American Diabetes Association 73rd Scientific Sessions

June 21-25, 2013, Chicago, IL Day #3 Highlights – Draft

Executive Highlights

Hello again from Chicago, where today the ADA announced a major new grant program, Pathway to Stop Diabetes – we can hardly wait to see the research that this $27-million effort produces in the years to come. But first, we’ll tell you about today…

We gained insights aplenty during the afternoon oral session on SGLT inhibitors. Dr. David Powell (Lexicon Pharmaceuticals, The Woodlands, TX) presented encouraging data on the use of a selective SGLT-1 inhibitor (LX2761) to treat diabetes in mice, where glycemic efficacy is seen at a lower dose than would cause GI side effects. In this Lexicon-heavy session, Dr. Pablo Lapuerta (Lexicon Pharmaceuticals, The Woodlands, TX) presented additional data on the impact of the dual SGLT- 1/SGLT-2 inhibitor LX4211 on blood pressure – in hypertensive patients, LX4211 reduced systolic blood pressure an average 14 mmHg over 12 weeks. Additionally, Dr. Muhammah Abdul-Ghani (University of Texas Health Science Center, San Antonio, TX) presented on a study in which dapagliflozin improved insulin sensitivity and insulin secretion. In an unexpected finding of the study, drug-induced glucosuria stimulated a compensatory increase in glucose production, thereby attenuating dapagliflozin’s efficacy. Taking a different angle on novel therapeutics, Dr. Brett Hauber (RTI Health Solutions, Durham, NC) presented data from a discrete-choice experiment suggesting that the average person with type 2 diabetes would want to pay only $5.86 more per month for a once-weekly oral antiglycemic agent instead of a daily version – of course, if adherence improves, we think that payers might reimburse the weekly option much more. As for more established therapeutic areas, today included corporate symposia from all three insulin manufacturers: Novo Nordisk, Sanofi, and Lilly.

In one of the most impressive device talks of the meeting, Dr. Trang Ly shared data on the use of Medtronic's Veo insulin pump in hypo unaware patients. Over six months, the pump eliminated (!) severe hypoglycemia without any increase in A1c – another strong testament to the clinical impact that low-glucose-suspend technology could have, once it is approved by the FDA. Tech highlights also included Dr. Steven Russell's (Mass General, Boston, MA) presentation comparing the Dexcom G4 Platinum, Abbott FreeStyle Navigator, and Medtronic Enlite. Dexcom accuracy (MARD) came in at an impressive 10.8%, slightly ahead of the Navigator at 12.3% and far ahead of the Enlite at 17.9%. Dr. Richard Bergenstal (Park Nicollet International Diabetes Center, St. Louis Park, MN) presented results from one of the few studies comparing structured self-monitoring of blood glucose to continuous glucose monitoring in patients with type 2 diabetes. Both SMBG and CGM resulted in significant improvements in A1c and time in range compared to baseline (no between-group difference), but only CGM reduced the percentage of readings in the hypoglycemic range. The day closed with the annual JDRF/NIH Research Meeting for closed-loop glucose control – a session that featured a keynote by Dr. Aaron Kowalski (JDRF, New York, NY).

On the obesity side, we were encouraged to see highly respected diabetes KOLs join obesity specialists at the podium of Vivus-sponsored and -supported events. For example, Dr. James Gavin (Emory University School of Medicine, Atlanta, GA) led Vivus’ product theater on Qsymia, and Dr. Ralph DeFronzo (University of Texas Health Science Center, San Antonio, TX) asserted that insulin resistance is the common factor between obesity, type 2 diabetes, hypertension, and other complications. We believe that having these KOLs support anti-obesity pharmacotherapy indicates growing awareness of obesity as a disease, especially among top endocrinologists.

During this year’s prestigious Banting Award Lecture, Dr. Graeme Bell (University of Chicago, Chicago, IL) spoke of his exciting career identifying the earliest genes associated with rare forms of diabetes. He noted that the terms “MODY” and “neonatal diabetes” really encapsulate a diverse set of diseases with varying mechanisms and genetic causes. He promoted genetic testing for MODY and neonatal diabetes, arguing that such testing could be cost-neutral and provide far better patient outcomes. He ended by noting that genetics, like insulin, cannot cure diabetes but can certainly improve the quality of treatment.

Table of Contents 


Oral Sessions: Hypoglycemia – Novel Concepts


Trang Ly, MBBS, DCH (Princess Margaret Hospital, Perth, Australia)

Dr. Trang Ly presented what Dr. Hans DeVries called “the most important study at this whole meeting” – a randomized controlled trial comparing low glucose suspend (LGS; n=46) to pump-only therapy (n=49) over a six-month period in patients with hypoglycemia unawareness. In the six months prior to baseline, the number of severe hypoglycemia events was comparable between the groups: six in the low glucose suspend group and five in the insulin pump-only group. Notably, after six months on low glucose suspend, the number of severe hypoglycemia events dropped from six to zero (!) in the low glucose suspend group, compared to an increase from five events to six events in the group on a pump only. This was highly compelling data in our view, especially because the definition of severe hypoglycemia was very strict in this study: seizure or coma (i.e., it was not the more common “needing assistance definition). Those using LGS also experienced less average time spent <70 mg/dl. Most importantly, these benefits occurred without a deterioration in A1c (baseline: 7.4%). We commend the authors for deliberately selecting hypoglycemia unaware patients, as this group stands to benefit the most from low glucose suspend technology.

  • This study randomized 95 hypoglycemic unaware patients to use of low glucose suspend or pump therapy-only for six months. Patients had a mean age of 19 years (4-50 year olds were included, with a fairly even distribution), a mean duration of diabetes of 11 years, at least six months on a pump, and a Clarke’s questionnaire score of >4. Hypoglycemia clamps were done in a subset of patients to assess counterregulatory responses. Severe hypoglycemia events were strictly defined as “seizure or coma.”
  • Low glucose suspend dramatically reduced the number of severe hypoglycemic events vs. those on pump therapy only. We found this data quite striking in just a six- month period – to us, it truly shows the power of even very simple automated insulin delivery to improve upon the challenges of dosing insulin manually.

Insulin Pump Only (n=49)

Low glucose suspend (n=46)

Severe hypoglycemia in six months preceding baseline

5 events

25.5/100 patient years

6 events

22.0/100 patient years

Severe hypoglycemia at study end (six months)

6 events

26.7/100 patient years

0 events

0/100 patient years

Incidence rate difference from baseline to endpoint

17.8 (p=0.019)

  • Importantly, there was no change in A1c in either group from a baseline of 7.4%. There was no difference at baseline in the percentage of time spent under 70 mg/dl. However, the average percentage of time spent under 70 mg/dl and 60 mg/dl during the overnight period improved in the LGS group during the study (p=0.006 and p=0.009).
  • As might be expected, sensor usage was not particularly high in the 12-18 year-old group using sensor-augmented pumps with low glucose suspend. By age group sensor use was 71% (4-12 years), 54% (12-18 years), and 81% (12-18 years). We would have been interested to see the data cut by age, as we would guess the improvement in hypoglycemia were even stronger in the youngest and oldest groups.
  • Epinephrine responses to hypoglycemia were unchanged in both groups post intervention. Parents and patients reported reduced fear of hypoglycemia in both groups. Hypoglycemia unawareness score improved in both groups.
  • As pump therapy-only was the control group in this study, we wonder how pump + CGM would have fared in a similar study of hypoglycemia unaware patients. Without this third arm, it’s possible that the severe hypoglycemia benefits could be attributed to the addition of CGM alone (rather than LGS). Of course, the results closely parallel the severe hypoglycemia findings in the ASPIRE in-home study (four events in the control group vs. zero in the intervention group), which compared sensor-augmented-pump alone to threshold suspend.

Questions and Answers

Dr. Hans DeVries (University of Amsterdam, Netherlands): I must compliment you. I think this is the most important study presented at this whole meeting. Did you administer the Clarke questionnaire at the end?

A: Yes. There was improvement, in both groups. In the interest of time, I have not presented all the data. We also measured fear of hypoglycemia and quality of life. There was a significant improvement in both groups.

Q: How did the LGS work – was it patients waking up to alarms and taking glucose, or was it mostly automated?

A: In about half of the cases, there was patient intervention – they would wake up and either resume insulin delivery or eat. In about half of the cases, you would continue to the full two-hour insulin suspension.

Q: Were there problems with false alarms?

A: It’s an important question; we found that early morning glucose values did correspond to patients being low overnight. That did suggest that these were true events being treated rather than false positives.

Q: You had limited data for clamps. Did symptom scores or anything change?

A: We did not show a change in the counter-regulation hormone response. It comes down to the fact that patients did not wear it enough. Perhaps they did not avoid hypoglycemia enough. As you know, the pilot data was in a smaller group.

Q: Did cognitive function and symptom scores change?

A: We did not do a cognitive assessment. Symptom scores did not change convincingly.

Q: Were all the severe hypoglycemia episodes at night?

A: In the control group, there were six events, and five of the six were at night. So severe hypoglycemia that was avoided was nocturnal hypoglycemia.

Oral Sessions: Updates and Applications of Continuous Glucose Monitoring


Steven Russell, MD, PhD (Massachusetts General Hospital, Boston, MA)

Dr. Steven Russell presented a head-to-head-to-head accuracy comparison of the Abbott FreeStyle Navigator, Dexcom G4 Platinum, and Medtronic Enlite CGMs in 24 patients simultaneously wearing all three sensors in 48-hour closed loop experiments – this expanded on some of the preliminary data shared at ADA 2012 in fewer patients. Dexcom’s G4 Platinum was the most accurate sensor (MARD: 10.8%, 85% in Zone A of the Clarke Error Grid), followed closely by Abbott’s FreeStyle Navigator (12.3%, 84% in Zone A); both were much more accurate than Medtronic’s Enlite with the Veo algorithm (17.9%, 68% in Zone A). All three devices had similar rate accuracy. Concluding, Dr. Russell discussed CGM calibration errors, noting that they are still a problem and providing some rules for optimal calibration. We salute the team’s strong data-driven approach to closed-loop control – it certainly shows in their rapid progress, and we’re guessing it helps quite a bit when talking with the FDA.

