initiation is required to achieve target A1c levels in newly diagnosed patients with extreme hyperglycemia. Furthermore, during Q&A, Dr. Zachary Bloomgarden hypothesized that newly diagnosed patients may be uniquely responsive to glycemic control interventions, citing data from the UKPDS study that showed similarly impressive A1c reductions during a three-month diet-based run-in period.

  • The 24-week randomized trial compared linagliptin+metformin vs. linagliptin in drug-naïve type 2 diabetes patients within 12 months of diagnosis. In this study, patients on linagliptin+metformin experienced an A1c reduction of 2.7% compared to 1.7% for patients on linagliptin alone (from a mean baseline A1c of 9.8%). In the per-protocol cohort, the linagliptin+metformin combination was associated with a 2.8% reduction in A1c, compared to 2.0% reduction in the linagliptin arm.
  • Notably, the subgroup analysis revealed that the majority of patients with baseline A1c ≥9.5% achieved an A1c <7% after 24 weeks of treatment with linagliptin+metformin. For patients with a baseline A1c <9.5%, the linagliptin+metformin group experienced an A1c reduction of 2.0%, which was significantly greater than the 1.4% reduction in the linagliptin alone group (mean baseline A1c of 8.7%). For the cohort of patients with a baseline A1c ≥9.5%, the linagliptin+metformin combination was associated with an impressive 3.4% reduction in A1c, compared to a 2.5% reduction in the linagliptin alone group (mean baseline A1c of 10.5%). These reductions in A1c were consistent across all major subgroups, including age, BMI, renal function, race, and ethnicity.

Questions and Answers

Dr. Zachary Bloomgarden, MD (Mount Sinai Hospital, New York, NY): Congratulations on getting 300 treatment-naïve patients recruited into your study. That is quite an accomplishment. This is reminiscent of the UKPDS cohort, where patients entered the trial with an A1c of 9%, had a three-month diet run-in and on average went to 7% with diet alone, suggesting this may indeed be a group of people who are uniquely able to respond to all sorts of interventions. So it’s fascinating that linagliptin alone was not bad.

A: It was a little bit of a surprise to us. We raised the question ourselves of diet and exercise. In the lingliptin alone group, there was no weight loss and in the linagliptin+metformin combination group, there was 1 kg weight loss. It’s interesting how we’ve always been led to insulin being the right way to bring A1c down in this patient population.

Q: Did response rates differ by race or ethnicity?

A: We wondered about that because there has been a lot of interest in this, especially with international clinical trials. There appears to be differences in some other treatments, so we did look for bias. We didn't have a large range of ethnicities (Hispanic, Asian, and Caucasian); however, we saw no difference at all among these racial subgroups. That does not mean there is no difference, we just did not find any evidence of a difference.

Q: Did you exclude ketonuria?

A: There were no patients with ketonuria. We were worried we’d be seeing type 1 diabetes instead of type 2 diabetes, so ketones were assessed, but nothing suggested they had ketonuria.

Posters

Efficacy and Tolerability of ITCA 650 (Continuous Subcutaneous Exenatide in Poorly Controlled Type 2 Diabetes with Baseline A1c >10% (114-LB)

Robert R. Henry, Julio Rosenstock, and Michelle A. Baron

Dr. Robert Henry and colleagues report six-month data from an open-label trial of Intarcia Therapeutics’ ITCA 650 (continuous subcutaneous exenatide infusion) in 60 type 2 patients with baseline A1c >10% (FREEDOM-1HBL). The participants first received the three-month, low dose (20 mcg/day) ITCA 650 mini-pump for 13 weeks followed by the six-month high dose (60 mcg/day) mini-pump for 26 weeks. Background anti-diabetic medications were maintained for the treatment period. This initial interim analysis included data from the patients who had completed treatment up to 13 weeks (n=50), 19 weeks (n=39), or 26 weeks (25). Increasing reductions in A1c were observed at each time point: -2.5% at 13 weeks, -2.9% at 19 weeks, and -3.2% at 26 weeks. Furthermore, an impressive proportion of these patients achieved A1c reductions of 2% (78%), 3% (50%), 4% (22%), and ≥5% (10%). Of the cohort, 30% achieved the A1c target of 7% and only two patients were classified as non-responders (i.e., A1c reduction <0.05% at the time of the interim analysis). Lastly, a mean weight loss of 2.4 lbs (1.1. kg) was observed at 26 weeks. Based on these data, the authors conclude that ITCA 650 has the potential to markedly improve glycemic control in patents with severe hyperglycemia and longstanding diabetes.

  • This study enrolled 60 type 2 patients whose high A1c level (>10%) made them ineligible to participate in the main double-blind placebo-controlled trial (FREEDOM 1). These patients met all of the other inclusion criteria for FREEDOM 1. At baseline, the participants had a mean age of 52 years, BMI of 32 kg/m2, A1c of 10.7%, fasting plasma glucose of 248 mg/dl, and duration of diabetes 9 years. Sixty-nine percent of the cohort also used oral anti-diabetic medications and 33% were male.
  • The figure below gives mean baseline A1c and mean A1c reduction for participants completing treatment periods of 13, 19, and 26 weeks:

 

13 weeks     (n=50)

19 weeks    (n=39)

26 weeks   (n=25)

Mean baseline A1c

10.8%

10.7%

10.9%

Mean A1c at timepoint

8.3%

7.8%

7.7%

Mean change in A1c

-2.5%

-2.9%

-3.2%

  • The authors note that adverse events were consistent with previous trials with ITCA 650 (data not provided).

Fixed Dose Combinations of Empagliflozin/Linagliptin for 24 Weeks in Drug-Naïve Patients with Type 2 Diabetes (T2DM) (129-LB)

A Lewin, R DeFronzo, S Patel, D Liu, R Kaste, HJ Woerle, UC Broedl

The first of two phase 3 posters on Lilly/BI’s Jardiance/Trajenta (empagliflozin/linagliptin; “empa/lina”) presented the results of a study in 667 drug-naïve type 2 diabetes patients. There has been a great deal of excitement about the combination of DPP-4 inhibitors and SGLT-2 inhibitors, as the combination of an insulin-dependent and insulin-independent mechanism of action were thought to potentially yield additive or synergistic efficacy. While the efficacy seen with the high-dose FDC (empagliflozin 25 mg/linagliptin 5mg) was certainly strong for an oral compound, it fell well short of additive efficacy – in fact, it did not achieve a statistically significantly greater A1c reduction than empagliflozin monotherapy. Empa/lina 25 mg/5 mg yielded a mean A1c reduction of 1.08% after 24 weeks, compared to -0.67% with linagliptin 5mg (p<0.001) and -0.95% with empagliflozin 25 mg (p = 0.179), from a baseline of ~8%. From what we could tell, the results may have been dampened by a weaker-than-expected performance from the high-dose FDC group, as the lower-dose FDC (empa 10 mg/lina 5 mg) had a greater mean A1c reduction (-1.24%) and achieved statistically significantly better efficacy than its component monotherapy doses. A sub-analysis in patients with a baseline A1c at or above 8.5% yielded slightly more logical results: although the high-dose FDC once again did not achieve significantly greater A1c reduction than empagliflozin 25 mg monotherapy, it was not less effective than the lower-dose FDC. Although the results were not altogether negative (A1c reductions of over 1% for an oral are impressive), it was somewhat disappointing to not see truly additive efficacy with the combination.

