International Diabetes Federation: World Diabetes Congress 2013

December 2-6, 2013; Melbourne, Australia Day #2 Highlights - Draft

Executive Highlights

Hello from Mel-bin (we are working on our Aussie accent) where Day #2 of IDF offered a slew of new data on the drug front, headlined by results on Sanofi’s U300 insulin glargine and Novo Nordisk’s renowned GLP-1/basal insulin combination product, IDegLira. Full results of the EDITION II trial on Sanofi’s U300 insulin glargine formulation were largely consistent with those of EDITION I: U300 offered nearly identical A1c reductions to the “normal” Lantus U100 (~0.6% reduction from a baseline of 8.2%) and offered an additional, primary distinguishing factor: between the two formulations U300 led to a statistically significant 10% reduction in all-daytime hypoglycemia (during the entire six months) and a statistically significant 23% reduction in confirmed or severe nocturnal hypoglycemia (although only during months three through six, which was a bit curious). Patients using the more concentrated formulation used about 10% more units of insulin per day (0.92 U/kg/day versus 0.84 U/kg/day), and saw slightly (and statistically significantly) less weight gain (no change compared to ~1 kg weight gain with U100 glargine). These results offer two fairly compelling benefits – hypoglycemia and weight difference – over Lantus. It remains to be seen how consistent the hypoglycemia and weight gain results are in different patient populations, which we will find out in 2014 when EDITION III, IV, and JPI report full results. We were impressed with these results and think patients and HCPs will really like the ability to take a lower volume of insulin.

Full results from Novo Nordisk’s DUAL II trial (n=413) comparing insulin degludec (IDeg) with a fixed-ratio combination of IDeg and liraglutide (IDegLira) corroborated DUAL I’s impressive full results first shown at ADA and then at EASD (which compared IDegLira, IDeg, and liraglutide). The study had a unique methodology in which both the IDeg and the IDegLira arms received a mean of 45U of degludec whether on its own or in combination with liraglutide, respectively. This design helped elucidate the impact of liraglutide alone in the IDegLira combination. From a baseline A1c of 8.7%, patients in the IDegLira arm experienced an average A1c reduction of 1.9% (the same A1c drop seen with IDegLira in DUAL I but from a higher baseline than DUAL I’s 8.3%), which was significantly greater than the 0.89% A1c reduction seen in the IDeg arm. The IDegLira arm had a comparable rate of hypoglycemia to IDeg, weight loss of 5.9 lbs. instead of weight neutrality with IDeg, and slightly elevated rates of nausea and vomiting compared to IDeg. Wow! These are real changes for patients and HCPs – the combination of such better efficacy and weight loss. We see why there is a lot of chatter about this being a first injectable for patients. 

On the technology front, Dr. Satish Garg (University of Colorado, Denver, CO) presented encouraging results from a single-center pilot study comparing use of Sanofi’s iBGStar on the iPhone 4 (n=50) to the Accu-Chek Nano (n=50) in patients with type 1 diabetes. Both groups achieved significant A1c reductions at three months, though there was a trend in favor of the iBGStar – a decline of 0.4% in the iBGStar group (baseline 8%; p=0.008) vs. -0.2% in the control group (baseline: 7.7%; p=0.04). Given the potential of mobile technology to change healthcare delivery, we look forward to full six-month data, blinded CGM results (Dexcom G4 Platinum), and cost analyses expected at ADA or EASD 2014 – we are eager to see the time in range data.

We continue to hear more about DPP-4 inhibitors and heart failure risk. Several symposia throughout the day reflected on the results from DPP-4 inhibitor CVOTs SAVOR-TIMI (of BMS/AZ’s Onglyza [saxagliptin]) and EXAMINE (of Takeda’s Nesina [alogliptin]), particularly those surrounding congestive heart failure (CHF). Similar to the comments made by Drs. Steven Nissen (Cleveland Clinic, Cleveland, OH) and Thomas Engstrøm (University of Copenhagen, Denmark) during IDF Day #1, Dr. Richard Gilbert (University of Toronto, Canada) expressed his tentative belief that the DPP-4 inhibitor class might increase CHF risk. Dr. Gilbert also emphasized that insulins, sulfonylureas, and thiazolidinones might also elevate one’s risk for CHF (all three have long had an association), leaving DPP-4 inhibitors the “best of an imperfect bunch”. He did not address GLP-1 analogs or SGLT-2 inhibitors, which is not too surprising given a current lack of long-term CV data for these two classes – we expect this to be even more widely awaited data. Incretin-1 expert Dr. Daniel Drucker (University of Toronto, Canada) noted that the failure of preclinical rodent studies to identify a CHF signal might be evidence that these models are poor predictive surrogates for older, high-risk patients with pre-existing CVD. We do note that in such patients, we wouldn’t be as likely to think of DPP-4 inhibitors as the “perfect” drug compared to newly diagnosed patients and patients without pre-existing CVD risk; we continue to wonder about DPP-4 inhibitor use in pre-diabetes though imagine there may be increasingly less enthusiasm for these studies. As it is, of course, there is still no pre-diabetes guidance from a regulatory perspective in the US – we’d love to see movement toward this changing. 

Table of Contents 

Detailed Discussion and Commentary

Oral Presentations: Hypoglycemia

An Investigational New Insulin U300: Glucose Control And Hypoglycemia In People With Type 2 Diabetes On Basal Insulin And OADs (Edition II)

Hannele Yki-Järvinen, MD, PhD (University of Helsinki, Helsinki, Finland)

Dr. Hannele Yki-Järvinen presented the full results of the EDITION II study on Sanofi’s U300 insulin glargine formulation. As background, topline study data was briefly discussed at this year’s ADA alongside the more detailed presentation of EDITION I (see page 12 of our ADA 2013 Insulin Report). EDITION II randomized 811 type 2 diabetes patients who were on baseline treatment with basal insulin and at least one non-SFU oral antidiabetic therapy to treatment with either the U100 (Lantus) or U300 formulation of insulin glargine. As was seen in EDITION I, insulin glargine U300 was non-inferior to the U100 formulation in terms of A1c-lowering (mean reduction of approximately 0.6% from a baseline of 8.2%); eight-point blood glucose measurements were also similar between groups. The main differentiating factor between the formulations was nocturnal hypoglycemia: between study months three and six, insulin glargine U300 led to a statistically significant 23% decrease in confirmed or severe nocturnal hypoglycemia. There was a 27% improvement in all nocturnal hypoglycemia, and a 10% improvement in all daytime hypoglycemia. As was seen in EDITION I, patients on U300 glargine required a higher daily dose of insulin (0.92 U/kg/day versus 0.84 U/kg/day with U100). Interestingly, U300 was modestly (~1 kg) and statistically significantly superior with regards to weight gain, an effect that was not seen in EDITION I. Sanofi continues to forecast FDA submission for insulin glargine U300 in 1H14.