  • Dr. Steven Russell shared comparative CGM accuracy data from 48-hour, inpatient closed-loop experiments in 24 patients (12 adults, 12 children). Patients simultaneously wore the Abbott FreeStyle Navigator, Dexcom G4 Platinum, and Medtronic Enlite (Veo algorithm). Calibration occurred per the manufacturer’s schedule using reference blood glucose values (GlucoScout) – before breakfast and dinner for the G4 Platinum and Enlite, and as prompted by the Navigator (i.e., it asks for calibrations at specific intervals after the sensor starts). A 6 am “sanity check” was also performed for the Navigator, and if the sensor value was far enough off, a calibration would be forced. Reference blood glucose values were taken every 15 minutes with the GlucoScout (n=4,657) and YSI was taken approximately every hour. Relative to YSI, the GlucoScout had a MARD of 6% and a slope of 1.05 (“This is a very accurate device”). Some of the inaccuracy of the GlucoScout was likely due to sampling error.
  • Dexcom’s G4 Platinum was the most accurate sensor (MARD: 10.8%, 85% of points in Zone A of the Clarke Error Grid), followed by Abbott’s FreeStyle Navigator (12.3%, 84% in Zone A) and Medtronic’s Enlite sensor (17.9%, 68% in Zone A). While the CGM vs. YSI slopes of the Enlite and G4 Platinum were near one, the Navigator had a slope of– this implies it tends to underestimate high blood glucose values. In the team’s previousstudy presented at ADA 2012, MARDs were 11.8% for the FreeStyle Navigator, 16.5% for the Dexcom Seven Plus, and 20.3% for the Guardian.
  • Dr. Russell noted that both the FreeStyle Navigator and G4 Platinum have lower MARDs and narrower standard deviations relative to the Medtronic Enlite. We see this narrowing of the spread in CGM accuracy as a very important advance, since it reduces the types of large errors that frustrate patients. All three devices had similar rate accuracy (CGM rate of change vs. plasma glucose rate of change).
  • “CGM calibration errors are still a problem.” Dr. Russell showed a study example from a FreeStyle Navigator calibration when the blood glucose was rising sharply – the calibration shifted the CGM curve right (relative to YSI) and made the Navigator inaccurate for the rest of the day. Dr. Russell also candidly explained that calibration can also rescue poor accuracy – he showed another example where an inaccurately reading sensor was quickly corrected after a calibration.
  • The MGH/BU team has developed calibration rules for the ongoing outpatient Beacon Hill study. Good times to calibrate are when the CGM rate of change is <1 mg/dl/min, it’s been 15 minutes since the last glucagon dose, and when at least 30 minutes have passed since the last meal. If it’s not a good time to calibrate, the team waits until the aforementioned conditions are met.

Questions and Answers

Q: With this technology being so young, it’s amazing how quickly these devices have developed to become some accurate. They are pretty close to traditional meters.

A: If you give them the right calibration. That’s still the Achilles of this technology. We had times when we calibrated poorly because we didn’t have these rules in place. Someone in the real world could fall prey to those, and it could lead to a dangerous conditions. We need a way to translate what we do in highly supervised settings to the real world.

Q: Which improvement is more important?

A: Accuracy is important, but it’s also important to reduce the variability of this accuracy. Ken Ward and others have looked at the occurrence of large CGM errors. Reducing the incidence of very large errors is really important as well. Those are the ones that can lead to inappropriate performance of the closed loop.

Q: In all of these studies, I would encourage comparison of the bihormonal approach with the insulin-only approach. Only you can do that. The field needs that to establish the necessity of glucagon. I would guess the average glucose would be substantially better with glucagon than without, but we need that study.

A: Thanks for the comment. We have decided to go with the bihormonal approach given the limited amount of effort we can spend and limited money. We’re fairly convinced that there are circumstances where only glucagon can prevent hypoglycemia – specifically, exercise. If you go into exercise with a normal blood glucose and see an average rate of change of -2 mg/dl/min, you’re hypoglycemic in 15 minutes. There’s no way that adjusting insulin can prevent that hypoglycemia. If you want truly closed loop with no carb interventions, the only way to do that is with a counterregulatory hormone.

Q: Has your closed-loop work established an accuracy threshold for CGM?

A: I presented data on our closed-loop results on Friday. We’ve only used the FreeStyle Navigator and G4 Platinum to drive our algorithm. Our control is very good with those sensors. The Navigator has had a MARD of ~12% in our studies. I can say that that’s good enough. To the extent that you can get better than that with G4 is great. What I cannot say is the upper threshold – what is the maximum you can have to still drive closed-loop. I don’t have clinical data on that.


Richard Bergenstal, MD (Park Nicollet International Diabetes Center, St. Louis Park, MN)

Dr. Richard Bergenstal and colleagues compared the impact of continuous glucose monitoring (CGM) vs. structured self-monitoring of blood glucose (SMBG) on glycemic control in patients with uncontrolled type 2 diabetes (n=104). The trial assessed change in A1c, time in range (70-180 mg/dl), and percent of readings in the hypoglycemic range. After four months, patients in both the CGM group and the SMBG group showed a statistically significant improvement in A1c and time in range from baseline; no between group difference was observed. However, when considering the percent of readings in the hypoglycemic range (blood glucose <70 mg/dl, <60 mg/dl, or <50 mg/dl) CGM utilization conferred a more significant benefit. By this metric, in fact, SMBG did not result in any significant changes from baseline. Dr. Bergenstal concluded that effective utilization of either SMBG or CGM data can improve A1c, but that CGM may be more effective than SMBG in reducing hypoglycemia whilst improving A1c in patients with type 2 diabetes.

  • “No study to date has used CGM to compare the degree of glucose control achieved using SMBG.” We were certainly excited to see Dr. Bergenstal and his team be the first and hope that his study will further fuel the conversation on CGM use and reimbursement in type 2 diabetes.
  • Patients with uncontrolled type 2 diabetes (A1c >7%) were randomized to either structured SMBG or real-time CGM (n=55 and 59, respectively); baseline therapy varied. Patients were seen every two to four weeks for therapy adjustments, which were made by reviewing the Roche Accu-Check 360 View for SMBG patients or the ambulatory glucose profile (AGP) for CGM patients. Patients’ baseline characteristics are outlined below.


CGM Group

SMBG Group




Number of Females



Age (years)



Age of Onset (years)



Height (in)



Weight (lbs)



BMI (kg/m2)



Systolic Blood Pressure (mmHg)



Diastolic Blood Pressure (mmHg)



  • Primary outcomes included change in A1c, time in range (70-180 mg/dl), and percent of readings in the hypoglycemic range, when defined as blood glucose <70 mg/dl,<60 mg/dl, or <50 mg/dl.
  • After 16 weeks, patients utilizing both CGM and SMBG data saw a significant decrease in A1c from baseline (p <0.001). Area under the curve (mg/dl x 24 hours) also improved significantly (p <0.001). However, there was no significant between group difference for either metric.

Study Arm

Baseline A1c

16-week A1c










  • Time in range (70-180 mg/dl) significantly improved in both groups (p <0.001); however, only CGM utilization resulted in a significant reduction in the percent of readings in hypoglycemia. Between group difference was significant for the percent of readings <70 mg/dl (p <0.01), <60 mg/dl (p <0.01), and <50 mg/dl (p <0.05). Importantly, when segmenting the data by medical therapy (insulin, sulfonylureas [SFU], or non-hypoglycemic agents) CGM appeared to have a more pronounced benefit compared to SMBG in insulin- andSFU- treated patients. In patients on non-hypoglycemic agents, this between group difference seemed to disappear.

Questions and Answers

Dr. Robert Vigersky (Walter Reed National Military Medical Center, Bethesda, MD): In your insulin-using patients, did you break out those who were on prandial insulin vs. basal insulin and were there any differences in the results?

A: Excellent question. We have a lot of breaking out to do with the data. You saw there were 59 patients in the CGM group and 55 patients in the SMBG group. When you break out these numbers among the various therapies it is getting very hard; the numbers are too small. It does appear that the benefits continue to expand the more aggressive the insulin therapy you are on, but again there’s a handful of patients in each group so I would be reticent to make conclusions.

Dr. Vigersky: Did you look at the use of CGM from a behavior modification approach? Did you give any questionnaires to patients on quality of life or to see how they actually use the CGM?

A: We’re just starting to look at that. We’ll be reporting on that, but the top level is that they say, ‘This is really interesting. No one has really showed me my data before.’ It wasn’t that we made dramatic medication changes, but that people saw their data and took some of their own action.

Dr. David Price (Dexcom, San Diego, CA): I was surprised that time spent in hyperglycemia didn’t change. Why do you think this was the case and what instructions did you give people about how to modify their lifestyle? What did you tell people to do?

A: There wasn’t extensive real-time education; it was more that we explained the therapy and said, here’s how to look at numbers, but we didn’t give them structured guidance. It was more look at your numbers and understand what’s happening. Then we did structured reviews each month.


Guido Freckmann, MD (Institute for Diabetes Technology at the University of Ulm, Ulm, Germany)

Dr. Guido Freckmann presented data on the accuracy and precision of Roche’s investigational CGM sensor. People with type 1 diabetes (n=30) each wore two sensors for seven days, calibrating each sensor twice daily. Every day, subjects performed self-monitoring of blood glucose (SMBG) tests at each of several time points: bedtime, 3 am, before each meal, and one, two, and three hours after each meal. Also, on days two and three, patients ate a high-glycemic-index breakfast with a delayed insulin bolus in order to cause large glucose excursions; reference measurements were taken every hour for five hours after this meal. Sensor accuracy was measured in mean absolute relative deviation (MARD) between CGM and SMBG values. The aggregate mean MARD was 9.2% overall (n=6,801 paired measurements), 12.3% in hypoglycemia (≤70 mg/dl), 9.1% in euglycemia (71-180 mg/dl), and 8.5% in hyperglycemia (>180 mg/dl). Researchers also measured the agreement between sensors, as described by precision absolute relative difference (PARD). The aggregate mean PARD was 7.5% overall (n=281,394 paired measurements), 12.4% in hypoglycemia, 7.4% in euglycemia, and 6.4% in hyperglycemia. We agree with Dr. Freckmann that the data suggest promise, but we do not think that the study design permitted a direct comparison to pivotal trials of available CGM systems (because, e.g., the Roche sensor’s accuracy was compared to measurements with the same meter used for calibration, rather than a separate reference method).