  • The phase 3 study randomized 677 drug-naïve type 2 diabetes patients – 667 completed the trial. Patients were randomized to one of five treatments: empagliflozin 25 mg/linagliptin 5 mg, empagliflozin 10 mg/linagliptin 5 mg, empagliflozin 25 mg, empagliflozin 10 mg, and linagliptin 5 mg. The poster presented 24-week data, but the study will go on for a total of 52 weeks.
  • Empa/lina demonstrated solid efficacy and non-glycemic effects, but the high-dose combination performance was weaker than we might have expected. The high-dose combination fell short of the low-dose combination across categories, from A1c reduction (1.08% vs. 1.24%, respectively), the number of patients reaching an A1c goal of below 7.0% (55% and 62%, respectively), and weight loss (-2.0 kg [~4 lbs] and -2.7 kg [6 lbs]). While the A1c reductions seen with the low-dose combination were statistically significantly greater than those seen with its component monotherapies, the high-dose combination did not achieve statistical superiority over high-dose empagliflozin monotherapy, although it did over linagliptin monotherapy. The percentage of patients achieving a final A1c below 7.0% provided a more positive framing of the data than did the raw mean A1c reductions. 
  • As opposed to the metformin add-on trial (see 130-LB below), empa/lina did not demonstrate significant reductions in fasting plasma glucose relative to empagliflozin monotherapy. The combinations did achieve reductions in FPG over linagliptin monotherapy, on the order of ~23 mg/dl.
  • Interestingly, in this study, there was no clear increase in genital infections with empagliflozin, either as monotherapy or in combination with linagliptin. However, the number of overall events was quite small. Other adverse events were more or less balanced between groups.

Fixed-Dose Combinations of Empagliflozin/Linagliptin for 24 Weeks as Add-On to Metformin in Patients with Type 2 Diabetes (T2DM) (130-LB)

R DeFronzo, A Lewin, S Patel, D Liu, R Kaste, HJ Woerle, UC Broedl

The second of two phase 3 posters on Lilly/BI’s Jardiance/Trajenta (empagliflozin/linagliptin; “empa/lina”) presented the results of a study in 674 type 2 diabetes patients on background metformin. As opposed to the other empa/lina poster, the efficacy results here were more logical and consistently statistically significant. From a baseline of ~8%, the high-dose combination (empa 25 mg/lina 5 mg) arm achieved a mean A1c reduction of 1.19%, which beat out the 0.62% reduction with empagliflozin 25 mg and 0.70% reduction with linagliptin 5 mg – we found it interesting that linagliptin had numerically greater efficacy than empagliflozin in this trial. The lower-dose combination (empa 10 mg/lina 5 mg) achieved a mean A1c reduction of 1.08%, while the empagliflozin 10 mg arm achieved a mean reduction of 0.66%. Over 60% of patients on the high-dose combination achieved a final A1c below 7%, while only 33% of empagliflozin 25 mg patients and 36% of linagliptin patients achieved that goal. Weight loss appeared to be tied to the empagliflozin dose – empagliflozin 25 mg (with or without linagliptin) led to a mean weight reduction of ~3 kg (~7 lbs), while empagliflozin 10 mg (with or without linagliptin) led to about a pound less weight loss. Genital infections were more common with empagliflozin, but the relationship did not appear to be dose-dependent. Overall, the combination (and each of the component monotherapies) was well tolerated. Although the A1c reduction for the combination was not additive, the percentage of patients who achieved a goal of < 7.0% was fairly close to additive.

  • The study enrolled 686 type 2 diabetes patients on background metformin – 674 patients completed the study. Patients were randomized to one of five treatments: empagliflozin 25 mg/linagliptin 5 mg, empagliflozin 10 mg/linagliptin 5 mg, empagliflozin 25 mg, empagliflozin 10 mg, and linagliptin 5 mg. The poster presented 24-week data, but the study will go on for a total of 52 weeks.
  • Both empa/lina arms achieved a mean A1c reduction over 1%. From a mean baseline of ~8%, the empa 25 mg/lina 5 mg arm achieved a mean A1c reduction of 1.19%, which was significantly greater than the 0.62% reduction in the empagliflozin 25 mg arm and 0.70% reduction in the linagliptin arm. We found it interesting that linagliptin beat out empagliflozin – it seemed like the high-dose empagliflozin arm performed worse than might have been expected. The empa 10 mg/lina 5 mg arm achieved a mean A1c reduction of 1.08%, relative to a 0.66% reduction in the empagliflozin 10 mg arm. All comparisons between the combination arms and component monotherapies were highly statistically significant.
    • The poster also broke out mean A1c reductions for patients with a baseline A1c at or above 8.5%. From a mean baseline of ~9.1%-9.3%, the high-dose combination group experienced a mean reduction of 1.84%, the low-dose combination group experienced a mean reduction of 1.61%, the high-dose empagliflozin group experienced a mean reduction of 1.22%, the low-dose empagliflozin group experienced a mean reduction of 1.29%, and the linagliptin arm achieved a mean reduction of 0.99%. All comparisons between the combination arms and the component monotherapies were highly statistically significant.
    • Empa/lina helped more patients achieve an A1c goal of less than 7%. Approximately 62% of the high-dose combination group and 58% of the low-dose combination group achieved that goal, compared to 33% of the high-dose empagliflozin group, 28% of the low-dose empagliflozin group, and 36% of the linagliptin group.
    • Both empa/lina combinations achieved significantly greater fasting plasma glucose reductions than the component monotherapies. The difference between the high-dose combination and high-dose empagliflozin was 16 mg/dl, while the difference between the high-dose combination and linagliptin was 22 mg/dl.
  • The reduction in weight from baseline appeared to largely be a function of the empagliflozin dose, independent of combination with linagliptin. The high-dose combination arm and high-dose empagliflozin arm lost 3 kg (~7 lbs), while the low-dose combination and low-dose empagliflozin groups lost 2.5 kg (~6 lbs). The linagliptin group lost less than 1 kg (~2 lbs).
  • Adverse events were generally balanced between groups.