  • As background, topline data from the EDITION II study on Sanofi’s U300 insulin glargine formulation was announced at this year’s ADA. Sanofi announced at that point that the major findings from EDITION II with regards to glycemic effects and hypoglycemia were consistent with those from EDITION I, which was covered in more detail at ADA. EDITION I found that the U300 glargine formulation was non-inferior to the U100 formulation (“normal” Lantus) with regards to A1c lowering (0.8%), and that participants on the U300 formulation experienced lower rates of severe or nocturnal confirmed hypoglycemia (36% with U300 versus 46% with U100; p=0.004). Interestingly, patients in the U300 glargine arm required a slightly higher daily insulin dose, on average. We speculate that this may be due to changes in absorption at the higher concentration. Slight weight gain of around 1 kg was seen in both groups. For our initial coverage of the EDITION I data presentation, see page 12 of our ADA 2013 Insulin Report.
  • EDITION II compares the safety and efficacy of insulin glargine U300 in type 2 diabetes patients on basal insulin therapy and oral diabetes medications (for comparison, EDITION I was in type 2 diabetes patients on basal-bolus therapy ± metformin). The open-label, multinational study randomized 811 patients with A1c between 7.0% and 10.0% who were on treatment with basal insulin (daily dose of at least 42 U/day – the same requirement as EDITION I) and oral antidiabetic agents (but not on sulfonylureas or mealtime insulin) to treatment with glargine U300 or U100 (Lantus) for six months (while continuing on oral agents). Notably, the trial enrolled patients with a relatively high mean baseline BMI (35 kg/m2) and long diabetes duration (~13 years) – similarly to EDITION I. The primary endpoint was change in A1c after six months, while the incidence of confirmed or severe nocturnal hypoglycemia was the main secondary endpoint. Both insulins were titrated to attain a target of 80-100 mg/dl. At baseline, mean A1c was 8.2%, mean duration of basal insulin was 3.8 years, over 95% of patients were on metformin, and the majority were on insulin glargine U100 as a their basal insulin.
  • Insulin glargine U300 was non-inferior to Lantus in terms of A1c lowering; both reduced A1c by slightly under 0.6%. Reductions in fasting plasma glucose were also comparable (~20 mg/dl in both groups), as were eight-point glucose measurements. Taken together with results from EDITION I, it seems fairly safe to say that the U300 insulin glargine formulation is comparable to the U100 formulation in terms of A1c-lowering efficacy.
  • As was seen in EDITION I, hypoglycemia was the major differentiating factor between the two formulations. Between months three and six, insulin glargine U300 led to a statistically significant 23% decrease in confirmed or severe nocturnal hypoglycemia. Over the entire six-month treatment period, patients on U300 glargine experienced a 27% reduction in risk for any nocturnal hypoglycemia and a 10% reduction in daytime hypoglycemia (both differences were statistically significant). When plotted as a function of A1c at the study endpoint, the incidence of confirmed or severe nocturnal hypoglycemia was most greatly reduced at low A1c values, perhaps indicating that insulin glargine U300 can help patients and providers more safely pursue lower A1c goals. We imagine that the ability to inject a smaller volume of insulin with U300 glargine may reduce the wound response or other adverse reactions at the injection site, which would reduce variability in insulin bioavailability and have a positive impact on hypoglycemia. Earlier studies on PK/PD have also shown that the U300 formulation has a flatter action profile than Lantus. We assume patients also would just like injecting lower volumes from an ease of use perspective.
  • There were a few other noticeable differences between the two insulin formulations. As was seen in EDITION I, the U300 group required a higher daily dose of insulin (0.92 U/kg/day versus 0.84 U/kg/day in the U100 group). One of the few differences between the results of EDITION I & II was with regard to body weight. While EDITION I found no significant difference between the weight gain (~1kg) seen with the two formulations, in EDITION II the U300 arm had no change in body weight – a statistically significant improvement over the U100 arm (which gained ~1 kg). Although the difference in mean weight gain was modest, we are very interested to see if future studies confirm this finding, as the prospect of a weight-neutral (or even a less weight-positive) insulin would be a major win for patients. We speculate that the improvement in hypoglycemia may have contributed quite strongly to the difference in weight gain (patients with hypoglycemia must consume carbs to compensate, likely leading to overall increased energy intake).
  • There were no standout differences between the groups in terms of adverse events, including injection site reactions and hypersensitivity. There was a slightly higher incidence of treatment-emergent adverse events in the U300 group (59% versus 51%), but Dr. Yki-Järvinen did not discuss this point further.

Questions and Answers

Q: The insulin dose requirement in the U300 group was 10% higher than in the U100 group in both studies. Why might this be?

A: If you measure the drug concentrations in the blood, the levels are similar even if the dose of U300 is higher. Something happens between the injection site and blood. I have no information on whether it might be a difference in degradation or something else. You’re right that the dose you need of the U300 is higher but the actual dose in the blood affecting glucose levels is similar.

Q: How, when there was more daily insulin in the U300 group, was there less weight gain as well?

A: Dose analyses are in the process of being conducted. The difference in weight gain might exist in EDITION III and IV as well, at least eyeballing the data. If you have less hypoglycemia, you would predict that people do not need to eat to compensate for it to the same extent, and have less weight gain. Whether that is the cause remains to be established. I think it’s interesting that in the face of similar glycemia, there was a small difference in weight gain, but sometimes a small difference is greatly emphasized with insulin. I think the most obvious explanation is difference in hypoglycemia.

Effects Of Liraglutide Adjunct To Insulin On Counterregulatory Hormone Responses To Hypoglycaemia In Type 1 Diabetes: A Randomized Trial

Thomas Pieber, MD (Medical University of Graz, Graz, Austria)

Dr. Thomas Pieber presented data from a study on the effects of Novo Nordisk’s GLP-1 agonist Victoza (liraglutide) on type 1 diabetes patients’ recovery from hypoglycemia, and important safety consideration given GLP-1 agonists’ suppression of glucagon. As background, this data was first presented at this year’s EASD (see pages 3 and 17 of our EASD 2013 Incretins Report). We continue to be very excited by the increasing interest in the use of incretin therapies in type 1 diabetes, given the relative lack of pharmacotherapies in this patient population. The double blind, crossover trial randomized 45 type 1 diabetes patients to liraglutide 0.6, 1.2, or 1.8 mg for four weeks of treatment followed by a hypoglycemic clamp (a similar four-week crossover placebo period occurred before or after). There were no statistically significant differences in glucagon secretion between the liraglutide and placebo arms during the hypoglycemic clamp; baseline glucagon secretion was lower in the liraglutide arms, but the magnitude of the increase in secretion (the counterregulatory response) was similar in all treatment arms. There were no significant differences in other counterregulatory hormones, including noradrenaline and cortisol. Patients on liraglutide needed significantly less infused insulin to maintain a given plasma glucose level during the clamp study. Overall, these results support the safety of liraglutide treatment in type 1 diabetes, at least with regards to hypoglycemia recovery.    

Questions and Answers

Q: When you transition patients onto liraglutide you would imagine that there would be changes in body weight and other factors. Was there more hypoglycemia in the liraglutide group?