  • In this seven-day study of Roche’s investigational CGM system, 30 people with type 1 diabetes each wore two Roche sensors concurrently. Patients had mean age of 47 years old, mean BMI of 27 kg/m2, mean A1c of 7.7%, and mean duration of diabetes of 23 years. Half were male, and 22 of the 30 used insulin pumps.
  • To obtain reference measurements, patients tested their capillary blood glucose with Accu-Chek Aviva meters roughly 15 times per day: before each meal; one, two, and three hours after each meal; before bed; and at 3 am. Dr. Freckmann explained that at each time point, two fingerstick tests were performed. The first fingerstick was used for calibrations and reference measurements, but it was considered “valid” only if the second fingerstick was within 10% of the first one – if not, testing were repeated until 10% agreement occurred. This certainly is a deviation from real-life conditions (albeit not as much as if the two fingersticks had been averaged), and we are not sure how much the performance data were inflated by this choice of study design.
  • The sensors were calibrated two hours after insertion and twice every day thereafter. The prototype sensors did not have the capacity for real-time calibration, so calibrations were performed retrospectively. These retrospective calibrations were prespecified in a partial effort to simulate prospective conditions: calibration was always performed with the same two tests every day (the pre-meal test in the morning and the pre-meal test in the evening). However, as noted above, a fingerstick was considered “valid” for calibration only if it agreed within 10% to another fingerstick taken concurrently.
  • On two study days, patients were fed high-glycemic-index breakfasts with a delayed insulin bolus in order to produce a wide range of glucose data. Fingerstick tests were performed every 15 minutes for the five hours following this meal. However, only one test per hour was included in the analysis as a reference measurement. (According to Dr. Freckmann, including more-frequent reference measurements would have made the sensor appear less accurate. As we understand it, MARD would have been roughly 1.5% higher if the reference measurements included the post-meal tests every 15 minutes rather than just the ones that occurred on the hour.)
  • Evaluating the accuracy of the CGM compared to the Accu-Chek Aviva blood glucose meter, the researchers found that mean absolute relative deviation (MARD) was below 10% overall and below 14% in the hypoglycemic range. Data were presented in two ways: aggregate MARD (with all of the paired data points pooled together) and average MARD (the average of the MARDs for each individual sensor). Dr. Freckmann cited the user guides of the Dexcom G4 Platinum, the Abbott FreeStyle Navigator, and the Medtronic Guardian REAL-Time to say that currently marketed CGM systems have MARDs ranging between 12.8% and 19.7%. However, we caution that a direct comparison of those numbers to the Roche sensor’s MARD could be misleading, due to the unusual protocol for calibration and reference measurements described above.

# CGM-SMBG data pairs

Aggregate MARD

#CGM sensors

Average MARD






≤70 mg/dl





71-180 mg/dl





≥180 mg/dl





  • To measure sensor precision, the researchers compared each patient’s two sensors to each other; they found that precision absolute relative deviation (PARD) was below 8% overall and below 12.5% in the hypoglycemic range. Data were presented in two ways: aggregate mean PARD (the mean of all the paired data points pooled together) and average mean PARD (the mean of the PARDs for each pair of sensors). To suggest a rough benchmark, Dr. Freckmann noted that PARD for currently marketed sensors have been found to range from 15.3% to 16.0% (Bailey et al., Diab Technol Ther 2009; Zisser et al., J Diabetes Sci Technol 2009) – of course, differences in study design make a direct comparison difficult.


data pairs

Aggregated mean PARD

# sensor pairs

Average mean PARD






≤70 mg/dl





71-180 mg/dl





≥180 mg/dl





  • Dr. Freckmann presented a simple simulation of the sensor’s ability to detect hypoglycemia below 55 mg/dl. To perform this analysis, the researchers looked at all of the CGM values taken when the reference measurements was under 55 mg/dl. Of these CGM values, 79% were below 60 mg/dl, 88% were below 65 mg/dl, and 96% were below 70 mg/dl. These percentages roughly correspond to how often a glucose value of 55 mg/dl or lower would be detected by the CGM if its alarm threshold were set at 60, 65, or 70 mg/dl. However, the actual rates of hypoglycemia detection and prediction would be different if the CGM could use trend information instead of just point estimates, so Dr. Freckmann looked forward to a that a true study of hypoglycemia prediction/detection with the Roche CGM.

Questions and Answers

Q: With accuracy improving in the hypoglycemic range, can you think of other applications for this sensor besides diabetes? We also monitor hypoglycemia in glycogen storage diseases and other metabolic disorders.

A: Yes.

Q: It seems currently that MARD is widely used as a measure for CGM accuracy. What is the regulatory requirement for accuracy, in order for a system to become commercially available? I do not see such a clear-cut requirement as the ISO standards for blood glucose meters.

A: I am not aware of such a clear-cut threshold. Currently CGM devices are approved only as adjuncts to blood glucose meters.


Xiaoxiao Chen, PhD (Senseonics, Germantown, MD)

Dr. Xiaoxiao Chen presented data from a recent 29-day clinical trial of Senseonics’ implantable continuous glucose monitor (n=24 patients, each with one-to-two sensors implanted in the wrist, upper arm, or abdomen). He showed that the fluorescence-based sensor appears to be more accurate when placed in the upper arm or abdomen (MARD <12%, Clarke A >80%) rather than the wrist (MARD 13.1%). Dr. Chen attributed the between-site differences to the wrist’s greater temperature fluctuations. These temperature fluctuations affect the sensor’s fluorescence, which seems to have led to worse accuracy (even though the system is designed to account for temperature changes). Dr. Chen concluded that Senseonics is now focused on developing sensors for implantation in the abdomen or upper arm.

  • Dr. Chen described Senseonics’ current plans for the design of its CGM. The device would consist of four elements: a sensor, a transmitter, a smartphone for data display, and a Web-based data management system.
    • Senseonics’ subcutaneously implanted sensor uses a glucose-binding, fluorescent polymer hydrogel inside a rigid PMMA encasement. Also inside the encasement is a light-emitting diode (LED) to excite the fluorescence, as well as two photodiodes to filter the light and detect fluorescence. When glucose reversibly binds to the hydrogel, the hydrogel fluoresces more strongly. As for shape and size, the sensor is a rounded cylinder with a length roughly equal to the diameter of an M&M.
    • Fluorescence data are wirelessly sent from the sensor to a transmitter that is worn on the body, near where the sensor is implanted. The transmitter converts the raw sensor data into glucose values and trends. Depending on the glucose signal, the transmitter can issue its own alarms and alerts by vibration and/or LED lights. Additionally, the transmitter wirelessly sends power to the sensor via near-field communication. The transmitter sends glucose data via Bluetooth low energy to a smartphone, where they are displayed for patients. The data will also be stored online.
    • The transmitter looks fairly similar to the transmitters worn with current CGM, albeit perhaps a bit larger. Based on the pictures that Dr. Chen showed, the transmitter appears to be thicker than a typical smartphone, with a ‘footprint’ roughly half the size of a playing card. Relative to Senseonics’ previous plans of using a transmitter embedded in a wristwatch, we think that the new design offers less of a convenience advantage compared to current CGM. That said, we think that many patients would be excited for a CGM that does not require frequent sensor insertions and that eliminates concerns about the sensor itself falling out.
  • Dr. Chen described the results of a 29-day study that included 24 patients wearing one-to-two sensors in various sites: the wrist, the upper arm, or the abdomen. The study included six clinical visits, each at least eight hours long, duringwhich sensor accuracy was compared against YSI reference values. Dr. Chen mentioned during Q&A that calibration was required twice daily, but we are unsure of the details.
  • Sensors implanted in the wrist had a mean absolute relative deviation (MARD) of 13.1% – slightly less accurate than sensors in the upper arm (MARD 11.5%) or abdomen (9.4%). A similar pattern was seen for performance in the Clarke Error Grid zone A (77% wrist, 83% upper arm, 91% abdomen) and in the Continuous Glucose Error Grid zone A (78%, 84%, 85%). This pattern of relative accuracy was consistent for measurements in hypoglycemia, euglycemia, and hyperglycemia.
  • The discrepancy between sensor sites was attributed to greater temperature fluctuations in the wrist than in other sites. The average difference between minimum and maximum temperatures in the wrist was found to be 6.4C, as compared to 4.4°C in the upper arm and 4.0C in the abdomen. The wrist also had a faster average rate of change: 2.5°C per hour, as compared to 1.0C per hour in both the upper arm and abdomen. Someone during Q&A noted that the wrist is also exposed to more ambient light, but Dr. Chen indicated that the sensor is designed to block external light sources.

Questions and Answers

Q: Is this system self-calibrating?

A: It requires two calibrations per day.

Q: Your system is photodynamic. Can it be affected by external light sources?

A: Yes, it could be affected by ambient lights. But our sensor is designed to block light from other sources.

Q: So sunlight would not affect it.

A: It could, but we do have a design to block the ambient light.


Achim Muller, MD (EyeSense, Grossostheim, Germany)

Dr. Achim Muller presented a small study of 10 people with diabetes wearing EyeSense’s percutaneous optical fiber CGM (FiberSense). The fiber is placed 5 mm under the skin (abdomen or upper arm) and connects to a base plate on the surface of the skin that fixes the sensor; a rather clunky detector is then worn on the body and reads the sensor data via a small cable. MARDs ranged from 7.8-8.8%, and 93- 94% of points were in Zone A of the consensus error grid (Zone B was the remaining 6-7%). For hypoglycemic, euglycemic, and hyperglycemic ranges, MARDs consistently averaged below 10%. The device was worn by patients for up to four weeks, and error over time only deteriorated in the last few days. Dr. Muller attributed this to the adhesive between the base plate and the skin, not the sensor itself. The accuracy data is encouraging, though the study was quite small. A major limitation we see is that the device does not look user friendly to wear – this will be key for the company to improve if it seeks to commercialize this CGM. It was also unclear whether the data was displayed real-time during the study, or whether it was retrospectively calculated. We would assume the latter since we did not see a receiver screen in the picture of the device.

  • The accuracy and acceptability of EyeSense’s FiberSense CGM was tested in 10 people with diabetes for up to four weeks of wear time. The study included six in-clinic measurement sessions with glucose challenges (3.5-4.5 hours each) and laboratory blood glucose taken every 10 minutes. Five off-clinic measurement sessions (up to five hours each) were alsoperformed, with SMBG taken every hour. There were 947 reference-CGM pairs for the upper arm placement and 857 reference-CGM pairs for the abdominal placement. To measure clinical acceptance, patients were asked to compare the EyeSense device to the Dexcom Seven Plus on comfort.
  • Patients rated the FiberSense a 4.0/5 for overall upper arm comfort and a 2.8/5 for abdomen comfort; this compared to 4.2/5 for the Dexcom Seven Plus worn on the abdomen. The slide noted that comfort was “comparable” to the Dexcom, though we would note that the abdomen rating for overall comfort was substantially lower. No p-values were presented. There were “no or only very mild skin effects” after four weeks of wearing FiberSense.