Efficacy and Safety of Once Weekly Dulaglutide vs. Once Daily Liraglutide in Type 2 Diabetes (AWARD-6) (110-LB)

KM Dungan, ST Povedano, T Forst, JGG González, C Atisso, W Sealls, JL Fahrbach

This poster presented the results of the long-awaited AWARD-6 trial, which found that Lilly’s once-weekly GLP-1 agonist dulaglutide provided non-inferior A1c lowering relative to Novo Nordisk’s once-daily Victoza (liraglutide). The open-label study randomized 599 type 2 diabetes patients on metformin. Head-to-head studies can sometimes use fairly wide non-inferiority margins (we’ve seen as large as 0.4%), so even though the topline results announced that dulaglutide achieved non-inferiority, there were plenty of potential surprises in the full data. However, the two drugs had similar glycemic effects – dulaglutide led to a mean A1c reduction of 1.42%, while liraglutide 1.8 mg led to a mean reduction of 1.36% (p < 0.001, baseline A1c = 8.1%). Approximately 68% of both groups achieved a final A1c of less than 7%, and seven-point SMBG profiles were effectively superimposable. The slight differences between groups emerged in the weight and hypoglycemia categories. Patients in the liraglutide arm lost an average of 3.6 kg (~8 lbs), while patients in the dulaglutide arm lost an average of 2.9 kg (~6 lbs) (p = 0.01) – we wonder if a difference that small will be perceived as clinically meaningful by HCPs. The incidence of hypoglycemia was slightly higher in the liraglutide arm (0.52 events/patient/year) than the dulaglutide arm (0.34 events/patient/year), but the number of events was so small that the difference is likely not very clinically meaningful. On the whole, the results of the study demonstrate that dulaglutide has a comparable clinical profile to liraglutide, and sets the stage for the two to compete on other points like pricing, device design, and patient preferences on does frequency.  

  • The incidence of hypoglycemia in both groups was very low, but appeared very slightly higher in the liraglutide arm. The incidence of hypoglycemia (defined as blood sugar at or below 70 mg/dl with or without symptoms) was 0.34 events/patient/year in the dulaglutide arm and 0.52 events/patient/year in the liraglutide arm. The incidence in both groups was so low that the difference may not be clinically meaningful, whether or not it is statistically significant (which was not mentioned). 
  • Liraglutide came out ahead with regards to weight loss, but only slightly. From a mean baseline of 94 kg (~210 lbs), patients in the dulaglutide arm lost 2.9 kg (~6 lbs), while patients in the liraglutide arm lost 3.6 kg (~8 lbs). The difference was statistically significant (p = 0.01), but given that both groups achieved weight loss of ~3kg, the difference may not be highly clinically significant. Novo Nordisk management has speculated that Victoza would come out ahead on weight during previous quarterly updates, primarily because liraglutide is a smaller molecule that is believed to cross the blood-brain barrier to a greater extent and act at neural appetite regulation centers.
  • The incidence of nausea was similar between arms – we have heard in the past that longer-acting GLP-1 agonists have less of an effect on GI motility and, as a result, generally cause less nausea. We might have therefore expected a slight advantage for dulaglutide, but of course other characteristics of the molecule beyond PK/PD could impact GI tolerability. Approximately 19% of patients in both arms experienced nausea, while ~7-8% experienced vomiting.
  • The results of AWARD-6 make dulaglutide the only GLP-1 agonist to achieve non-inferiority to liraglutide in a phase 3 trial.

Rate Ratios for Nocturnal Confirmed Hypoglycemia with Insulin Degludec vs. Insulin Glargine Using Different Definitions (402-P)

S Heller, C Mathieu, R Kapur, ML Wolden, B Zinman

This poster presents the results of a post-hoc analysis by Novo Nordisk to determine the robustness of their previous finding that treatment with ultra-long acting insulin degludec (trade name Tresiba) led to significantly lower rates of nocturnal hypoglycemia than treatment with insulin glargine (Sanofi’s Lantus) in patients with type 2 diabetes and numerically lower rates in patients with type 1 diabetes. This analysis was likely fueled by FDA criticism of the methods used in the original meta-analysis in degludec’s registration packet. This new study conducts several analyses using different definitions of nocturnal hypoglycemia including i) only confirmed episodes with symptoms; ii) the ADA definition; and iii) a different time frame for the nocturnal period to show that the original findings remain robust no matter which definition of “nocturnal” or “hypoglycemia” is used. The results of these analyses confirmed the findings from the original meta-analysis under nearly all of these conditions. The one exception was when the nocturnal period was extended to 0:01-7:59, in which case hypoglycemia was reduced only in the population of patients with type 2 diabetes treated with basal-bolus therapy (and not in type 1 diabetes or in insulin-naïve type 2 diabetes). Under all other conditions, treatment with insulin degludec led to significantly lower rates in all patients with type 2 diabetes and to numerically but not significantly lower rates in patients with type 1 diabetes. The table below summarizes the rate ratio and 95% confidence intervals for all conditions (rate ratio of 1 indicates an equal rate of hypoglycemia, <1 indicates a lower rate with insulin degludec, >1 indicates a lower rate with insulin glargine). Overall, the data seems to indicate that treatment with insulin degludec may lead to significantly lower rates of nocturnal hypoglycemia in patients with type 2 diabetes compared to treatment with insulin glargine, though the less impressive results with the time period 0:01-7:59 do provide some reason for cautious skepticism.