A: We have a poster presentation that includes more details from the trial. There was weight loss in the liraglutide groups, which was dose-dependent. We had to reduce patients’ insulin dose in the liraglutide arms, as expected. With regards to hypoglycemia, the trial was designed to avoid hypoglycemia during the run-in period, in order to preserve the integrity of the clamp study, so no real conclusions can be drawn about the treatment-related hypoglycemia incidence during run-in.

Oral Presentations: Late-Breaking Abstracts – Basic and Clinical Science

Liraglutide Contributes Significantly To Glycaemic Control Achieved In IDegLira: A Double-Blind Phase 3 Trial In Type 2 Diabetes

Tina Vilsbøll, MD (University of Copenhagen, Copenhagen, Denmark)

Dr. Tina Vilsbøll presented full results from DUAL-II, the second of two phase 3a trials for Novo Nordisk’s GLP-1/basal insulin fixed-ratio combination product, IDegLira. DUAL-II compared insulin degludec (IDeg) to the combination of insulin degludec and liraglutide (IDegLira). Our coverage of the study’s topline results announced in December 2012 can be read here. In this 26-week study, 413 patients with type 2 diabetes and inadequate control on basal insulin and one or two oral agents were given metformin and randomized to IDegLira or IDeg in a double-blind fashion. Importantly, the maximum allowed doses were 50 dose steps for IDegLira (50U IDeg + 1.8 mg liraglutide) or 50U for IDeg, and the final mean dose of IDeg either on its own or as part of IDegLira was equivalent in the two arms at 45U. As a result, Dr. Vilsbøll emphasized, the results elucidate the additional benefit of adding liraglutide in a fixed-ratio with IDeg. From a baseline A1c of 8.7%, patients in the IDegLira arm experienced an average A1c reduction of 1.9%, which was significantly greater than the 0.89% A1c reduction seen in the IDeg arm (p<0.0001) – this suggests that liraglutide contributed 1% of the A1c reduction achieved with IDegLira. The IDegLira arm achieved this result with a comparable incidence of hypoglycemia when compared to IDeg (24% vs. 25%). Patients in the IDegLira arm lost an average of 2.7 kg (5.9 lbs), whereas, the IDeg arm experienced essentially no weight change (~0.2 kg lost [0.4 lbs.]) from baseline to week 26. Dr. Vilsbøll highlighted that because of the slow titration performed in the IDegLira arm (one dose step was defined as 1U IDeg and 0.36 mg liraglutide), the IDegLira arm experienced only slightly more nausea (6.5% vs. 3.5%) and vomiting (3.5% vs. 0%) than the IDeg arm.

  • The mean age of participants was 57 years and the mean A1c was 8.7%. The mean BMI was 33.7 kg/m2 and the mean diabetes duration was 11 years.
  • The mean basal insulin dose at screening was 29U (standard deviation of 8U) in both treatment groups. The breakdown of participants’ diabetes treatment at screening is below.


IDegLira (%)

IDeg (%)

Basal insulin type



     Insulin detemir



     Insulin glargine



     Other basal insulin









     Metformin + SU/glinides



  • Patients in the IDegLira arm experienced an average A1c reduction of 1.9%, which was significantly greater than the 0.89% A1c reduction seen in the IDeg arm (both from a baseline of 8.7%; p<0.0001). This suggests that liraglutide contributed a 1%  IDegLira improved glycemic control by lowering both fasting plasma glucose and postprandial glucose. The IDegLira arm’s fasting plasma glucose was significantly lower than that of the IDeg arm (63 mg/dl vs. 47 mg/dl; p=0.002). Furthermore, nine-point glucose profiles demonstrated that people on IDegLira had a lower mean prandial increment across meals (39.6 mg/dl vs. 43.2 mg/dl; p=0.026) and lower mean plasma glucose (135 mg/dl vs. 157 mg/dl; p<0.0001).
  • The incidence of hypoglycemia was comparable between the IDegLira and the IDeg treatment groups at 24% and 25%, respectively. In this vein, the rates of confirmed hypoglycemic events per person were 1.5 for IDegLira and 2.6 for insulin degludec (p=0.13).
  • Dr. Vilsbøll characterized IDegLira as being well tolerated, as the discontinuation due to adverse event rate was only 1.0%. No participants in the IDegLira arm who had previously been on basal insulin discontinued IDegLira due to nausea.
  • Taken together with the results from DUAL-I, which were presented at ADA 2013, these are some of the treatment profiles we have ever seen a single product offer. Several speakers during IDF Day #1 (and at previous conferences) have expressed the sentiment that clinicians might view IDegLira essentially as an improved version of insulin and that it may become the preferred approach for initiating insulin – indeed it is a product that offers all of the benefits of insulin (robust A1c reduction) with very few downsides (no more hypoglycemia, no more weight gain and in fact, even some weight loss).

Questions and Answers

Q: What was the target fasting glucose?

A: The target was around 5 mmol/l [90 mg/dl]. If a patient had a fasting between 4 mmol/l [72 mg/dl] and 5 mmol/l [90 mg/dl] the medication dose was continued. It was very aggressive actually.

Comment: You had some of the most aggressive titrations yet it still leveled out and the fasting still did not quite make it to target.

A: In this study the primary endpoint was to show that adding liraglutide to this basal insulin makes sense. It was not a matter of pushing all patients to target, because you would then need more insulin. What was unique in this trial was that it was double blinded. Most insulin studies are not. I think the first patients were just included in DUAL 5, which is to compare aggressive titration of IDegLira with insulin glargine when both are titrated to target.

Q: Was this a blinded study?

A: It was blinded. Impressive isn’t it?

Q: I am interested in seeing the group that went all of the way to 50 units. How many people were up-titrated to that point and what was their result?

A: In the IDeg group 67% went to the upper dose and 65% did so in the combination group.

Q: What was that group’s final A1c?

A: I don't know, but you can see that it was higher than the target. The aim of the study was to look at how liraglutide contributes to this combination. The purpose was not to show that IDeg works in people with type 2 diabetes. That was shown in IDeg’s phase 3 program [presumably he means in DUAL-I].

Q: What happens if you combine liraglutide with glargine?

A: Whoa, you will never know that because the two companies will probably not do that combination. There have been studies looking at insulin glargine and detemir and studies are ongoing comparing glargine and degludec. I don't know if that will ever be done.

Q: What dose of metformin was used?

A: I actually do not know exactly the dose, but it was maintained. The patients had to be on a stable dose of metformin, and it was the maximally tolerated dose. But I do not remember exactly the average.