JDRF/NIH Closed-Loop Research Meeting


Aaron Kowalski, PhD (JDRF, New York, NY)

Dr. Aaron Kowalski opened the meeting with a nice mix of optimism and realism: “We’ve made tremendous progress, but the proof is in the pudding and we need to deliver…Here we are. We’re on the cusp. It’s go-time right now.” He provided a nice review of the major artificial pancreas (AP) achievements since ADA 2012, headlined by significant outpatient trial experience in the past year. Dr. Kowalski then ran through each area of his six-panel roadmap to an AP – he detailed all the specific examples research groups are doing in each area. At next year’s ADA, Dr. Kowalski expects to see significant new data as a number of trials report out. He concluded with optimistic gratitude, “ As someone with diabetes and the brother of someone who battles severe hypoglycemia, I really thank everybody. Everybody in this room is playing an integral part in moving this field forward. We’re not there yet. We have a low glucose suspend system around the world, hopefully in the US soon.”

  • “We still need better tools to treat people with diabetes.” Dr. Kowalski showed A1c, severe hypoglycemia, and DKA data from the T1D Exchange – all emphasized his point quite well that people with type 1 diabetes are not doing that well. We’ve become very familiar with these slides given their growing presence in talks in the past year, though they are still jarring every time we see them. Whenever we see those average A1c numbers at top clinical centers (well above 8%) and rates of severe hypoglycemia as high as 14%, we're reminded that the needle still has plenty of room to move.
  • Dr. Kowalski’s six-panel AP roadmap has guided JDRF’s strategy in the past few years. He emphasized that it was not designed to say, “This is the only way to develop an AP.” Rather, it was Dr. Kowalski’s attempt at Voltaire’s maxim: “Don’t let perfection be the enemy of the good” – the roadmap attempts to bring incremental devices to market that bring meaningful clinical outcomes.
  • The “number one major advance” in AP research since ADA 2012 has been the dramatic increase in outpatient experience with prototype systems (“absolutely incredible”). Later on in his talk, he called Dr. Roman Hovorka’s ongoing three-week, unsupervised home study “absolutely amazing and “data that is going to be game changing.” Other important 2012-2013 achievements include(d) the release of the FDA’s comprehensive AP guidance, the recent FDA/NIH/JDRF workshop, 16+ approvals of new or significantly modified studies by FDA, MHRA, and other regulatory bodies, and 32+ peer reviewed manuscripts and abstracts within the JDRF consortium.
  • Threshold low glucose suspend: “This is so incredibly important as a first step.” Dr. Kowalski highlighted the ASPIRE in-home data just published in the NEJM. Even just based on a threshold, the study showed a significant 38% reduction in nocturnal hypoglycemia (“fantastic”). “Importantly,” he noted, “A1c was similar in the two groups.” He concluded the section emphatically: “We can do this. This is real, and the risk is low.”
  • Predictive suspend/attenuation: Several studies are going on around the world, including work at Medtronic, studies in Australia from Dr. Tim Jones’ group, and joint work at Stanford/Colorado/Western Ontario/Jaeb. These include several home studies.
  • Treat to range: Dr. Kowalski covered an broad array of ongoing work in this area, including studies at UVA/Montpellier/Padova/UCSB/Sansum, AP@home, and Stanford/Colorado/Yale. Exciting upcoming studies include a Helmsley Charitable Trusted funded camp study this summer, multi-center treat-to-range studies, and trials at Yale testing missed meal boluses and exercise.
  • Speeding insulin: Yale has upcoming closed-loop studies on the InsuPatch and hyaluronidase. UCSB/Sansum are testing Roche’s DiaPort and MannKind’s Technosphere insulin.
  • New algorithms: UCSB and the Illinois Institute of Technology are working on new algorithms, especially those that deal with exercise and reduce the burden of meal announcements.
  • Multi-hormone: A number of investigators are in this space, including Dr. Ken Ward’s group in Oregon (glucagon), the BU/MGH team’s bihormonal work (the ongoing insulin/glucagon Beacon Hill study and upcoming Summer 2013 camp studies; “lots of buzz”), and Yale’s work on pramlintide and upcoming work with liraglutide.


Roman Hovorka, PhD (University of Cambridge, Cambridge, UK) and Boris Kovatchev, PhD (University of Virginia, Charlottesville, VA)

Dr. Roman Hovorka and Dr. Boris Kovatchev exchanged competing views about the role of remote monitoring for artificial pancreas devices. Dr. Hovorka contended that remote monitoring is useful for data collection but not worthwhile as an added safety feature. In his group’s ongoing outpatient trial of overnight control, the only safety measure is reversion to open-loop dosing; he noted that this feature has been used safely in 10-15% of ~450 nights. In his rebuttal, Dr. Kovatchev said that the main value of remote monitoring would be to diagnose problems proactively, while several other attendees spoke in favor of reactive, real-time monitoring as well. These speakers argued that the costs of remote monitoring are low and that the additional safety could be important, even if it doesn’t make the system “bulletproof.”

  • Dr. Hovorka considers remote monitoring a “wonderful tool for data capture” during clinical studies, but he is wary of using it for safety mitigation during clinical research. He believes that the technology is not reliable enough to be a core safety feature. Also, once remote monitoring has been introduced, researchers may have a hard time ever proving that the system is safe enough to remove the monitors. He proposed that the failsafe for closed-loop products should be a reversion to open-loop diabetes management – a strategy that has worked safely in roughly 450 nights of home use in his group’s ongoing clinical study. (He indicated that reversion to open loop has occurred on 10% to 15% of nights.) Looking to commercialized closed-loop products, Dr. Hovorka said that he can see the utility of real-time remote monitoring for apatient’s loved ones, but he is more skeptical of the value for clinicians, given that healthcare providers already have so little time to interact with patients.
  • Taking the engineering perspective, Dr. Kovatchev argued that the chief benefit of remote monitoring is not to respond to emergencies, but to diagnose issues in advance. (We were unsure whether he meant diabetes problems, technical problems, or both.) He added that remote monitoring would reduce the burden on local clinical staff and would allow centralized teams of experts to address complex problems. Dr. Bruce Buckingham has shown that remote monitoring can reduce hypoglycemia in a diabetes camp setting, Dr. Kovatchev noted. The system operated 97% of the time in this study; given that it was “the first trial ever done,” Dr. Kovatchev suggested that the technology would improve from here. He envisions a gradual progression toward a system that has vertical integration of the pump and sensor, a smart-phone controller, and a cloud-based platform for data management. He explained that this design would enable distributed computing (e.g., basic safety features on the pump, with increasingly complex calculations on the smartphone and in the cloud).

Quotes from discussion

Dr. Hovorka: Our experience is that the educational barrier is not about closed-loop control; it’s about learning about pumps and CGM.

Dr. Kowalski: This is not an artificial-pancreas-specific issue…I think the idea that you can remotely monitor and identify diabetes issues is a broad problem, and we don’t do it with the technologies that we have now.

Dr. Stuart Weinzimer (Yale University, New Haven, CT): It’s a totally different scale once you release these systems to the public. I will use John Mastrototaro’s example: if 300,000 people use a system every night for a year, that is 110 million nights.

Dr. Howard Zisser (Sansum Diabetes Research Institute, Santa Barbara, CA): I think that we get lost in the idea that the system has to be bulletproof. I think that the goal is simply to make the risk as low as possible.

Dr. Jonathan Javitt (Telcare, Bethesda, MD): An artificial pancreas is probably $500 to $1,000 of electronics, at the end of the day. The cost of adding remote monitoring is under $50. The bandwidth cost of transmitting that data at Telcare’s connectivity rates is less than $5 per month, so I think that the economic argument is challenging.

Dr. Javitt: An artificial pancreas is probably $500 to $1,000 of electronics, at the end of the day. The cost of adding remote monitoring is under $50. The bandwidth cost of transmitting that data at Telcare’s connectivity rates is less than $5 per month, so I think that the economic argument is challenging.

Dr. Javitt: [Remote monitoring] is today’s technology, and it’s easily achievable. If it only saves one life per 10,000, that’s probably all it needs to do.

Bryan Mazlish (New York City, NY): My wife and I have a remote-monitoring tool for our seven- year-old son. I think that we can all agree that there is a benefit to remote monitoring in general. With regard to the artificial pancreas, at the end of the day, if you are okay with open-loop therapy and that is the failsafe, I don’t see why you need remote monitoring specifically to monitor the artificial pancreas.

Dr. Steven Russell (Massachusetts General Hospital, Boston, MA): I think that we will probably move to automated monitoring. A system that sends alerts might someday be part of the business model: what you are actually paying for is the remote-monitoring service, and the bionic pancreas is sold for free…I am not sure what the right business model is, but I would not be comfortable without some kind of remote monitoring.

Dr. Kovatchev: Similar to Dr. Kowalski’s progression toward the artificial pancreas, I suggest that we view the current version of remote monitoring as a first step toward the final goal: remote diagnostics, vertical integration, and distributed computing.


Bruce Buckingham, MD (Stanford University, CA), Moshe Phillip, MD (Tel Aviv University, Petah Tikva, Israel)

The debate led by Drs. Bruce Buckingham and Moshe Phillip asked whether treat-to-range techniques (such as predictive low glucose suspend) worked better than full closed-loop control (either at day or at night). Both researchers had conducted closed-loop studies, and they unsurprisingly came out strongly in favor of the closed loop. They admitted that closed-loop control still has some safety issues to be mitigated, but they were clear that it gave superior results. As Dr. Phillip put it: “Some people say ‘perfection is the enemy of the good,’ but sometimes it’s okay to be the best.” In the discussion, Dr. Hovorka maintained that “the argument that treat-to-range is better overnight [than closed loop] doesn’t hold in any studies I have seen.”

  • Drs. Buckingham and Phillip considered four approaches to diabetes management– two during the night and two at daytime. Predictive low glucose suspend (PLGS) anticipates nocturnal hypoglycemia and avoids it by switching off insulin. Nocturnal closed-loop control completely manages insulin administration with no input from the patient during sleep. (The chief risk of nocturnal closed loop is that the sensor could fail or become impaired by drug interference.) Treat to range (TTR) during the day is similar to open loop, except that when the system detects hypoglycemia or hyperglycemia, it takes action to keep the patient in the safe range. A daytime closed-loop system would take total control of glucose levels during the day, without a pre-meal bolus.
  • Dr. Buckingham took the view that PLGS is highly effective - the sensor doesn’t trigger insulin dosing (so it’s safer), severe hypoglycemia is avoided, and data clearly that there is no increased risk of diabetic ketoacidosis (DKA). When comparing closed-loop control to TTR in the daytime, he took the view that TTR really just creates a buffer zone for inaccurate sensors – when sensors are more accurate, then the closed-loop system would do a better job. However, he acknowledged that many safety aspects still need mitigating, such as sensor failure, set failure, communication failure, and unrealistic insulin doses.
  • Dr. Phillip took the view that nocturnal closed loop gives many benefits (reduces variability, reduces mean glucose, improves time in range, reduces morning glucose, reduces patient mistakes, improves quality of life, decreases the burden of alarms). In short, it has all the benefits of PLGS. Dr. Phillip quipped, “Some people say ‘perfection is the enemy of the good’, but sometimes it’s OK to be the best.”Quotes from discussionDr. Kowalski: I used to think it would be hard to get approval for an overnight closed loop controller … but I have flipped my opinion. We are significantly reducing risk versus open loop.