Table: Rate ratio for nocturnal confirmed hypoglycemia, insulin degludec/insulin glargine

 

Type 2 insulin-naïve

IDeg N=1279

IGlar N=631

Type 2 basal-bolus

IDeg N=742

IGlar N=248

Type 1

IDeg N=637

IGlar N=316

Nocturnal confirmed hypo, original definition (0:01-5:59)

0.64 [0.48, 0.86]

0.75 [0.58, 0.99]

0.83 [0.69, 1.00]

Nocturnal confirmed symptomatic hypo (0:01-5:59)

0.56 [0.39, 0.80]

0.68 [0.51, 0.91]

0.88 [0.72, 1.08]

Nocturnal ADA documented symptomatic hypo (0:01-5:59)

0.73 [0.56, 0.97]

0.72 [0.55, 0.93]

0.91 [0.74, 1.11]

Nocturnal confirmed hypo, original definition (21:59-5:59)

0.60 [0.45, 0.80]

0.73 [0.59, 0.91]

0.88 [0.76, 1.03]

Nocturnal confirmed hypo, original definition (0:01-7:59)

0.93 [0.75, 1.15]

0.77 [0.60, 0.97]

1.00 [0.86, 1.17]

  • This was a post-hoc meta-analysis of six 24- or 52-week randomized, controlled, open-label phase 3a trials involving patients with type 1 and type 2 diabetes and using several definitions of nocturnal hypoglycemia. Definitions included i) confirmed symptomatic episodes; ii) symptomatic episodes with plasma glucose £70 mg/dl (the ADA definition); and iii) the original definition with a different time frame for the nocturnal period (21:59-5:59).
  • Insulin-naïve patients with type 2 diabetes treated with basal-only insulin had significantly lower rates of nocturnal hypoglycemia when treated with insulin degludec (N=1279) than with insulin glargine (N=631), using those three definitions. The rate ratios and 95% confidence intervals with the three definitions listed above were i) 0.56 [0.39, 0.80]; ii) 0.73 [0.56, 0.97]; and iii) 0.60 [0.45, 0.80], compared to 0.64 [0.48, 0.86] in the original meta-analysis. A rate ratio of 1 indicates equal rates of hypoglycemia, a ratio <1 indicates a lower rate with insulin degludec, and a ratio >1 indicates a lower rate with insulin glargine.
  • Patients with type 2 diabetes on basal-bolus therapy had significantly lower rates of nocturnal hypoglycemia when treated with insulin degludec (N=742) than with insulin glargine (N=248), using those three definitions. The rate ratios and confidence intervals with the three definitions were i) 0.68 [0.51, 0.91]; ii) 0.72 [0.55, 0.93]; and iii) 0.73 [0.59, 0.91], compared to 0.75 [0.58, 0.99] in the original meta-analysis.
  • Patients with type 1 diabetes had numerically but not significantly lower rates of nocturnal hypoglycemia when treated with insulin degludec (N=637) than with insulin glargine (N=316), using those three definitions. The rate ratios and confidence intervals with the three definitions were i) 0.88 [0.72, 1.08]; ii) 0.91 [0.74, 1.11]; and iii) 0.88 [0.76, 1.03], compared to 0.83 [0.69, 1.00] in the original meta-analysis.
  • Additional analysis using 0:01-7:59 as the nocturnal period demonstrated an advantage of insulin degludec over insulin glargine only for patients with type 2 diabetes on basal-bolus therapy. The rate ratios and confidence intervals were 0.93 [0.75, 1.15] for insulin-naïve patients with type 2 diabetes, 0.77 [0.60, 0.97] for patients with type 2 diabetes on basal-bolus therapy, and 1.00 [0.86, 1.17] for patients with type 1 diabetes.
  • Additional analysis of the maintenance period only (after the initial 16-week titration period in each trial) showed that all patients with type 2 diabetes had significantly lower rates of hypoglycemia with insulin degludec than with insulin glargine using all definitions and that patients with type 1 diabetes had significantly lower rates with insulin degludec only with the original definition.

Glycemic Control and Hypoglycemia with New Insulin Glargine 300 U/mL in People with T1DM (EDITION IV) (80-LB)

PD Home, RM Bergenstal, MC Riddle, M Ziemen, M Rojeski, M Espinasse, GB Bolli

This study presented the primary results from the EDITION IV phase 3a trial of Sanofi’s new U300 insulin glargine. In the trial, patients with type 1 diabetes on background basal-bolus therapy (n=549) were randomized 1:1:1:1 to once-daily U300 or standard insulin glargine in either the morning or evening while continuing mealtime insulin. As noted in the topline results, U300 was non-inferior to standard insulin glargine in reducing A1c levels (mean change -0.40% with U300 vs. -0.44% with standard insulin glargine; baseline 8.1%) at the end of six months of treatment. Rates of any time confirmed or severe hypoglycemia (<70 mg/dl) were not different between the two groups, although U300 users had reduced nocturnal hypoglycemia in the first eight weeks of treatment (HR 0.69; 95% CI 0.53-0.91). These results are similar to EDITION III, in which benefit to nocturnal hypoglycemia was weighted to the initial weeks of treatment – while different from EDITION I and II, it remains unclear if this will represent a meaningful benefit overall. We are curious if the inclusion of morning administration was able to reduce the risk of nocturnal hypoglycemia overall. Notably, we do note that rates of nocturnal hypoglycemia from week eight to six months of treatment was not a pre-specified main secondary endpoint for this study.

  • This global, multi-center, open-label study, patients with type 1 diabetes (n=549) were randomized 1:1:1:1 to either U300 insulin glargine or standard insulin glargine in either the morning or evening. Average baseline A1c was 8.1%, average BMI was 27.6 kg/m2, and average diabetes duration was 21 years for both U300 (n=274) and insulin glargine (n=275) groups. Patients were followed over a six-month period. As noted across the EDITION studies, the total insulin dose at the end of the treatment period was slightly higher for U300 users (+0.19 units/kg/day from baseline) compared to standard glargine users (0.10 units/kg/day from baseline).
  • U300 demonstrated non-inferior A1c reductions compared to standard insulin glargine (mean change -0.40% with U300 vs. -0.44% with standard insulin glargine; baseline 8.1%). There were no significant differences between the morning and evening groups.
  • Rates of any time confirmed or severe hypoglycemia (<70 mg/dl) were not different between the two groups, although U300 users had reduced nocturnal hypoglycemia in the first eight weeks of treatment (HR 0.69; 95% CI 0.53-0.91). Rates of hypoglycemia were equal between the morning and evening groups. Overall, severe hypoglycemia was seen in 6.6% of the U300 users versus 9.5% of the standard glargine users.
  • Notably, similar to EDITION II, patients taking U300 gained significantly less weight versus standard glargine users (difference -0.56 kg [1.2 lbs]; p=0.037). U300 users gained an average of 0.5 kg (1.1 lbs), while insulin glargine users gained an average of 1.0 kg (2.2 lbs).