Empagliflozin Improves Glycemic Control In Patients With Type 1 Diabetes: A Single-Arm Clinical Trial

Bruce Perkins, MD (Toronto General Research Institute, Ontario, Canada)

This single-arm, open-label, proof of concept, eight-week study explored use of BI/Lilly’s SGLT-2 inhibitor empagliflozin in 42 patients with type 1 diabetes (mean age: 24 years; mean BMI: 25 kg/m2). We first covered results of this study at ADA 2013 (see page 139) and later in our EASD 2013 (see page 51). Results of the treatment period were compared to a two-week placebo run-in period. Mean A1c levels decreased by 0.4% from an 8% baseline. Frequency of symptomatic hypoglycemia was reduced by 33% (0.12 to 0.04 events/day). Dr. Bruce Perkins offered four reasons for the low risk of hypoglycemia with empagliflozin: 1) empagliflozin’s insulin-dependent mechanism of action; 2) a physiological GFR decline during hypoglycemia; 3) lower glucose delivery to the proximal tubule when the plasma glucose concentration is low; and 4) increased hepatic gluconeogenesis. Two cases of diabetes ketoacidosis occurred that forced the two participants to drop out of the study. Dr. Perkins did not attribute these occurrences to empagliflozin, instead attributing them to the effects of aggressive insulin reductions (by 50% and 70%), as well as a case of gastroenteritis and a pump failure. Importantly, though, he noted that these cases raise the possibility that SGLT-2 inhibition might modify the clinical presentation of DKA, since the two participants had lower glucose concentrations than typically seen with DKA (306 mg/dl and 212 mg/dl). Dr. Perkins therefore concluded during Q&A that it is essential future trials of SGLT-2 inhibitors for type 1 diabetes include the measurement of plasma ketones.     

  • In Q&A, Dr. Perkins hypothesized on the reason the reported carbohydrate intake in participants increased dramatically (from 177 grams per day at baseline to 229 grams per day at week eight). He suggested that it could be participants became more accurate in their carb counts as the trial progressed, or that they consumed additional carbohydrates to compensate for the excretion of more glucose.

Questions and Answers

Q: How consistent was it that the insulin dose went down? Were they given SMBG monitoring routines?

A: The dose adjustments were based on capillary blood glucose measures. There was a lot of attention given especially during the first days of initiation. People’s fasting glucose levels were extremely tight and really required reductions in their basals.

Comment: So you just follow those patterns and trends closely and adjusted.

Q: Were ketones tested throughout the trial?

A: We did not systematically measure ketones, but I think that is an essential part of any further study in type 1 diabetes.

Comment: People talk about being concerned about DKA with SGLT-2 use in type 1 diabetes.

A: These cases were symptomatic but we need to understand how many ketones are present asymptomatically and if it differs with the drug’s use.

Q: Can you please explain the increase in gluconeogenesis?

A: I am not able to explain it extremely well. There may be a compensation for the increased glucose excretion. What is clear is that on empagliflozin there are lower insulin dose requirements. So it may be that lower insulin doses are allowing the hepatic gluconeogenesis.

Comment: I was struck by the increase in carb intake.

A: To my knowledge this has not been reported before. It may be that over the course of the trial people reported their carb counts more accurately – that is a possibility. You can speculate that there is some mechanism that is involved just as you could say that when diabetes is diagnosed there is caloric loss. We did not expect this finding, and the study was not designed to look at why it happened.

Q: You are not going to tell us about the renal findings?

A: No, but I can give you a brief summary. The use of an SGLT-2 inhibitor appears to have a favorable renal profile that looks like RAAS inhibition.

Combining The GPR40 Agonist Fasiglifam With Sitagliptin Improves Glycemic Control In Patients With Type 2 Diabetes Mellitus With Or Without Metformin

Xuejun Peng, MD, PhD (Takeda, Osaka, Japan)

Dr. Xuejun Peng presented the results of a phase 2 study investigating the glycemic effects of Takeda’s phase 3 GPR40 agonist fasiglifam used in combination with Merck’s DPP-4 inhibitor sitagliptin (Takeda’s DPP-4 inhibitor Nesina was not approved at the time of the study’s planning). Dr. Peng emphasized that GPR40 agonists stimulate insulin release in a glucose-dependent manner, distinguishing them from cruder secretagogues such as sulfonylureas and making them an excellent potential co-therapy for DPP-4 inhibitors (which also increase insulin secretion in a glucose-dependent manner). The 12-week, randomized, placebo-controlled, double blind, multicenter study randomized 360 treatment-naïve patients to fasiglifam 25 or 50 mg, either with or without a 100 mg sitagliptin dose. There was also a sitagliptin 100 mg monotherapy group as well as a placebo group, making for six groups in total. At week 12, the placebo-adjusted A1c reduction seen with fasiglifam 50 mg + sitagliptin (an impressive 1.2% from a baseline of ~8.5%) was greater than that seen with fasiglifam 50 mg monotherapy (~0.8%) or sitagliptin monotherapy (~0.6%). For nearly every parameter studied — including fasting plasma glucose, the percentage of subjects achieving an A1c goal below 7.0%, and C-peptide levels — the combination performed significantly better than either monotherapy. No dose-dependent effect on body weight was observed; the combination appeared to be well tolerated; and the incidence of hypoglycemia was low and similar across groups (supporting fasiglifam’s glucose-dependent mode of action). Happily for patients and HCPs (both of whom will be major beneficiaries for the drive toward FDCs in our view), Takeda appears to be positioning its GPR40 candidate as a potential partner to DPP-4 inhibitors, an excellent idea in our minds given the increasing interest in fixed-dose combinations for diabetes.

Oral Presentation: Obesity and Bariatric Surgery

Bariatric Surgery Reduces The Incidence of Albuminuria In The Swedish Obese Subjects (SOS) Study

Lena Carlsson Ekander, MD, PhD (University of Gothenburg, Gothenburg, Sweden)

Dr. Lena Carlsson Ekander presented an analysis of the Swedish Obesity Subjects (SOS) Study (largely considered the most comprehensive, oldest source of data on bariatric surgery) demonstrating that bariatric surgery was associated with a significantly reduced incidence of albuminuria when compared to conventional care over the course of 15 years. The investigators for abstract (the last author of which was the SOS Study’s original PI, Dr. Lars Sjöström [University of Gothenburg, Gothenburg, Sweden]) only looked at people in the SOS study who did not have albuminuria at baseline (n=1,610 in the control and 1,498 in the surgery group). They tested for albuminuria by performing a 24-hour urine collection at baseline, and after two, 10, 15, and 20 years. After 15 years of follow-up, people who underwent bariatric surgery had a 54% risk reduction (63% adjusted risk reduction) of progressing to albuminuria. This meant one case of albuminuria would be prevented over the course of ten years if nine SOS participants underwent bariatric surgery. Dr. Ekander found that BMI did not predict the incidence of albuminuria in the control group or the treatment benefit in the surgery group. Similarly, neither the presence of diabetes, hypertension, or high triglycerides, nor a person’s gender significantly impacted the efficacy of bariatric surgery on the prevention of albuminuria. However, when Dr. Ekander considered the number needed to treat (NNT; i.e., the number of bariatric surgery patients needed to prevent a case of albuminuria) for each subgroup she detected several trends, including that the NNT for people with diabetes was four versus 10 for people without diabetes.

  • The NNT for several subpopulations differed, suggesting that these may be characteristics that predict bariatric surgery’s preventative efficacy for albuminuria.