Quotes from discussion

Dr. Kowalski: I used to think it would be hard to get approval for an overnight closed loop controller … but I have flipped my opinion. We are significantly reducing risk versus open loop.

Dr. Hovorka: Our experience is that closed loop works by reducing hypoglycemia risk. The argument that treat to range [meaning PLGS] is better overnight [than closed loop] doesn’t hold in any studies I have seen.

Dr. Phillip: Almost any controller does very well at night. But if someone takes a big bolus before they went to bed, then nobody’s controller can’t take the insulin away.

Dr. Russell: I think the thing you are looking for is glucagon.

Dr. Tom Peyser (Dexcom, San Diego, CA): We have a membrane [that reduces acetaminophen interference] that is being used in partnership with Edwards, and that will be part of a future product.

Dr. John Mastrototaro (Medtronic Diabetes, Northridge, CA): Our approach [to eliminate interference from acetaminophen] has been to look at an orthogonally redundant sensor. One sensor is a check for the other, and both don’t behave similarly in the presence of interference. Which sensor do you believe? We have some diagnostics, but you can always ask the person to double-check their blood glucose.


Steven Russell, MD, PhD (Massachusetts General Hospital, Boston, MA) and Rick Mauseth, MD (Benaroya Research Institute at Virginia Mason, Seattle, WA)

Drs. Steven Russell and Rick Mauseth provided short lists of closed-loop metrics that they believe should be standardized – there was a refreshing amount of overlap between their five-minute talks. In our view, there is clear need for this in the AP research field, so we’re glad to finally see some very tangible and visible discussion of it.

  • Dr. Russell emphasized that there is not a one-size fits all approach to standardization, but it would be useful to have some common metrics. He proposed a nice list of minimum standards for bionic pancreas study reporting: mean blood glucose and mean CGM glucose over the study period, time in the specific ranges of <70 mg/dl and 70-180 mg/dl, use of means (“we’re not treating median people”), carbs per meal, carb interventions (timing and size), exercise (type and intensity), insulin and glucagon dosing, when CGM calibrations occurred (what was the criteria for doing them?), accuracy of CGM (MARD) and reporting percentage, any open loop interventions that are done, any system down-time and the causes of that down time, and data excluded from analysis (was it pre-specified criteria?)
    • “There is no reason not to show subject level data from all of these experiments. You can learn a lot.” Dr. Russell enthusiastically called for reporting subject-level data, which he believes can be done in online supplements. The MGH/BU team always does this in their publication (one page per patient showing CGM, blood glucose, insulin data, glucagon data, meal information, and more). Dr. Russell’s team has gotten a lot of useful insights to improve their controller, and he believes publishing such granular data could help others too.
  • Dr. Rick Mauseth also discussed closed-loop metrics standardization, focusing on controllers and system-level performance. He believes a comparison of controller efficacy (e.g., AP@home’s CAT trial) is possible, though it’s highly dependent on study design. Additionally, since controllers evolve incrementally and quite quickly, it’s challenging to run head-to-head studies before the controllers have already moved to the next version. Dr. Mausethargued for comparison metrics on basic system performance (e.g., how much of the time did it work) and a focus on reliability, robustness, and safety. He noted that JDRF consortium members have drafted a white paper on this topic (Bequette, Doyle, Hovorka, Lum, Weinzimer, Zisser). In terms of system failure, he questioned how groups are defining it and for how long. Other key areas for standardized reporting include how a controller was initialized, when a missed reading or dose occurred and why, whether there was interference (cable loose vs. restart), and details on the frequency of user action (including calibration).

Quotes from Discussion

Dr. Steven Russell: JDRF has recently funded a project to develop a continuous insulin monitor. It will be measuring insulin in close to real time. We will be able to measure pharmacokinetics and how long until insulin levels in the interstitial fluid rise. That feedback can then be given to the closed loop controller.

Dr. Roy Beck: There’s an awful lot to learn on a subject level. I agree with what you said about median. But the same is true of the mean. You can lose a lot of the information when looking at the central tendency. In a lot of these cases, we’re interested in the extremes.

Dr. Roman Hovorka: I wanted to comment on the reporting a mean of population results. If I look at it from the outside, closed loop is another therapeutic intervention. Any other study reports population means. It’s compare a standard treatment in a population. The AP is nothing different than that. Immunosuppressive therapy treats an individual, just like an AP. But you always see population level mean plus errors.

Dr. Steven Russell: As we move to pharmacogenomics, there are drugs that have failed that will probably be resurrected. Something that worked in 20% of people and did not in 80% of the people is going to fail a phase 3 trial. That could still be a good drug.

Dr. Aaron Kowalski: It is astounding how far this field has come. This year is the tipping point. We’re going to have a tremendous amount of outpatient data for the next 12 months. It’s going to be transformative.

Symposium: Closing the Communication Loop – Technology Update in Pediatric Diabetes


Stephen W. Ponder, MD (Scott and White Healthcare, Temple, TX)

Dr. Stephen Ponder stressed the role of the patient within his or her own diabetes care, focusing on results with the Advanced Diabetes Management System (ADMS), a new technology that automates blood glucose monitoring data retrieval, analysis, and reporting. In the trial, children in his practice (age <12) were randomized to receive either standard care (n=24) or supplementation with the ADMS device (n=24) for one year. Patients with ADMS were allowed access to two features, with no further physician intervention: 1) A real-time alert sent out to a family member whenever a recent blood sugar was out of range and 2) a daily email of a day-over-day plot that displayed data from the last 21 days. At the end of the trial, patients using the device 1-3 times/week showed significantly greater declines in A1c (7.8% to 7.1%; p=0.01) versus patients using the device <1 time/week (8.0% to 7.8%) and controls (8.1% to 8.3%). Dr. Ponder suggested these results support the notion that anyone can be taught pattern management without the aid of a provider in the middle of the data stream. We are encouraged by the potential of this device and hope for more data from a wider range of individuals outside one practice; we also are interested to see what qualities define those patients that used the device more frequently.

  • Dr. Ponder stressed the role of the patient within his or her own diabetes care. With regard to the patient-provider relationship, he suggested the patient is the only person with full access to the details of their care, with the provider often making decisions based off incomplete data. Referencing a recent psychological study that indicated the average person makes 200-300 decisions per day about food alone, he posited that the patient’s numerous daily decisions about care likely play a strong role and asked how providers might empower those decisions.
  • The ADMS is a new technology that automates blood glucose monitoring data retrieval, analysis, and reporting, with the hopes of informing patient decision- making. Dr. Ponder emphasized the simplicity of the device, which only requires a single plugging into one’s blood glucose monitor; data is then transferred wirelessly to a server for collection and analysis.
  • Dr. Ponder spent the remainder of this talk discussing a study (Toscos et al., Diabetes Care 2012) evaluating the use of the ADMS in pediatric patients. In the trial, children in his practice (age <12) were randomized to receive either standard care (n=24) or supplementation with the ADMS device (n=24) for one year. Patients with ADMS were allowed access to two features: 1) A real-time alert sent out to a family member whenever a recent blood sugar was out of range and 2) a daily nighttime email of a day-over-day plot that displayed data from the last 21 days in a simple color-coded format to highlight values out of range. Importantly, following initial education in pattern management, families received no additional input or education from the provider and were left to use the data independently.
  • Results indicated improvements in both diabetes and psychosocial outcomes in patients demonstrating high frequency of usage of the ADMS. Patients naturally divided into two groups of varying frequency, with 13 using the device <1 time/week and 11 using the device 1-3 times/week. At the end of one year, patients using the device 1-3 times/week showed significantly greater declines in A1c (7.8% to 7.1%; p=0.01) versus patients using the device <1 time/week (8.0% to 7.8%) and controls (8.1% to 8.3%). Parents of more frequent users showed improvements on the Blood Glucose Monitoring Communication scale (a validated survey to gauge emotional response to BGM; lower score is better) as well (13.5 to 11.3 vs. 13.6 to 14.3 in less frequent users and 13.5 to 14.5 in controls; p=0.03), though there was no difference in the children’s scores on the survey. Finally, more frequent users showed improvements in the Diabetes Self-Management Profile (higher score better; 63.8 to 71.2 vs. 62.0 to 61.3 and 59.5 to 61.8; p=0.04), indicative of more rigorous diabetes self-management.

Questions and Answers

Q: Do you think there’s a possibility that comprehension, education, and confidence may have been driving the frequency of docking? You said the frequency was associated with change.

A: I think that’s a very valid point. We wanted consistency across teaching style so stayed in our own clinic and to avoid the challenges of adolescence, patients who were under 12. We eliminated patients with A1c over 12 or psychoaffective disorders. But you’re absolutely right; we can look at people not docking frequently and pull them in. I’m asking what can we do with the device itself and how to leverage the technology.

Q: I like the idea of letting patients take care of themselves, and we started a social network. Is there research on that?

A: We did a study in 2005 not published with 75 people. They could designate a loved one to receive data. We found significant improvements in measurements of control over six months. They were sending that data to someone socially they thought cared about them. So that social implication is important. If we can tap into that, it has tremendous power.

Q: Do you have any stories to tell about what actions they could take with the data?

A: All were taught to look for trends and patterns. It was up to them to see what they did with that information.


Joyce M. Lee, MD, MPH (University of Michigan, Ann Arbor, MI)

Dr. Joyce Lee (also known as @joyclee) discussed the use of social media by healthcare providers, with a focus on Twitter. She opened with a description of the various popular social media modalities, highlighting Twitter as a microblogging platform with a wide potential for providers. Following a review of the basics of Twitter (e.g., how to open an account, terminology definitions) and some precautions (looking to preserve patient confidentiality, she referenced the Mayo Clinic’s 12-word social media policy: “Don’t lie, Don’t pry, Don’t cheat, Can’t delete, Don’t steal, Don’t reveal”), Dr. Lee detailed the many potential benefits, including: using the modality as a way to inform research (she noted that personal connections made over Twitter had previously provided her with information to aid in her research), to translate one’s results to a wider population (many details important to patients often remain hidden away in academic journals), and to enhance one’s reputation as a scholar (she noted that successful networking can often lead to new opportunities in one’s career). Importantly, she also suggested the medium as a way to stay connected with the patient community and gain insight into the average patient’s daily life outside of the clinic.