ISIS-GCGRRX, an Antisense Glucagon Receptor Antagonist, Caused Rapid, Robust, and Sustained Improvements in Glycemic Control Without Changes in BW, BP, Lipids, or Hypoglycemia in T2DM Patients on Stable Metformin Therapy (109-LB)

Erin Morgan, Anne Smith, Lynnetta Watts, Shuting Xia, Wei Cheng, Richard Geary, and Sanjay Bhanot

Dr. Erin Morgan report the results of a double-blind 13-week trial that randomized type 2 patients on stable metformin therapy to placebo (n=26) or ISIS Pharmaceutical’s ISIS-GCGRRx (n=23 for 100 mg dose, n=10 for 200 mg dose with load, n=16 for 200 mg dose without load). As background, ISIS-GCGRRx is an antisense drug that targets the mRNA of the glucagon receptor (GCGR). Baseline characteristics were similar across the four groups (mean age of 50-57 years, BMI of 31-38 kg/m2, baseline A1c of 8.6-9.1%, and fasting plasma glucose of 168-224 mg/dl). As calculated in the intent-to-treat analysis, ISIS-GCGRRx provided statistically significant A1c reductions (ranging from -1.3% to -2.0%) vs. placebo (0.16%). Similar statistically significant improvements were observed for fructosamine and GLP-1 levels (data provided below). Furthermore, a higher percentage of patients in the ISIS-GCGR groups achieved an A1c of 7% (ranging from 48-75%) vs. those in the placebo group (13%). In addition, ISIS-GCGRRx resulted in higher C-peptide levels during a 2-hour oral glucose tolerance test compared to placebo. The authors highlight that ISIS-GCGRRx is well tolerated and did not trigger the off-target effects seen with small molecules – i.e., the investigators observed no changes in LDL-cholesterol, triglycerides, blood pressure, or body weight.  The authors conclude that because ISIS-GCGRRx directly reduces the production of the glucagon receptor, it may provide greater glycemic control vs. small molecule drugs, with fewer non-specific effects.

  • A subset of participants (the 200 mg “with load” group) first received a loading dose of ISIS-GCGRRx (four injections over 14 days) followed by the standard once-weekly dosing for 11 weeks. Other participants (the 200 mg “without load” group) received the standard dosing for the entire treatment period.
  • ISIS-GCGRRx provided statistically significant A1c reductions, as well as a four-fold increase in GLP-1 levels:

 

Placebo (n=26)

100 mg (n=23)

200 mg (load; n=10)

200 mg (no load; n=16)

Baseline A1c

8.61%

8.62%

9.13%

8.83%

A1c reduction at week 14*

-0.16%

-1.33%

-1.95%

-1.56%

Baseline GLP-1 level

5.35

6.83

8.16

4.76

Change in GLP-1 level at week 14*

-0.31

9.86

16.20

20.01

* measurements were taken one week after the last drug dose.

  • A greater proportion of the ISIS-GCGRRx group achieved an A1c ≤7% compared to the placebo group.

 

Placebo (n=26)

100 mg (n=23)

200 mg (load; n=10)

200 mg (no load; n=16)

Percentage achieving an A1c ≤7% at week 14*

13%

48%

75%

56%

* measurements were taken one week after the last drug dose.

  • ISIS-GCGRRx was well tolerated: the investigators observed no cases of symptomatic hypoglycemia and only infrequent, predominantly mild injection site reactions that resolved rapidly. The authors note that while ISIS-GCGRRx did increased liver enzyme levels, these target-related ALT elevations were “consistent with the pharmacology of glucagon receptor inhibition and similar to those observed with small molecule glucagon inhibitors” (mean ALT elevation was 1.6x ULN for the 100 mg group and 2.7x ULN for the 200 mg group). The liver enzyme elevations declined after drug discontinuation, and ISIS-GCGRRx had no effect on liver function or bilirubin.

LX4211, a Dual Inhibitor of SGLT1/SGLT2, Reduces Postprandial Glucose in Patients with Type 2 Diabetes Mellitus and Moderate to Severe Renal Impairment (132-LB)

Pablo Lapuerta, Arthur Sands, Ike Ogbaa, Paul Strumph, David Powell, Phillip Banks, and Brian Zambrowicz

Dr. Pablo Lapuerta and colleagues present the results of a double-blind randomized, seven-day trial of Lexicon Pharmaceuticals’ LX4211 in 31 type 2 patients with moderate to severe renal impairment (mean baseline eGFR of 43 ml/min/1.73m2; other baseline characteristics detailed below). The participants were randomized to LX4211 400 mg once daily (n=16) or to placebo (n=15) in additional to their insulin therapy or oral anti-diabetic medication, with a treatment period of seven days. A standard breakfast meal was administered on days -1, 1, and 7, and data on glucose and GLP-1 were measured 15 minutes before the breakfast, as well as 1, 2, 2.5, 3, and 4 hours post-breakfast. LX4211 treatment resulted in statistically significant reductions in post-prandial glucose vs. placebo (which were evidence in patients with eGFR <45 ml/min/1.73m2), as well as reductions in fasting plasma glucose (average of -20 mg/dl; p=0.056). Participants on LX4211 also experienced statistically significant increases in post-meal total and active GLP-1 levels vs. those on placebo, which reflected the drug’s inhibition of gastrointestinal SGLT-1. The authors highlight that urinary glucose excretion was only slightly elevated in the LX4211 group (37 g/24 hours) compared a minor decrease in those on placebo (-1.4 g/24 hours; p<0.001). They also note that the PK results support the use of LX4211 400 in renally impaired patients, as there was no increase in LX4211 exposure for patients with eGFR <45 ml/min/1.73m2 relative to those with eGFR ≥45 ml/min/1.73m2. Based on these results, the authors conclude that LX4211 improves glycemic control in type 2 patients with renal impairment and call for longer-term clinical studies in this patient population.

  • At baseline, the participants had a mean age of 66 years, BMI of 34 kg/m2, duration of diabetes of 17 years, and eGFR of 43 ml/min/1.73m2. Seventeen percent of the patients were male, and 21% were Caucasian. The participants reported recent or concomitant use of insulin (61%), SFU (39%), metformin (29%), TZD (10%), and DPP-4 inhibitors (10%). As expected, the rates of common co-morbidities were high: hypertension (90%), hyperlipidemia (90%), neuropathy (42%), and cardiovascular disease (39%).
  • The tables below detail the change in fasting plasma glucose and urinary glucose excretion, stratified by eGFR level:

Table 1: Fasting Plasma Glucose

 

LX4211 vs. Placebo       

p-value

eGFR 45-59 ml/min/1.73m2

-17

0.29

eGFR <45 ml/min/1.73m2

-27

0.08

Mean for all patients

-20

0.056

Table 2: Urinary Glucose Excretion

 

LX4211        

Placebo   

p-value

eGFR ≥45 ml/min/1.73m2

51.6

-1.9

<0.001

eGFR <45 ml/min/1.73m2

19.4

-1.0

0.032

Mean for all patients

37.3

-1.4

<0.001

  • All adverse events were of mild to moderate intensity, and the frequency of adverse events was comparable between the LX4211 and placebo group:

 

LX4211         (n=16)

Placebo    (n=15)

Number of patients (%) with 1 treatment-emergent adverse event (TEAE)

7 (44%)

5 (33%)

Number of patients (%) with 1 drug-related TEAE

1 (6%)

3 (20%)

Safe and Effective Use of the Single-Use Pen for Injection of Once Weekly Dulaglutide in Injection-Naïve Patients with Type 2 Diabetes (122-LB)

G Matfin, A Zimmermann, K Van Brunt, R Threlkeld, D Ignaut

This poster presented results from an open-label, four-week outpatient study investigating the usability of the single-use pen (SUP) designed to administer 0.5 ml of Eli Lilly’s dulaglutide in injection-naïve individuals with type 2 diabetes, as assessed by the injection success rate during the final of four weekly injections of placebo using the SUP. Study participants (n=211) were on average 61 years old, with diabetes duration of 7.7 years, and BMI of 31.7 kg/m2 at baseline (36% of participants only had a high school education or less). All but two of the 211 participants successfully injected placebo using the SUP during their final (fourth) injection, for a success rate of over 99%. The injection success rate for the initial injection was 97.2%, suggesting ease of use without much practice. Participants reported experiencing very little injection pain, rating the pain an average across injections of 1.0 on a 0-10 scale. In addition, participants reported a significant reduction in fear of self-injecting, as assessed by the change in their average modified D-FISQ Fear of Injecting Subscale Score. The vast majority of participants found the pen easy to use, and said they would be willing to use the pen if it were available.

The Novel Glucagon Analogue ZP-GA-1 has Superior Physicochemical Properties while Maintaining the Pharmacokinetic and Pharmacodynamic Profile of Native Glucagon (390-P)

Pia Noerregaard, Mette Svendgaard, Anders Valeur, Lise Giehm, Francesca Macchi, Keld Fosgerau, and Ditte Riber.

Dr. Pia Noerregaard et al. provide in vitro and animal data indicating that Zealand Pharma’s glucagon analogue ZP-GA-1 has greater solubility and stability compared to native glucagon while exhibiting a similar PK/PD profile. Specifically, ZP-GA-1 was found to have a solubility of >25 mg/ml at physiologic pH compared to native glucagon (~0.2 mg/ml). Chemical stability studies showed that after seven days at 40°C, ZP-GA-1 (1 mg/ml tested at a pH of 6.5-7) showed a lower rate of degradation (1.8%) compared to native glucagon (51%; 1 mg/ml tested at a pH of 4).  In addition, a 360-day study of ZP-GA-1 at 5°C showed a degradation of 3.3% (no glucagon comparison was performed). Regarding PK/PD parameters, a crossover study in four male beagles showed that ZP-GA-1 and glucagon had similar PD profiles (based on glucose plasma concentrations) and PK profiles (based on Tmax, Cmax, and half-life) when compared as single injections or as IV infusions. The PK results were also confirmed in rats. Similarly, rat models of hypoglycemia indicated that both ZP-GA-1 and native glucagon injections provided dose-dependent increases in blood glucose levels, which were restored to baseline levels or above. In concluding, the authors note that based on these data, ZP-GA-1 is suited as a liquid formulation for the treatment and/or prevention of severe hypoglycemia either as a rescue kit and/or as part of an artificial pancreas.

Also…

Oral Presentations: Contemporary Issues in the Epidemiology of Diabetes

Hemoglobin Glycation Index Identifies Subpopulations with Harms or Benefits in the ACCORD Trial (166-OR)

James Hempe, PhD (Louisiana State University, New Orleans, LA)

To preface this post-hoc analysis of the ACCORD trial, Dr. James Hempe reminded us that different people have different relationships between A1c and mean blood glucose. When patients have a higher A1c than would be predicted based on mean blood glucose, they are said to have high hemoglobin glycation index (HGI); patients with lower-than-predicted A1c have low HGI. To investigate the importance of HGI in ACCORD, Dr. Hempe compared patients’ A1c to their fasting plasma glucose (a proxy for overall mean glucose). At baseline the high-HGI group included more patients who had baseline retinopathy or nephropathy, who were African-American or Hispanic, and who were using insulin. Patients with high HGI seem to have driven the increased mortality in ACCORD’s intensive treatment arm. By contrast, in the low- and moderate-HGI groups, intensive therapy conferred statistically significant risk reduction in major adverse cardiovascular events, ACCORD’s primary outcome. All three HGI groups had increased risk of hypoglycemia requiring assistance when they received intensive treatment. Similar data on HGI have been seen in other trials, but Dr. Hempe does not think that the metric is ready for clinical use. Indeed, some questioners suggested that this study’s results could have confounded by postprandial glucose, ethnic factors, and/or treatment-induced hypoglycemia.

Biomarkers Associated with Severe Hypoglycemia and Failure to Achieve Good Glycemic Control in T2DM: The ACCORD Study (169-OR)

Lisa Chow, MD (University of Minnesota Medical School, Minneapolis, MN), Haiying Chen (Wake Forest Baptist Medical Center, Winston-Salem, NC), Micahel E. Miller, Santica M. Marcovina, Elizabeth R. Seaquist, (Seattle, WA)

Dr. Chow presented data from a nested, case-control study within ACCORD that identified specific biomarkers that are predictive of severe hypoglycemia and an inability to achieve target A1c levels (<6%) in the intensively treated group. Specifically, IAA, GAD, IA-2A, and Zn-T8 antibodies were correlated with patients’ responsiveness to insulin intensification. This data holds significant clinical potential, as the increased risk for mortality in ACCORD was largely driven by patients who were not responsive to intensive therapy. Most importantly, testing for such antibody biomarkers could predict patient responses to intensive therapy and help individualize treatment.