     Not present










Above median (154 mg/dl)




Urinary albumin


     Above median (9.3 mg/24h)




  • Because the SOS Study was not a randomized controlled trial, the two study populations had several statistically significantly imbalances in baseline characteristics. Namely, these were age (the control group was slightly older), presence of diabetes and hypertension (both more prevalent in the surgery group), BMI (the surgery group was heavier), and urine albumin excretion (UAE; higher in the surgery group). Overall, these imbalances likely placed the surgery group at higher risk for developing albuminuria, according to Dr. Ekander.

Baseline characteristic




Age, years




Diabetes, %




Hypertension, %




BMI, kg/m2




UAE, mg/24 hours




Questions and Answers

Q: Did you look at if there were changes in risk factors following bariatric surgery?

A: We only looked at baseline risk factors.

Q: Were you able to track some of these folks to see if they developed end-stage renal failure?

A: We have very few patients with end-stage renal disease based on eGFR. We have to look at that more closely, but if we only use that as a measure of end-stage renal disease, then there are only 20 or so people in the entire study cohort that meet the criteria.

Q: In people with albuminuria at baseline, what difference was there in progression?

A: We have not looked at that yet. The aim was to look at prevention at this time.

Oral Presentations: Hypoglycemia

Reduced Risk Of Hypoglycemia With Insulin Degludec Vs. Insulin Glargine In Patients With T2D: A Meta-Analysis Of 5 Randomized Trials

Alan Garber, MD, PhD (Baylor College of Medicine, Houston, TX)

Dr. Alan Garber presented a meta-analysis of five phase 3 trials comparing rates of hypoglycemia with insulin degludec (Novo Nordisk’s Tresiba) to insulin glargine (Sanofi’s Lantus) in patients with type 2 diabetes – the twist was that this analysis used a much lower cutoff for hypoglycemia (<2.3 mmol/l; 41 mg/dl) than Novo Nordisk’s more standard <3.1 mmol/l (56 mg/dl), the prespecified definition. Use of the lower cutoff substantially improved the overall hypoglycemia advantage of insulin degludec relative to insulin glargine – the original 17% reduced risk of hypoglycemia (<3.1 mmol/l) improved to a 33% reduced risk at the lower <2.3 mmol/l cutoff. The small number of <2.3 mmol/l events meant that the 95% confidence interval for the rate ratio slightly widened from [0.74-0.94] to [0.56-0.82], though the new result was still highly statistically significant. The lower hypoglycemia cutoff did not meaningfully change the nocturnal hypoglycemia advantage of insulin degludec relative to insulin glargine – the original 32% reduced risk of nocturnal  hypoglycemia changed to 27% at the <2.3 mmol/l cutoff. Dr. Garber did not show data for type 1 diabetes using the lower hypoglycemia cutoff, which was disappointing – as a reminder, insulin degludec was associated with a 10% increased risk of overall hypoglycemia in phase 3 trials in type 1s, though the results were not statistically significant. It would have been valuable to have seen the type 1 data analyzed using the lower cutoff.

Questions and Answers

Dr. Stephanie Amiel (Kings College London, UK): Nice data. I may have missed it, but did you show data using the more stringent hypoglycemia cutoff for type 1 diabetes patients?

A: I’ll try to find it for you.

Role Of Mobile Technology To Improve Diabetes Care In Adults With Type 1 Diabetes: Remote-T1D Study

Satish Garg, MD (University of Colorado, Denver, CO)

Dr. Satish Garg presented encouraging results from a single-center pilot study comparing use of Sanofi’s iBGStar with the iPhone 4 (n=50) to the Accu-Chek Nano (n=50) in patients with type 1 diabetes. The study was very “real-world,” with both groups asked to contact the clinic as “frequently as they needed.” After three months, (n=88 completers) A1c improved in both groups, though there was a trend in favor of the iBGStar – a decline of 0.4% in the iBGStar group (baseline 8%; p=0.008) vs. a 0.2% decline in the control group (baseline: 7.7%; p=0.04). Due to the study’s small size and differences in baseline A1c, the between-group difference was not significant (p=0.2); we suspect a larger study may have shown a benefit to using the iBGStar though it is hard to say – we are especially looking forward to CGM data where time in range data may be telling. Dr. Garg attributed the slightly more positive outcome in the iBGStar arm to making the data available to patients on the iPhone – interestingly, the iBGStar facilitated more clinic contacts during the first month, though there was no difference from the control group by three months (thoughts below). Patient reported outcomes (hypoglycemia fear, behavior, and worry) improved in both groups and were not significantly different between the control and intervention groups. Dr. Garg only presented results for the first three months of the study, with full six month data, blinded CGM results (Dexcom G4 Platinum – great to see next-gen technology making it into studies), and cost analyses expected at ADA or EASD 2014.

  • This investigator initiated, single-center, prospective, open label pilot study (Clinical Identifier: NCT01825382) randomized 100 patients to use of an Accu-Chek Nano meter (n=50) or Sanofi’s iBGStar plus an iPhone 4 (n=50). It was a three-month study with a three-month extension period. Both groups received test strips and a blinded Dexcom G4 Platinum receiver and sensors.  The iBGStar group also received a data plan for the iPhone for use during the duration of the trial. All patients could keep the devices following the study. The trial was partially sponsored by Sanofi.
  • The goal of the study was to address the role of mobile technology to improve patient outcomes. Participants in both groups had eight visits post randomization, which included telephone visits to remind patients to wear the blinded CGM. Broadly speaking, this seemed like a very real-world study, with patients given the devices and told to contact the clinic as frequently as needed – kudos to Dr. Garg’s team for such a hands-off study design, which we believe is critical in SMBG and mobile health.
  • Patients had a mean age of ~39 years and a mean BMI of 27 kg/m2. There were no significant differences in baseline demographics between the iBGStar and control groups. Of the 100 randomized patients, 88 completed a three-month follow-up.
  • Hypoglycemia fear, behavior, and worry sub-scales improved in both groups; the between-group differences were not statistically significant. Interestingly, these patient-reported parameters were the study’s designated primary outcome, though Dr. Garg’s discussion focused on the A1c results. 
  • The iBGStar facilitated more clinic contacts during the first month, though there was no difference from the control group by three months. We think this speaks to sustaining motivation with new technology, which is no easy task. Perhaps additional aspects could be added to keep patients engaged, such as gamification or making the app more social. Those aspects certainly aren’t for every patient, though health apps are generally trending in that direction – we’ve been particularly impressed with Strava (a cycling/running app), which engages users through very easy self-tracking, unique social interaction/competition, and challenges.

Questions and Answers

Q: Can you talk more about the iBGStar intervention? You said clinic visits were the same. With iBGStar, was there some interaction with the center on the basis of glucose readings and dose adjustments?

A: We do have all the data and have not analyzed it. Patients were asked to contact the clinic as frequently as needed. Those in the iBGStar group could take a screenshot of a whole week or month of glucose values, and email it or send it as a text to the staff. That aspect was not available in the control arm, as the Accu-Chek Nano meter cannot do that. The control group could only download the results and send them as an email attachment or fax. Initially, the majority of the contacts in the first month with the clinics was definitely higher in the iBGStar arm. But at the end of three months, there was no difference in the two arms. It might be that making the data available to patients on the iPhone had an impact. We will probably look at the data more clearly down the road.