Michael Tansey, MD (University of Iowa, Iowa City, IA)

Dr. Michael Tansey explored CGM use in pediatric populations. Setting the stage for his presentation, Dr. Tansey reviewed findings from the landmark JDRF-CGM trial to demonstrate that the benefits of CGM were closely related to frequency of use across all ages; as a reminder, the study included patients with type 1 diabetes ≥ eight years of age. He next explored CGM use in younger children (ages four to 10 years) in his discussion of the DirecNet CGM efficacy and safety study (Mauras et al., Diabetes Care 2012). He noted that parents of children with type 1 diabetes on CGM were highly satisfied with the technology, despite no significant improvement in A1c at six months. Dr. Tansey then provided myriad cuts of data from the T1D Exchange clinical registry according to patient age. Interestingly, of the patients using CGM at the time of enrollment into the registry, adults (age ≥26 years) were more likely than any other age group to have discontinued CGM use one year later. Dr. Tansey underscored that CGM discontinuation was a challenging topic to study and that further research was needed to understand the multiple factors at play.

Questions and Answers

Q: My impression of the JDRF study and the DirecNet study was that the overall satisfaction was very high yet use was low. How does one understand that paradox?

A: It speaks to the heart of this matter. I don’t have a real clear answer. There is not always a direct correlation between the degree of benefit and degree of use. There may be a disconnect there.

Q: I don't have many patients on CGM, but I do have patients who love the device because they know every time they want to use it they can.

A: An additional comment. I think more education is going to be needed about the devices so people can understand what they are getting into.

Q: Do you have any thoughts on what drives the discontinuation of CGM? There seems to be a conflict between the two studies. The JDRF study indicated that CGM use did not improve A1c and the T1D exchange indicated there was a significant improvement in A1c.

A: First, as to the reason why people might discontinue use, I think the reasons will be varied. There are barriers to use: alarms, some patients were bothered by pain at insertion. More data is needed. To answer your second question, again in the JDRF study there was no significant difference in patients aged 9-15 and 15-24 years old, but look at use. There was a significant drop in those using it ≥6 days per week. Remember the T1D data was not a randomized data set.

Dr. David Price (Dexcom, San Diego, CA): I have a comment and a question. First, a comment: the discontinuation rate in the T1D Exchange was different between the sensors being used. There’s another poster, 886-P, that went into discontinuation rates and the difference between sensors. Dr. William Polonsky did a survey in adults and found that greatest reason for discontinuation and the greatest benefit was related to trust in the data – people that trusted the data used it and did not discontinue it. Do you think that’s true in kids?

A: Anecdotally, the earlier CGM devices, which some of this data does cover, were not as good. When you look at some of the data on testing frequency, subjects who are testing less are inherently trusting more.

Q: I wonder about CGM marketing strategy. Is there a role for short-term CGM use? For example, just during sick days.

A: I don’t think that has been addressed very clearly. I think there could be potential for specific situational, short-term use.

Dr. Stuart Weinzimer (Yale University, New Haven, CT): There is something I don’t think the JDRF study captured. Although people saw a benefit, many of our children don’t want to be thinking about diabetes more than they have to. There are a small percentage of people who want to think about diabetes every minute, every day but the rest of us may not want to and we didn’t really capture that in our data.


Sarah Jaser, PhD (Vanderbilt University, Nashville, TN)

Dr. Sarah Jaser highlighted the centrality of communication in medical care, particularly in pediatric diabetes. Discussing parent-child communication first, she noted that family functioning and communication are strongly linked to both glycemic control and psychosocial functioning of children with diabetes. In particular, data from studies have demonstrated improved quality of life, less depression, and improved glycemic control when parents utilize positive parenting behaviors such as child-centered communication (i.e., parent displays an awareness of a child’s needs, moods, interests, and capabilities) and positive reinforcements. Similarly, studies have found that the quality of provider- patient communication has a significant impact on patient adherence. In one study, the odds of patient adherence was 2.16 times greater when the physician was rated as a good communicator. Dr. Jaser identified time, culture, health numeracy, and stress as important factors that affect communication. With regards to interventions, she noted that several interventions have proven effective at improving communication within families (diabetes behavioral system therapy, WE-CAN problem solving interventions, coping skills training) and between patients and providers (training that focuses on collaborative communication, empathy, and improved attitudes toward psychosocial issues). In closing, Dr. Jaser expressed optimism for the use of technology to improve communication in pediatric diabetes, and she pointed to the importance of continued research on current patient uses of technology as well as ways in which to make technology more personal (more emotional, motivational) to deliver effective technology solutions.


Oral Sessions: On the Horizon – Selective Sodium Glucose Co-Transporter Inhibition


David Powell, MD (Lexicon Pharmaceuticals, The Woodlands, TX)

Dr. David Powell presented the results from a series of mouse studies characterizing the effects of the SGLT-1 inhibitor LX2761. In these mouse studies, Lexicon demonstrated: 1) LX2761 has poor systemic exposure, and causes little, if any, increase in urinary glucose excretion (as assessed by oral gavage to adult C57 mice); 2) LX2761 delays intestinal glucose absorption and increases intestinal GLP-1 release; 3) LX2761 acts synergistically with a DPP-4 inhibitor (sitagliptin) to increase postprandial levels of GLP-1; 4) LX2761 decreases postprandial excursions 15 hours after delivery to healthy mice fed ad libitum; and 5) LX2761 improves glycemic control in the KKAy mouse model of type 2 diabetes and in adult male C57 mice with STZ-induced diabetes. In conclusion, Dr. Powell stated that selective inhibition of SGLT-1 can improve glycemic control in mice, and as such, further studies are warranted to test whether SGLT-1 inhibition can improve glycemic control in people with diabetes.

Questions and Answers

Q: How do you speculate this drug would compare to alpha-glucosidase inhibitors?

A: We’re averaging once a day, and don’t have to give the drug with meals. I think with those drugs you have to give them with meals. Those don’t block absorption of glucose, but rather, disaccharides. The gut is fairly good at absorbing glucose fermented to short-chain fatty acids, but complex carb metabolites are produced with alpha-glucosidase inhibitors, so I wonder whether that is associated with GI side effects.

Q: Do you expect to dose this drug once daily in humans?

A: Based on what we’re seeing in mice, once-daily dosing improved glycemic control. That’s what we’re hoping for.

Dr. Ralph DeFronzo (University of Texas Health Science Center, San Antonio, TX): This is a very important study. Although people have shied away from combining SGLT-1 and SGLT-2, I actually strongly advocated that pharmaceutical companies think about this. As long as you do not cause GI symptoms, this could be an added benefit. Having said that, you didn’t tell us if the rats had GI side effects.

A: We got interested in this because LX4211 inhibits SGLT-1, yet there were no GI side effects seen relative to placebo. So, it made us realize there’s a therapeutic window. That’s why LX2761 was developed. Are there more side effects when you target the gut? The bottom line is, yes, if you give enough, you will cause loose stools. It’s dependent on the amount. We do see a therapeutic window of maybe ten fold between the dose that gives a 50% decrease in glucose excursion and the dose that gives you loose stool.


Pablo Lapuerta, MD (Lexicon Pharmaceuticals, The Woodlands, TX)

In this 12-week dose-ranging study (n=299), patients with inadequately controlled type 2 diabetes taking metformin were assigned to receive placebo or one of four doses of LX4211 – 75 mg QD, 200 mg QD, 200 mg BID, or 400 mg QD. Patients in the study were 18-75 years of age, had BMI ≤45 kg/m2, and A1c between 7.0-10.5%; at baseline, patients were on average 56 years old, with A1c of 8.1%, BMI of 33 kg/m2, and blood pressure of 125/79 mmHg. Both patients with and without hypertension were allowed in the study, and there were no restrictions on antihypertensive medication use. LX4211 reduced systolic blood pressure (SBP) in a dose-dependent manner (estimating from the chart presented, the 75 mg QD, 200 mg QD, 200 mg BID, and 400 mg QD doses reduced SBP approximately 0.1, 4.0, 4.5, and 6.0 mmHg, respectively, while SBP lowered approximately 0.3 mmHg with placebo). For the 400 mg dose, patients with elevated SBP (≥130 mmHg) experienced an average reduction of 14 mmHg versus placebo (p=0.002), while those with normal SBP (<130 mmHg) experienced minimal change in SBP – Dr. Pablo Lapuerta noted that these decreases were consistent with approved antihypertensive therapies. In contrast, there were no dose-dependent changes in diastolic blood pressure (DBP). For the trial’s A1c- lowering efficacy results, please see our AHA 2012 coverage at

  • Dr. Lapuerta noted several strengths and limitations of the study. In terms of strengths, the study had precise blood pressure data, demonstrated a clear dose response, had clear separation between treatment and placebo, used trough measures of blood pressure, and demonstrated systolic-blood-pressure-lowering efficacy consistent with that of approved antihypertensive agents. As for limitations, the study had a limited sample size, many patients already had good blood pressure control at baseline, the study duration was short, there were no blood pressure measures taken at the peak, and GLP-1 was not measured.


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

Dr. Muhammad Abdul-Ghani presented results from a study examining the effects lowering plasma glucose concentrations with dapagliflozin has on insulin sensitivity and insulin secretion in patients with type 2 diabetes. In the study, patients (n=18; baseline BMI 31.1 kg/m2, baseline A1c 8.2%) were randomized to dapagliflozin or placebo in a 2:1 fashion. Five days and three days prior to randomization (Days -5 and -3), respectively, subjects received a 75-gram OGTT and an insulin clamp 3H-glucose infusion. Following randomization (Day 0), subjects were admitted to the clinical research center (on Day 1) for measurement of basal hepatic glucose production with 3H-glucose on Days 1-3. Subjects were administered dapagliflozin from Day 2 through Day 15 of the study, and were given a repeat OGTT on Day 14 and insulin clamp 3H-glucose infusion on Day 15. In the study, lowering the plasma glucose concentration with dapagliflozin improved insulin-stimulated tissue glucose uptake (insulin sensitivity) and glucose-stimulated insulin secretion. However, the glucosuria produced by the inhibition of SGLT-2 stimulated a compensatory increase in (hepatic) glucose production, which attenuated the clinical efficacy of dapagliflozin.

Questions and Answers

Q: What do you suppose the signal for glucagon secretion in your study was?

A: We don’t know. We’re searching for that now.

Q: Did you do any follow-up studies where you gave a DPP-4 inhibitor?