  • Importantly, Dr. Chow’s data showed that biomarkers can predict the risk of severe hypoglycemia and failure to achieve A1c <6.0%. In all of the trial’s regression models, the odds ratio for risk of severe hypoglycemia and failure to achieve A1c <6.0% were significantly higher when IAA, GAD, IA-2A, and Zn-T8 antibodies were positive. For at least one antibody present, the mean odds ratio for the three models was ~4.0 compared to an odds ratio of 1.0 for no antibody present. Further, when two antibodies were present, the odds ratio jumped to ~12.0 for the three models. Excluding IAA, which Dr. Chow’s group designated as “positive” in the setting of insulin use, GAD antibodies were the islet antibody most frequently positive (17% of cases, 6% of controls). These findings have important clinical implications as one audience member pointed out during Q&A, as the ability of biomarkers to predict patient tolerance to intensification of diabetes treatment can help better individualize therapy.
  • For background, Dr. Chow’s team conducted a nested case-control design within ACCORD and used only participants in the intensive glycemic control arm. There were 326 cases of severe hypoglycemia (defined as hypoglycemia requiring assistance) and failure to achieve A1c <6.0%. These cases were each matched to four controls (total control n=1,075) who achieved A1c <6.0% prior to the ACCORD transition or death without severe hypoglycemia.
    • Markers of insulin deficiency and islet antibodies were measured at baseline. A case was defined as insulin deficient if fasting C-peptide levels were £0.45 ng/ml and insulin sufficient if fasting C-peptide levels were >0.45 ng/ml. Antibodies were either measured as positive or negative:

Antibodies

Positive

Negative

Insulin (IAA) *considered positive if patients on baseline insulin (index)

>0.01

£0.01

Glutamic acid decarboxylase (GAD) [DK unit/ml]

³33

<33

Tyrosine phosphatase-related islet antigen 2 (IA-2A) [DK units/ml]

³5

<5

Zinc transporter (Zn-T8)

>0.02

£0.02

  • Dr. Chow then applied conditional logistic regression using three different models:

Model 1: Insulin deficiency and/or islet antibodies

Model 2: Model 1 + adjusted for age and BMI

Model 3: Model 2 + removal of any case who died and their controls (21 cases removed, 86 controls removed)

  • The results compared the characteristics of cases to controls. Dr. Chow highlighted that mean duration of diabetes for cases (patients with severe hypoglycemia) was 15 years, significantly longer compared to the 9-year duration in controls (patients with no hypoglycemia). We note that this was a point that Dr. Skyler also emphasized in the Saturday debate on glycemic control’s effect on CV risk reduction, hinting that advanced disease progression may have caused the hypoglycemic events and increased risk of mortality. The cases also had notably higher proportion of insulin use at baseline (89%) compared to controls (24%). Dr. Chow also pointed out that the controls were more likely to exhibit zero of the measured antibodies, while the cases were more likely to be positive for at least one antibody. Furthermore, if the cases were positive for antibodies, it was usually only antibody.

 

Cases (n=326)

Controls (n=1,075)

p-value

Age (years)

63.3

62.6

matched

BMI (kg/m2)

31.6

32.5

matched

A1c (%)

8.54

8.08

<0.01

Duration of diabetes (years)

15

9

<0.01

Insulin use at baseline

191 (89%)

259 (24%)

<0.01

% with cardiovascular events at baseline

119 (37%)

322 (30%)

0.05

Insulin deficiency (C-peptide <0.45)

55 (17%)

8 (1%)

<0.01

GAD positive

56 (17%)

62 (6%)

<0.01

IA-2A positive

12 (4%)

4 (0.4%)

<0.01

IAA positive

202 (62%)

276 (26%)

<0.01

Zn-T8 positive

7 (2%)

7 (0.7%)

<0.01

Number of antibodies (yes/no)

 

 

 

0

108 (33%)

757 (70%)

<0.01

1

174 (53%)

292 (27%)

 

2

33 (10%)

22 (2%)

 

3

7 (2%)

3 (0.3%)

 

4

4 (1%)

1 (0.1%)

 

  • As a reminder, the ACCORD study randomized 10,251 patients with type 2 diabetes plus either diagnosed CVD or at least two CV risk factors to either standard glycemic control (A1c 7.0 – 7.9%) or intensive glycemic control (A1c <6.0%). After 3.7 years, the study was terminated early due to increased mortality risk and the intensive glycemic control group (median A1c of 6.4%) transitioned to standard therapy.

Questions and Answers

Q: Getting A1c <6.0% is tough. Dr. Matthew Riddle showed that failure is associated with trying to get A1c<7.0%. Why can’t patients get A1c <6.0% even when you have all the available drugs? A possible solution is glycemic variability. Was that a contributor in your model, and if so what percent of cases you looked at was explained by this?

A: First, we didn’t look at glucose variability in this study, since we were looking at baseline measures from ACCORD. Secondly, the controls were people who had achieved A1c <6% and didn’t have severe hypoglycemia. You’re right that this is a unique situation since ACCORD trial design used really intensive treatment, so we are comparing the very best of those patients to the very worst or comparing pts with antibodies vs. those who don’t.

Q: Is there a reason why the control group (standardized treatment group) studied in ACCORD was not included in your study?

A: The goal of our study was primarily looking for patients who achieved A1c <6.0%, so we didn’t include the standardized group.

Comment: This is a very important paper and if your recommendations were implanted, we could save a lot of unnecessary complications in type 2 patients. I would like you to even expand your recommendations to include testing for all four antibodies. That kind of test is very inexpensive – $50 for all four antibodies – and such information could alter treatment dramatically. Also, we should be measuring this also in all patients who were never on insulin, so you can capture more patients who are at high risk for hypoglycemia.

A: We could consider measuring C-peptide for each antibody, and you bring up great points. In terms of measuring GAD, we could also measure insulin and maybe C-peptide for that. However we were trying to balance what was ideal vs. what was realistic.

Q: You showed a subgroup of patients with low C-peptide and antibodies; these aren’t type 2 patients. Why were they included in this study? If you expect other influences on those four main antibodies, the ACCORD study showed that without type 1 antibodies.

A: The patients enrolled in ACCORD were all assumed to have type 2 diabetes, so they were phenotypically and clinically assessed as type 2 diabetes patients. Yet when going back and measuring GAB levels, we found that those levels were positive. In terms of C-peptide they may not be truly type 1, but may have some progressive beta cell failure. Explaining the GAP antibodies, they could have been latent type 1 or LADA. There are strict criteria for LADA diagnosis, and these original ACCORD patients had lived with it for years. I would say it might be considered longstanding LADA or type 2 with some type of beta cell deficiency.