Q: Do you consider this a pilot trial?

A: Yes, it was definitely a pilot trial.

Oral Presentation: Insulin Resistance - Clinical

Dapagliflozin Improves Muscle Glucose Uptake And Increased Hepatic Glucose Production In Type 2 Diabetes Individuals

Muhammad Abdul-Ghani, MD, PhD (University of Texas Health Science Center at San Antonio, San Antonio, TX)

Dr. Muhammad Abdul-Ghani (in Dr. Ralph DeFronzo’s group) presented results from a two-week study suggesting that dapagliflozin improves muscle glucose sensitivity but also increases hepatic glucose production and plasma glucagon levels. Patients received the SGLT-2 inhibitor dapagliflozin (BMS/AZ’s Forxiga) for 14 days (n=18; n=12 for dapagliflozin, n=6 for placebo). The average baseline A1c of participants in the treatment arm was 8.4% (8.8% for placebo), and fasting plasma glucose of 165 mg/dl (161 mg/dl for placebo). Significantly, Dr. Abdul-Ghani highlighted that the observed endogenous glucose production (which Dr. Abdul-Ghani presumed to be hepatic glucose production [HGP]) increased with the use of dapagliflozin, significantly decreasing the efficacy of dapagliflozin that could be achieved if HGP was blocked – Dr. Abdul-Ghani even suggested eliminating this rise in HGP could even double the reduction of fasting plasma glucose by SGLT-2 inhibitors. Indeed, although urinary glucose secretion increased by ~80 g/day, this was offset by an increase in HGP of ~45 g/day. In addition, participants on dapagliflozin experienced a 23% increase in plasma glucagon concentrations – another counter-regulatory effect working against dapagliflozin’s blood glucose-lowering efficacy. Turning to dapagliflozin’s role in insulin sensitivity, Dr. Abdul-Ghani noted that dapagliflozin appeared to increase patients’ insulin resistance/insulin sensitivity index by ~two-fold, with the total body glucose disposal increasing by 19% (p <0.01) even after controlling for the glucose secreted through the urine.

  • As would be expected, fasting plasma glucose levels and two-hour plasma glucose levels measured by OGTT dropped significantly (p=0.02 and p <0.05, respectively) after 14-day dapagliflozin treatment. Fasting plasma glucose dropped levels dropped 28 mg/dl while two-hour plasma glucose dropped 72 mg/dl. Similarly, the change in glucose over two hours also decreased significantly by ~40 mg/dl.
  • Notably, insulin secretion (p=0.03) and beta-cell function (ΔC-peptide/ΔG + MI: P=0.02; ΔC-peptide/ΔG + Rd: p=0.03) were significantly increased after 14 days of treatment with dapagliflozin. Dr. Abdul-Ghani remarked that insulin approximately doubled after treatment with dapagliflozin. In the past, Dr. Ralph DeFronzo has posited that SGLT-2 inhibitors improve glucotoxicity through their glucose-lowering mechanism. Similarly, the two-hour change in insulin increased significantly during OGTT, as did the change in C-peptide. Insulin increased ~14 μU/ml while the change in C-peptide increased ~2.4 pmol/l (p <0.05 for both).
  • Participants had three measurements with 3H-glucose infusion (to measure HGP), and two 75 g OGTTs and euglycemic hyperinslinemic clamps: one at the beginning of the study and one at the end of the study (days six and seven), and three measurements were made with a 75 g OGTT. Additionally, HGP was measured before treatment on day one, through the first dose of dapagliflozin on day two, and again on three while OGTTs and euglycemic hyperinslinemic clamps were done at the beginning of the study and on days six and seven. Participants in the dapagliflozin arm took a 10 mg/dl dose of dapagliflozin each day, beginning on day two and continuing for up to 14 days.
  • The study was randomized 2:1 for treatment vs. control (n=18; treatment: 12; placebo: 6), with no significant differences between the two groups’ characteristics. The average BMI of the treatment group was 31.4 vs. 33.3 kg/m2 in control, and the average age of the treatment group was 50 years vs. 54 in the control.

Questions and Answers

Q: When you saw the increase in glucose production did you see any decrease in hepatic fat?

A: We did not look at that in this study.

Comment: It might be beneficial to see if there was a change from all of the excess glucose outpouring.

Q: What you were measuring was not the hepatic glucose production but rather the endogenous glucose production. Your conclusion that the liver is introducing the extra glucose to the system is reasonable, but is there any possibility that there was an increase in renal glucose production?

A: That is exactly the study we are doing now – we are looking to dissect where the glucose is coming from: the kidney or the liver. There are two points that would suggest this glucose is coming from the liver: 1) Glucagon is markedly increased, and the kidney is not responsive to glucagon whereas the liver is highly sensitive; and 2) the amount of glucose that the kidney makes would have to almost double in order to account for the increase in glucose that we saw. But your point is well taken, and we’re doing that study now.

Q: It is puzzling that glucagon levels could go up; do you have the ratio of glucagon to insulin?

A: I don’t have an answer for why glucagon goes up. We have some speculations, but we are doing studies in order to prove them. One key is the drop in plasma glucose concentration. Additionally, the glucagon to insulin ratio increases markedly even though the drop in fasting glucose is very modest and wasn’t significant when it was compared with the placebo – you had to compare the ratios to gain significance; this markedly increased and persisted for two weeks. The increase in insulin was incremental area under the curve during OGTT, which is indicative of the beta cell function.

IDF Award Lecture – Basic Science

Beyond HbA1c: Hyperglycemic Variability And Diabetic Complications

Michael Brownlee, MD (Albert Einstein College of Medicine, New York, NY)

The great Dr. Michael Brownlee, winner of one of only two IDF 2013 awards, gave an outstanding and extensively detailed basic science talk on glycemic variability. He framed his presentation with a look back at the DCCT, where A1c actually explained only 11% of the risk for microvascular complications (Diabetes 1995; Diabetes 2008). His lecture focused on mechanisms that could explain the remaining 89% of the risk for complications, centering on reactive oxygen species (ROS). Several studies have demonstrated that elevated ROS production persists for days after transient hyperglycemia. Recent data has added a more nuanced understanding: the transient exposure to hyperglycemia that occurs above a critical threshold level activates a multi-component positive feedback loop (Giacco et al., submitted). Dr. Brownlee also highlighted familial clustering studies showing that susceptibility to diabetic complications is determined in part by genetics. He concluded his presentation with very recent research on glyoxalase 1 (Giacco et al., Diabetes 2013). Notably, Dr. Brownlee discussed the enzyme in the context of nephropathy, noting that its activity appears to determines the glycemic set point at which diabetic complications occur. A recent study showed that glyoxalase 1 regulates kidney ROS levels in both non-diabetic and diabetic mice – notably, glyoxalase 1 knockdown in non-diabetic mice phenocopied diabetic nephropathy in every dimension. Concluding, Dr. Brownlee highlighted the critical importance of continuing to understand complications development: “Most diabetic patients with ESRD do not have access to hemodialysis, and for those who do, the five-year mortality rate is 70%. We have a lot to do with human morbidity and mortality.”