A: We don’t have results yet, but that’s the obvious thing to look into.

Q: Are there other drug candidates you may consider combining with SGLT-2 to knock down hepatic glucose production?

A: DPP-4 inhibitors are the obvious option, but I am a little bit skeptical about their efficacy. GLP-1 agonists may be more efficacious, but I am still skeptical. Maybe glucagon antagonists, but I’m not sure if they’d be good for clinical use.

Q: What about metformin?

A: Subjects were already receiving metformin. Also, metformin doesn’t affect glucagon. This study exposes the interaction between the liver and kidney, and their crosstalk in glucose homeostasis. I personally think they are related through the central nervous system. When we are giving dapagliflozin, we are forcing the kidney to excrete glucose, and producing a difference in glucose between the renal artery and the renal vein. It could possibly be that the brain is detecting the difference, and acting directly on the liver to compensate. For example, someone with normal glucose tolerance would be at the immediate risk of hypoglycemia. The brain has to react in order to prevent hypoglycemia. This compensatory response is problematic in people with type 2 diabetes, as they are already hyperglycemic.


Brian Zambrowicz, PhD (Lexicon Pharmaceuticals, The Woodlands, TX)

In this 12-week dose-ranging study (n=299), patients with inadequately controlled type 2 diabetes taking metformin were assigned to receive placebo or one of four doses of LX4211 – 75 mg QD, 200 mg QD, 200 mg BID, or 400 mg QD. Patients in the study were 18-75 years of age, had BMI ≤45 kg/m2, and A1c between 7.0-10.5%; at baseline, patients were on average 56 years old, with A1c of 8.1%, BMI of 33 kg/m2, and blood pressure of 125/79 mmHg. In the subgroup of patients with BMI ≥30 kg/m2 at baseline, patients in the 75 mg QD, 200 mg QD, 200 mg QID, and 400 mg QD LX4211 lost an average 0.9 kg (2.0 lb), 1.8 kg (4.1 lbs), 2.9 kg (6.4 lbs), and 2.0 kg (4.3 lbs), while patients on placebo lost an average 0.4 kg (1.0 lb) (the 200 mg QD, 200 mg BID, and 400 mg QD were statistically significant versus placebo [p<0.001]). In the subgroup of patients with elevated triglycerides (200-500 mg/dl) at baseline, LX4211 treatment resulted in significant reductions from baseline in the 75 mg QD, 200 mg QD, and 400 mg QD arms (67.6 mg/dl, 49.0 mg/dl, and 81.8 mg/dl, respectively; p<0.05). Side effects appeared balanced with placebo; there were no major increases in GI side effects such as diarrhea, nausea, vomiting, and constipation beyond placebo. For the trial’s A1c-lowering efficacy results, please see our AHA coverage at

Questions and Answers

Q: In your study, there were relatively fewer mycotic infections with your dual SGLT- 1/SGLT-2 inhibitor than with SGLT-2 alone. Can you explain the reason behind that?

A: One of the things I did mention was that LX4211 had relatively low urinary glucose excretion. I think there is a mechanistic reason for that. The amount of glucose you’re going to spill is dependent on how well you inhibit SGLT-2, but you also have to look at how much blood glucose can be filtered. SGLT-1 addresses mainly postprandial glucose. If you lower postprandial glucose all meals of the day, there is less glucose to filter in the blood. The maximum glucose excretion we’ve seen in trials is 45 grams in a day with LX4211, whereas [other SGLT-2 inhibitors had maximum glucose excretion of 60-70 grams] over 24 hours.

Q: Can you elaborate on what happened to LDL? Triglycerides went down, but what happened to LDL, and how does it compare to SGLT-2 inhibitors?

A: There was no significant increase from baseline; however, I would say there’s probably a trend there. The increase is quite small. It may become significant in larger studies. I would say that the effect is clearly SGLT-2 dependent. Though we don’t understand why, we think it may be related to the level of urinary glucose excretion as well.

Q: Did you look at leptin levels in the study?

A: Not in this study. But, we are planning to look at that. There’s a cascade, because short-chain fatty acids are absorbed fermentation of glucose in the colon, and when they reach the bloodstream they can trigger the release of leptin.


Katja Rohwedder, MD (AstraZeneca, Cambridge, UK)

Dr. Katja Rohwedder discussed a post-hoc analysis of a 52-week non-inferiority trial comparing dapagliflozin (2.5-10 mg/day) to glipizide (5-20 mg/day) as adjuncts to metformin (1,500 mg/day) in ~800 type 2 patients (at baseline, mean age of 58-59 years, diabetes duration of 6-7 years, weight of 88 kg [194 lbs], and A1c of 7.7%). At 52 weeks, 78% of participants remained in the study and drop-out rates were comparable between the two treatment groups. The two drugs provided the same A1c reduction (0.52%); furthermore, a similar percentage of participants in each arm experienced an improvement in A1c (75% with dapagliflozin vs. 74% with glipizide). Not surprisingly, more patients on dapagliflozin exhibited weight loss (83%) than those on glipizide (27%). An A1c reduction coupled with weight loss was observed in 67% of the dapagliflozin group vs. 21% of the glipizide group (difference of 46 percentage points; 95% CI: 39-52); furthermore, 31% of those on dapagliflozin achieved an A1c reduction0.5% with a weight loss3 kg (7 lbs), compared to only 4% of those on glipizide (difference of 27 percentage points; 95% CI: 22-32). While response to drug therapy did not differ by baseline weight, disease duration, or gender, the patients who achieved A1c reductions0.5% had higher A1c levels at baseline (this is consistent with previous studies). Regarding safety data, dapagliflozin was associated with less hypoglycemia compared to glipizide; however, both urinary tract infections and genital infections were more commonly observed with dapagliflozin, though Dr. Rohwedder commented that these events rarely led to study discontinuation.

Efficacy Data




A1c Reduction

Weight Reduction

Both A1c & Weight Reduction

A1c Reduction >0.5% & Weight Reduction >3 kg (7 lbs)











Safety Data


No Hypoglycemia

Genital Infections

Urinary Tract Infections










Questions and Answers

All questions were asked by the session moderator, Dr. Ralph DeFronzo.

Q: Is it time to get rid of SFUs and go to drugs that really work without causing safety issues?

A: I hope so.

Q: Did you look at glucose excretion in the urine and was it related to weight loss in either group?

A: No, we haven’t looked at that specific analysis.

Q: Did you measure insulin levels, since insulin is related to weight gain and hypoglycemia?

A: We have the information on fasting insulin levels and we have done OGTTs in a subgroup of patients, but we haven’t looked at the specific correlation. It’s a good idea.

Q: What was the definition of hypoglycemia and severe hypoglycemia?

A: Major hypoglycemia episodes were defined as less than 3 mmol/l (54 mg/dl) or if the investigator saw symptoms. It was only reported in the glipizide arm, in three patients. In general, every blood glucose measurement below 3.5 mmol (63 mg/dl) was considered hypoglycemia. Investigators could also report cases of hypoglycemia if they saw symptoms.

Comment: I would say this is a pretty clear-cut distinction between oral agents in terms of weight gain, an important side effect that we’re all concerned with in diabetes.


Fernando Lavalle González, MD (Universidad Autonoma de Nuevo Leon, Nuevo Leon, Mexico)

Dr. Fernando Lavalle González presented data showing that canagliflozin provided greater reductions in A1c and in weight compared to sitagliptin. The 52-week study randomized 1,294 type 2 patients to canagliflozin 300 mg, canagliflozin 100 mg, sitagliptin 100 mg, or placebo (2:2:2:1 ratio). After 26 weeks, those assigned to placebo were switched to sitagliptin 100 mg (PBO/sita group). The modified intent-to-treat analysis showed that at 52 weeks, canagliflozin 300 mg provided a larger A1c reduction (-88%) than canagliflozin 100 mg and sitagliptin (-0.73% for both). Greater improvements in fasting plasma glucose were also observed with canagliflozin 300 mg (-35 mg/dl) and 100 mg (-26 mg/dl) compared to sitagliptin (-18 mg/dl; p<0.001 for both comparisons). As expected, the weight loss observed with canagliflozin 300 mg (4.2%; 3.7 kg [8.1 lbs]) and 100 mg (3.8%; 3.3 kg [7.3 lbs]) was significantly more than that observed with sitagliptin (1.3%; 1.2 kg [2.6 lbs]; p<0.001 for both comparisons). Canagliflozin was associated with reductions in blood pressure, as well as elevations in LDL and HDL cholesterol. On the safety front, canagliflozin was associated with a higher rate of genetic mycotic infections compared to sitagliptin and PBO/sita, as well as a higher rate of osmotic diuresis, though Dr. González noted that these events led to few study discontinuations. Interestingly, the incidence of documented hypoglycemia was higher with both doses of canagliflozin (6.8%) compared to sitagliptin (4.1%) and PBO/sita (2.7%).

  • Canagliflozin was associated with reductions in blood pressure, as well as elevations in HDL and LDL cholesterol (data in table below). Dr. González mentioned during Q&A that the rise in HDL-C was unexpected.



Comparison to
(percentage points)


Comparison to
(percentage points)

CANA 300 mg

8.8% (4.4 mg/dl)

(95% CI: -1.8, 7.4)

13.2% (5.5 mg/dl)

(95% CI: 4.4, 10.0)

CANA 100 mg

7.7% (4.3 mg/dl)

(95% CI: -2.8, 6.2)

11.2% (4.5 mg/dl)

(95% CI: 2.5, 7.9)

SITA 100 mg

6% (3.1 mg/dl)


6% (2.4 mg/dl)



Δ Systolic Blood Pressure

Comparison to

Diastolic Blood

Comparison to

CANA 300 mg

-4.7 mmHg

-4.0 mmHg


-0.3 mmHg


CANA 100 mg

-3.5 mmHg

-2.9 mmHg


-1.8 mmHg


SITA 100 mg

-0.7 mmHg


-1.8 mmHg


  • While the rates of adverse events (AE) were comparable between the groups, canagliflozin was associated with higher rates of genital infections and hypoglycemia:


SITA 100 mg

CANA 100 mg

CANA 300 mg

Any adverse event





Serious adverse event





Urinary tract infection





Genital infection (M)





Genital infection (F)





Osmotic diuresis-related adverse events










Severe hypoglycemia





Questions and Answers

Q: Can you comment on the drop in blood pressure? It looks to me like the drop in blood pressure comes fairly quickly and the drop in weight comes later. Maybe the weight plays some role in sustaining the drop in blood pressure. Can you comment on the early blood pressure drop?

A: In other studies on blood pressure, half of the drop in blood pressure can be related to losing weight. The other half is a direct effect of ACE inhibition and other mechanisms of the drug.