Posters

Costs of Diabetes in the U.S.: 1996-2030 (142-LB)

H Chen, MV Venkat, L Rotenstein, JP Dong, N Ran, M Yarchoan, R Kahn, KL Close

This study (our very own!) looked at costs directly attributable to diabetes in the US from 1996 to 2010, adapting the methodology used in the ADA’s five-year cost-of-illness studies, and projected costs up through 2030. Total costs rose from $64 billion in 1996 to $167 billion in 2010 – those numbers may sound low, but only because the analysis did not count the sizable indirect costs of diabetes (lost productivity, premature death, etc.). Astoundingly, annual diabetes costs were projected to rise to $494 billion by 2030 based on the historical trajectory. The primary driver for costs was increasing prevalence of diabetes. If annual diabetes incidence were reduced by 5% from the years 2010 through 2030, the US could save a cumulative total of $427 billion; a 10% reduction would lead to cumulative savings of $798 billion. A breakdown of costs encouragingly found that inpatient hospitalization costs went from a 58% share of total costs in 1996 to 46% in 2010, and were forecast to account for 36% of total diabetes costs in 2030. On the other hand, non-insulin medication costs increased the most, from 7% of total costs in 1996 to a forecasted 26% in 2030 – the authors suggest that better glycemic control could have contributed to the reduction in hospitalizations, although a cost-of-illness study cannot be used to support causation. Overall, these numbers present a compelling argument for primary prevention, as the magnitude of the costs attributable to diabetes is proportional to the size of the affected population.

  • Investigators of this study found that the total costs directly attributable to diabetes in the US rose from $64 billion in 1996 to $167 billion in 2010, and are predicted to rise further to $494 billion in 2030. The nearly half-trillion 2030 figure would be a whopping 196% increase from 2010, and is higher than estimates in past scientific literature.
  • Relatively modest reductions in annual diabetes incidence could save the US hundreds of billions of dollars through 2030. A 1% reduction in annual incidence between 2010 and 2030 was projected to save a total of $87 billion, a 5% reduction was projected to save $427 billion, and a 10% reduction was projected to save $798 billion. The majority of savings would occur towards the end of the 2010-2030 time period as prevalence curves diverge from the unaffected estimate
  • In an analysis of the components of total diabetes costs, the investigators found that inpatient hospitalization costs decreased the most in terms of percentage of total diabetes costs, while non-insulin prescription medications and diabetes supplies gained the greatest share. Care categories studied included hospital inpatient, hospital outpatient, emergency department, physician’s office, nursing home, home health, prescription medications excluding insulin, insulin, and diabetes supplies. Inpatient hospitalization represented 58% of total costs in 1996, 46% in 2010, and a projected 36% in 2030. Non-insulin medications represented only 7% of total costs in 1996, 16% in 2010, and a projected 26% in 2030. The costs of diabetes supplies also increased proportionally, from a mere 3% in 1996 to 10% in 2010, and a projected 12% in 2030. The authors hypothesized that usage of medications and supplies might be contributing to reduced hospitalizations, but this is an area that needs to be explored further.
  • In a segmentation of costs by complication/primary diagnosis, the investigators found that costs associated with renal and endocrine complications are rising rapidly. Treating nephropathy remains an area of unmet need in diabetes care, and additionally the type 2 diabetes patient population with existing renal impairment has fewer treatment options for hyperglycemia.
  • Future studies may look at demographically segmented data, quality-of-life costs, and differences between the various types of diabetes.

Investigation of the Presence and Impact of Social Stigma on Patients with Diabetes in the USA (59-LB)

A Folias, A Brown, J Carvalho, V Wu, K Close, R Wood

Understanding the social perceptions of diabetes and their impact on patients’ health is important for determining the best way to address these perceptions. Ms. Folias’s team surveyed 5410 diabetes patients, including both type 1 (29%) and type 2 (71%) diabetes patients [note: the patients studied are part of a larger patient panel (n=12,000) managed by dQ&A, a diabetes market research company that is a sister company of Close Concerns]. The clear majority of type 1 diabetes patients (76%) affirmed that there was a stigma attached to diabetes. Interestingly, a smaller percentage of type 2 diabetes patients (52%) voted that diabetes and its care came with a stigma – the percentage was slightly higher (55%) among insulin-treated type 2 diabetes patients. Out of all those who believed that diabetes was associated with stigma, 72% stated that the stigma was based in a perception that diabetes is a personal failure. Over 50% of participants felt that this stigma affected them socially, and over 25% reported that social stigma impacted their ability to manage their treatment. Notably, the perception of stigma did not vary significantly by annual household income, region, education, or duration of diabetes. Insulin use (vs orals only), worse self-reported glycemic control, and higher BMI were predictors for a higher perception of stigma. Of course, this survey measured perception of stigma rather than stigma itself, but the perception of stigma is an important barrier to adherence.  

  • The 5,422 survey participants represented a wide variety of type 1 and type 2 diabetes patients, differing by age, glycemic control, treatment type, and geographic region. Type 1 diabetes participants made up 29% of the survey pool and varied by age (13% children and 87% adults) as well as A1c (49% ≤ 7% and 51% > 7%). Type 2 diabetes participants, 71% of the respondents, included insulin users (45%) as well as non-insulin users (55%), and also varied by A1c (61% ≤ 7% and 39% > 7%). The whole panel included participants were on GLP-1 analogs, pumps, CGM, MDI without a pump, and/or tested their blood glucose three or more times a day. Participants were distributed through the West, Midwest, South, and Northeast regions.
  • A majority of respondents with type 1 diabetes (76%), and a smaller majority of those with type 2 diabetes (52%), believed that diabetes comes with social stigma. Within type 2 diabetes patients, perception of stigma was greater among those using insulin (62%) vs those on orals alone (52%).
  • Out of the respondents who perceived a stigma, a significant proportion (27% - 42%) also stated that it impacted their diabetes management. Of course stigma has massive intangible impact on quality-of-life, but the way it impacts management is how it can most directly affect outcomes.
  • The majority of patients believed that diabetes was perceived as a failure of personal responsibility (72%), a burden on the healthcare system (65%), and a character flaw (52%). This negative view also may prevent the public from focusing on preventing or treating diabetes.
  • Patients with more intense disease states and therapies, worse measured and self-reported glycemic control, or higher BMI were more likely to feel guilt, shame, or isolation due to diabetes. Just as notably, the perception of diabetes stigma did not appear to vary by annual household income, region, education, or duration of diabetes.
  • Broken down by categories: Children with type 1 diabetes reported the greatest degree of feelings of guilt, shame, embarrassment, isolation, or blame due to their diabetes (39%), followed by adults with type 1 diabetes (38%). Next came type 2 patients on MDI or a pump (35%), while 21% of type 2 diabetes patients on oral therapies alone reported negative emotional impact of stigma.

 

-- by Melissa An, Adam Brown, Eric Chang, Hannah Deming, Jessica Dong, Varun Iyengar, Hannah Martin, Nina Ran, Emily Regier, Joseph Shivers, Sanjay Trehan, Jenny Tan, Manu Venkat, Vincent Wu, and Kelly Close