Symposium: Public Health Challenges in Treating Diabetes

Guidelines: Do We Have The Best Approach To Guide Practice?

Philip Home, DPhil, DM (Newcastle University, Newcastle upon Tyne, UK)

Dr. Philip Home gave a very balanced presentation on clinical guidelines, noting their advantages and carefully acknowledging the challenges in their formation and implementation. Much of his presentation emphasized the value of guidelines for the busy practicing clinician – they help promote best practices in a field where the average practitioner or specialist can’t possibly keep up on all the areas of research (Dr. Home very frankly acknowledged that even he can’t keep up with every happening!). However, he also made it clear that developing guidelines in the face of unclear evidence is quite challenging, since “the evidence base is generally weak” – many RCTs are short term, underpowered, in selected populations, not comparative, and in many cases aren’t available at all. (We would also add that many RCTs don’t reflect “real life” for patients.) Dr. Home was fairly critical on the topic of meta-analyses, noting, “Many of them are really very poor quality.” Notably, the number of meta-analyses in diabetes increased from 61 in 2007 to 223 in 2012. The end of his talk turned to guidelines implementation and highlighted a few success stories from around the world. Dr. Home was cautious on the recent worldwide move in guidelines to individualize therapy, mainly because the increased flexibility also allows for less well structured, organized, and disciplined therapy. We thought this was a particularly valuable point, especially given the environment that individualized therapy must operate in: too few HCPs to handle patients with diabetes, little patient time with HCPs, and poor reimbursement when patients are able to interact with their providers. That said, we also think new technology could help enormously on this front; “time in range” data can tell us a great deal about what therapies could benefit patients most. Going toward more individualized therapy does move patients away from “one size fits all” therapy and well as away from the “treat to failure” model under which so many patients have suffered.

  • “Why do we need to guide clinical practice?” Dr. Home provided a clear list of reasons: 1) exposure to diabetes in medical school is very limited; 2) new evidence in diabetes care appears weekly; 3) diabetes care covers several areas of practice (Dr. Home called out the 2005 IDF guidelines, which had 19 different chapters); 4) many practitioners in diabetes work in other fields too; 5) the evidence base is both large but also deficient; and 6) modern methods of access to advice require a quality information feed.
  • “A review of one DPP-4 inhibitor for EASD 2011 found 16 relevant clinical trials on diverse aspects published in 2010-2011.” Said Dr. Home, “I was unaware of about half of the papers that I was able to find.” This comment really put into perspective the sheer volume of research published every week in this field.
  • The number of published meta-analyses in diabetes increased from 61 in 2007 to 223 in 2012 (Home, Diabetes Care 2013). Dr. Home outlined many issues with meta-analyses, which he has found are often of “very poor quality” – 1) the selected choice of topic is often biased by prior knowledge; 2) they include small studies not designed for the purpose; 3) they include poor quality studies that use data gathered for secondary purposes; 4) they include observational studies with all their inherent problems; and 5) one study often dominates that analysis and contributes two-thirds or even 75% of the data. Dr. Home believes meta-analyses can be useful, particularly if they help combine underpowered studies to give better point estimates and 95% confidence intervals.

Questions and Answers

Q: I would like to ask you about meta-analyses – there are many in diabetes, and some are poor quality. One of problems I see is that people tend to regard them as providing a higher level of evidence to support clinical practice. To be honest, I think they are sometimes an easy way to achieve a publication. What do we do when people take them as gospel truth?

A: The reason I wrote that article in Diabetes Care was over the concern of many, many meta-analyses reaching the editor’s desk. There is some concern that reviewers won’t be as rigorous with them as they should be. I think it’s an issue and they need to be looked at more carefully. Where they are good quality, meta-analyses can be extremely valuable. But interpretation of meta-analysis is a difficult area. I would like to see a lot less published and a lot better comment and discussion in them about their weaknesses.

Symposium: GLP-1

Extra Pancreatic Effects Of GLP-1

Daniel Drucker, MD (University of Toronto, Toronto, Canada)

Dr. Daniel Drucker discussed the preclinical and clinical data on the extra-pancreatic effects of GLP-1 receptor agonists (GLP-1 RAs), paying special attention to their CV effects. Overall he said that it is unclear what clinical impact GLP-1 RAs have beyond the pancreas, except for on the CV system where he thinks GLP-1s have a neutral or favorable effect. Turning to the recent results from SAVOR and EXAMINE (CVOTs for BMS/AZ’s Onglyza [saxagliptin] and Takeda’s Nesina [alogliptin], respectively), Dr. Drucker pressed that the potential association of DPP-4 inhibitors with congestive heart failure (CHF) was a surprise for him and his colleagues. Dr. Drucker did not hypothesize on whether the heightened risk for CHF is a class effect or specific to some agents, nor on a potential mechanism for this association. Instead, he cited rodent models’ failure to elucidate a CHF signal as evidence that these models might be poor predictive surrogates for older, high-risk patients with pre-existing CVD. Looking beyond the CV system, Dr. Drucker noted that GLP-1 RAs are renoprotective and neuroprotective across a broad range of preclinical models. Additionally, mice lacking the GLP-1 receptor are more susceptible to kidney and central nervous system injury. In humans, Dr. Drucker highlighted a study suggesting that people with Parkinson’s disease who take exenatide do better on the dementia rating scale-2 independent of their glucose or body weight (Aviles-Olmos et al., J Clin Invest 2013).   

Questions and Answers

Q: You showed from the SAVOR and EXAMINE trials that there was no benefit shown; what do you make of the prior meta-analyses that suggested they could be cardioprotective?

A: I think we are all very well aware that meta-analyses of clinical trials for registration are very different than the type of patient populations in SAVOR and EXAMINE. We have been perhaps seduced by our desire to extrapolate the animal data and studies in pretty healthy humans to add more weight into these meta-analyses than we should. We need to step back and be more critical with the questions we are asking.

Q: Do you think that the duration of these studies was long enough to demonstrate results?

A: The trials were short, because they were designed to meet regulatory requirements. It is a valid hypothesis that testing the drugs in younger healthier populations could be beneficial, but it is a very expensive prospect. TECOS [the CVOT for Merck’s Januvia] is a somewhat longer study. We are sort of stuck, because the trials are designed to obtain events so they are studying much more high-risk individuals in whom we are unlikely to modify the disease.

Q: With regards to the increase in heart failure admissions, do we know baseline characteristics for those patients?

A: In the outcome studies there were not routine echocardiograms done on a regular basis – that was not feasible. There was a suggestion that people who had already had a heart failure were more likely to be tipped over when in the trial.

Corporate Symposium: The Evolution of Diabetes Management in the 21st Century: The Role of Sitagliptin (Sponsored by Merck Sharp and Dohme)

Potential Cardiovascular Effects Of DPP-4 Inhibitors And Implications Of Long-Term Outcomes Trials For Patients With Type 2 Diabetes

Richard Gilbert, MD, PhD (University of Toronto, Toronto, Canada)

Dr. Richard Gilbert extrapolated what the SAVOR-TIMI and EXAMINE (the CVOTs for BMS/AZ’s Onglyza [saxagliptin] and Takeda’s Nesina [alogliptin], respectively) results tell us about the CV effects of DPP-4 inhibitors more broadly. On a high level, Dr. Gilbert concluded that both trials demonstrate their respective agent’s CV safety, which likely bodes well for other DPP-4 inhibitors. With regards to DPP-4 inhibitors’ impact on congestive heart failure (CHF) risk, tentatively thinks that the significant elevation seen in SAVOR and trend towards higher risk seen in EXAMINE indicates that the increased risk is a class effect. Notably, however, he suggested that increased CHF risk might be a broader effect of multiple anti-hyperglycemic classes. He explained that research suggests sulfonylureas, insulins, and thiazolidinones are all associated with higher rates of CHF (he did not address GLP-1 agonist or SGLT-2 inhibitors). Additionally, he pointed to the lack of a prior CHF signal or an apparent mechanism of action by which DPP-4 inhibitors cause CHF as evidence that this risk might not be isolated to DPP-4 inhibitors. Given that DPP-4 inhibitors are not associated with weight gain or elevated hypoglycemia risk, as are these other classes, Dr. Gilbert suggested during the subsequent panel discussion that “DPP-4s are still the best of an imperfect bunch” – a sentiment the other panelists nodded affirmatively to. Dr. Gilbert also remarked that HCPs might need to reevaluate their A1c goal for people who are at a higher risk for CHF, since it might be generally less safe for them to take the antidiabetic agents required to reach a low target.   

Questions and Answers

Q: In your opinion, do you think that this increase in CHF is a class effect or molecule effect?

A: I think it is a surprise to everybody, if it were only a molecule effect then I would not expect the EXAMINE study to show it. I would say that we need more data. I would hold out until we see the full data set, particularly the results of TECOS [the CVOT for Merck’s Januvia]. The other thing to keep in mind is if this happens with all agents. We see it with SUs, TZDs, and insulin. I think we need to know a lot more before we make any decisions.

Q: What was the timeframe for the hospitalizations?

A: The majority of the events occurred within the first six months of initiation of therapy and then the curves remained fairly stable.

Panel Discussion

Q: The overall cost of hypoglycemia to the health system is a concern for individuals. The DPP-4 inhibitors and more expensive than sulfonylureas. Has there been an overall cost effectiveness assessment?

Dr. Juliana Chan (Chinese University of Hong Kong, China): Not that we know of. I anticipate that there will be more cost-effective analyses coming out.

Dr. Michael Nauck (Diabeteszentrum, Bad Lauterberg, Herz, Germany): I tried to compile data where there was a hospital – a very well defined capture area ­– and the result of ten of such studies (many were in Germany, Switzerland, and Sweden) was that after 40,000 patient years of SU use there will be one death related to SUs. That does not translate into cost-effectiveness but does show that there is a problem.

Q: Is there any indication for the CHF mechanism?

Dr. Nauck: I have heard an interpretation that for the purpose of these studies CHF was defined by giving additional diuretic medications. I do not know how the situation is elsewhere, but I could imagine a German ER where a young physician treats a person who is a little out of breath and gives extra diuretics early on unnecessarily. This would then get included as a CHF event. The CHF risk was not seen in the deaths, so it could be something silly like that.

Dr. Richard Gilbert (University of Toronto, Toronto, Canada): These were the adjudicated events of CHF. They had to have evidence of heart failure – either radiological or an increase in bnp. So the usual way we would diagnoses heart failure was adjudicated, so it was not just the random intern. I think the events are true.

Dr. John Prins (The University of Queensland, Queensland, Australia): There is an as of yet unpublished study called VIVIDD of vildagliptin showing increased ventricular volumes on echoes. So we now have three showing volume changes that were not anticipated. 

Q: Are there particular patients that should not be treated with these agents?

Dr. Gilbert: The issue is that the patients who were more likely to get heart failure in SAVOR were more likely to have heart failure anyways. They had elevated bnp, a prior history, etc. – factors that made them more likely to develop heart failure. What I think it means is that we then need to consider what target A1c we are aiming for and what are our choices. We do not have heart failure safety data for any of the other drugs. There is data raising concern for insulin, SUs, and certainly TZDs. Then we have all of the other problems you have to deal with, with those drugs – weight gain and hypoglycemia. My view is that if you have to get glucose down then the DPP4s are still the best of an imperfect bunch.

Dr. Prins: I am seeing nods of agreement, so I think that is a good evaluation.

Q: Are there any trials planned for looking at the use of DPP-4 inhibitors in prediabetes?

Dr. Carolyn Deacon (University of Copenhagen, Copenhagen, Denmark): I think that there is one small trial using sitagliptin in India. The problem is that the progression is so slow that it is going to take a long time to get any results.

Corporate Symposium: Orchestrating Success in Diabetes Management with Premix Insulins (Sponsored by Novo Nordisk)

Combining Premix Insulin And Incretins

Marc Evans, MD (University Hospital Wales, Cardiff, UK)

Dr. Marc Evans discussed the interesting topic of combining premixed insulin and incretins, centering his discussion on DPP-4 inhibitors. Though there is a rational basis for combining these therapies based on their complementary effects, he highlighted the scarcity of data on their combined use. The 24-week Sit2Mix trial will seek to fill in some of the gaps (Clinical NCT01519674) – the study will enroll insulin naïve type 2s inadequately controlled on metformin and sitagliptin. Patients will be randomized to either BiAsp 30 once or twice daily + metformin + sitagliptin or BiAsp 30 twice daily + metformin. In concluding, Dr. Evans provided a succinct summary slide on this area: Insulin + Incretin = rapidly evolving clinical and research field. There’s no doubt about that, especially on the heels of new DUAL II data from Novo Nordisk in today’s oral presentations.

Panel Discussion Highlights

Q: Is there a role for insulin degludec instead of glargine beyond the observed benefits for hypoglycemia?

Dr. Marc Evans (University Hospital Wales, Cardiff, UK): There is a poster on this issue. The flexible dosing with degludec, from 8-40 hours, translates into patients gaining a lot in terms of quality of life. They don’t have to worry about taking their insulin at the same time of day. There’s also an advantage for degludec in its potential for combination with aspart. There is growing data for the utility of this particular combination, from the perspective of hypoglycemia and an efficacy advantage, once or twice daily.

Q: What’s the optimum approach to add to insulin – a GLP-1 agonist or a DPP-4 inhibitor.

Dr. Philip Home (Newcastle University, UK): A GLP-1 every time.

Dr. Marc Evans: We look forward to the combination with degludec and liraglutide.

Dr. Home: What about degludec plus aspart plus liraglutide?

Dr. Evans: We could go on forever! The answer is there – a GLP-1 agonist every time with insulin. That’s largely because of the benefit in terms of body weight.

--by Adam Brown, Hannah Deming, Hannah Martin, Manu Venkat, and Kelly Close