Comment: In the first three to four days, you get a negative salt and water balance. And this may be playing an important role in the initial drop in blood pressure.

Q: It was a nice surprise for me to see the increase in HDL cholesterol. Do you have any idea why this elevation occurred?

A: It’s an observation seen during the study. There are some comments about this in people who use diuretics. There are some comments from nephrologists saying that this kind of HDL and LDL pattern is seen in people using diuretics. This is an observation and you can see that there is not a relation to the mechanism of action of the drugs.

Q: Have you found an explanation for why the higher canagliflozin dose had less of an effect than the lower dose?

A: No, not really.

Q: Are there any particular side effects of canagliflozin that you found to be part distributing?

A: No, you usually see genital mycotic infections, which are treated rapidly and resolve in patients. We didn’t see any safety concern

Comment: It’s very commonly stated that this class is associated with an increase in urinary tract infections. If you look at the data rather than what’s said, this opinion doesn’t hold up. And you saw this today. At the lower dose, there was a little rise in UTIs, but it was not statistically significant. At the higher dose, there was no increase. I bet that if you combine the two doses, you wont’ see a statistically significant increase.

Q: I was surprised by the LDL cholesterol levels with the sitagliptin group.

A: This was unexpected but you can see that it’s a small rise, just 6%. This is what we obtained in the study.

Comment: Across studies with canagliflozin, the rise in LDL with canagliflozin 100 mg is 4 mg/dl. It’s 8 mg/dl with canagliflozin 300 mg. If you’re truly treating you patient to goal and their LDL level is 70 mg/dl, the worst case scenario is that you’re going from 70 to 78 mg/dl and most HCPs wouldn’t even increase the dose of statin.

A: Yes, the increase is very small. It’s no more than four to six mg/dl.

Symposium: Non-Glycemic Effects of Incretin-Based Therapy – Glucagon-Like Peptide-1 (GLP-1) and Dipeptidyl Peptidase-4 (DPP-4) (Supported by Boehringer Ingelheim and Eli Lilly)


Vanita Aroda, MD (MedStar Health Research Institute, Hyattsville, MD)

Upwards of 1,000 people flocked to hear Dr. Vanita Aroda present on incretin safety. Dr. Aroda attended the June 5-6 NIDDK/NCI workshop on pancreatitis, diabetes, and pancreatic cancer, and her presentation largely recapitulated highlights from the discussion that took place there (for our coverage of the meeting, please see our reports at and The conclusions she drew, in her fast-paced and well- organized presentation, resonated largely with prevailing sentiments on the subject: 1) potential mechanisms have been identified in animal models to suggest a potential pancreatitis risk; in her view, the real debate is over which of these models is relevant and representative since different models have produced differing results; 2) current clinical evidence is insufficient to support altering the risk/benefit profile for incretin-based therapies; 3) recent studies (e.g., Singh et al., JAMA Int Med 2013 and Butler et al., Diabetes 2013) have not prompted substantial changes in clinical recommendations; and 4) there is a great need to pool together the appropriate expertise and data based on rigorous methodologies to address these questions.

  • Dr. Aroda reviewed the many factors that complicate the investigations into pancreatitis risk: type 2 diabetes increases risk of pancreatitis and pancreatic cancer by 82% (Huxley et al., British Journal of Cancer 2005). Additionally, there is the chicken and the egg problem of reverse causality – individuals recently diagnosed with diabetes (<4 years) have a 50% greater risk of pancreatic cancer compared to those with longer diabetes duration (odds ratio of2.1 vs. 1.5; Huxley et al., British Journal of Cancer 2005).
  • Mechanistically, animal models have provided conflicting results on the effects of the exocrine pancreas. Dr. Aroda emphasized that the real question is discerning which models were appropriate and representative. Liraglutide did not induce pancreatitis in mice, rats, or monkeys at exposure levels greater than 60 times the levels used in humans (Nyborg et al., Diabetes 2012). Meanwhile, in the Pdx-1 Kras mouse (a model primed to develop chronic pancreatitis and pancreatic cancer), 12 weeks of exendin-4 treatment produced expansion of pancreatic duct glands; additionally, premalignant pancreatic intraepithelial lesions (PanINs) were identified in these animals. The FDA’s re-examination of toxicology and carcinogenicity studies has not provided any additional clarity.
  • Recent clinical evidence of elevated pancreatitis risk for incretin-based therapies comes from two largely flawed studies. Dr. Aroda relayed criticisms of Dr. Butler’s “cadaver study” (Diabetes 2013) and Dr. Singh’s retrospective insurance claims cohort analysis (JAMA Int Med 2013) that were discussed at the NIH pancreatitis meeting. The three groups from which Dr. Butler collected pancreata (nondiabetic, type 2 diabetes + incretin therapy, and type 2 diabetes without incretin therapy) were very small and poorly matched for background treatment, diabetes duration, age, gender, and BMI. Dr. Aroda referenced Dr. Steven Kahn’s commentary stating that the study also did not control for the effects of prolonged life support. In the Singh et al., study, the treatment group had higher background rates of risk factors for pancreatitis (e.g., obesity, alcohol use, hypertriglyceridemia, tobacco abuse, etc.). She reviewed methodological limitations of observational studies, including inability to control for covariates/confounders or a number of biases (e.g., reporting bias, notoriety bias, channeling bias [preferential prescribing to specific patient populations], selection bias, and reverse causation).
  • The NIH workshop also discussed the FDA’s Adverse Events Reporting System (AERS) database, concluding that additional data mining of AERS is unlikely to shed more light on these safety signals. Given the nature of the voluntary, spontaneous reporting, these data can only be hypothesis generating rather than hypothesis confirming.
  • So far, randomized controlled trials (RCTs) of incretin-based therapies have not detected a pancreatitis signal. For liraglutide, Dr. Aroda stated that the rate of pancreatitis has been 1.8 cases/1,000 patient-years of exposure, which is comparable to the background rate in diabetes. Three cases of pancreatic cancer have been reported on liraglutide – one in a patient treated on liraglutide for 152 days, one in a patient treated for seven days and was then diagnosed at stage 4 (suggesting it was not related to the seven days of liraglutide treatment); and one was reported prior to randomization. Similarly, she stated that no significant difference has been observed between exenatide and control groups in RCTs for exenatide. In RCTs for sitagliptin, the rate of pancreatitis was found to be 0.05 events/100 patient-years and 0.06 events/100 patient- years in the sitagliptin and comparator groups, respectively.
  • Looking forward, Dr. Aroda expressed optimism that the EMA’s Safety Evaluation of Adverse Reactions in Diabetes (SAFEGUARD) to assess the CV, cerebrovascular, renal, and pancreatic safety of currently marketed non-insulin glucose lowering agents will provide better quality clinical data – it will provide up to 240 million patient years of exposure.
  • During this presentation, Dr. Aroda also briefly addressed hypoglycemia, CV safety, and thyroid concerns for incretin-based therapies. As we have heard before, she stated that thyroid safety concerns stem from rodent models that do not match humans’ thyroid c-cell response to GLP-1 receptor agonism.

Questions and Answers

Q: That was a beautiful description done in a scholarly way. However if tomorrow morning you have a patient in front of you, and the patient is currently on an incretin and says, Doctor, I have heard a lot of things on television. What is your advice going to be with regard to that patient?

A: I guess I would flip that question to the audience and ask how many would say to stop the drug?

[No one raises hand]

A: How many would try to educate the patient on balancing risk and continue? [Scattered hands go up]

A: I am overwhelmingly surrounded by scholars much more scholarly than I. I think we need to spend

more time with patients educating them on what the comparative benefits and risks are.

Q: I agree with that answer


Q: Can you speak about levels of GLP-1 induced by surgery?

A: GLP-1 levels increase after bariatric surgery, and we have not seen an increase in pancreatic cancer. Obesity surgery is an area where you see decrease in these cancers.

Q: We can capture numbers of acute pancreatitis. My bigger question is, what about numbers of people with asymptomatic pancreatitis that we won’t know about for a long time? Studies may not show us that we have increased risk of pancreatic cancer until we have a whole lot of people already at greater risk. That’s my concern with short-term risk.

A: Do you mean chronic pancreatitis?

Q: Yes.

A: Some have asked whether it is worth it to look at enzyme fluctuations. There hasn’t been good correlation. All studies have been monitored by Data Safety Monitoring Boards, so if there were signals we would be alerted.

Symposium: Update on New Insulin Preparations for the Management of Diabetes


Mary Korytkowski, MD (University of Pittsburgh, Pittsburgh, PA)

After providing background information on U-500 insulin, Dr. Mary Korytkowski reviewed the current guidelines for its use and discussed its use in clinical practice, then briefly touched on concentrated insulins on the horizon (U-200 insulin degludec and U-300 insulin glargine) and how they will be incorporated into clinical practice. Dr. Korytkowski explained that U-500 is currently used alone, or in combination with long-acting, intermediate-acting, or rapid-acting analogs. Given the 12-16 hour duration of action of U-500, the introduction of truly long-acting concentrated insulin formulations such as U-200 or U-300 may restrict U-500 to use as a pre-meal insulin in the future. Dr. Korytkowski noted that because concentrated insulin formulations have different pharmacokinetics and pharmacodynamics versus U-100 insulin, adjustments in insulin doses are required when changing patients from U-100 to concentrated insulin. Dr. Korytkowski commented that the use of concentrated insulin formulations is likely to continue to increase in the future, given the increasing prevalence and severity of obesity and insulin resistance.

  • Dr. Korytkowski briefly discussed U-200 insulin degludec and U-300 insulin glargine, noting that they provide similar glycemic control as U-100 insulin glargine, and have low risk of hypoglycemia. In the BEGIN LOW VOLUME trial in insulin- naïve patients with type 2 diabetes, U-200 insulin degludec improved glycemic control similar toinsulin glargine, with a low risk of hypoglycemia (Gough et al., Diabetes Care 2013). In a PK/PD study of U-300 insulin glargine versus U-100 insulin glargine in patients with type 1 diabetes, the profile of U-300 was much flatter than U-100 (Tillner et al., ADA 2012). In the EDITION I trial, U-300 insulin glargine brought about similar changes in A1c compared to U-100 insulin glargine, but with a slightly lower incidence of hypoglycemia (Riddle et al., ADA 2013).

Questions and Answers

Q: The U-200 formulation of insulin degludec has the exact same PK profile as the U-100 formulation of insulin glargine, so this is the exception to the rule. Otherwise, I fully agree that highly concentrated insulin [has different PK compared to U-100].

A: That’s a good point, thank you. In the study in Diabetes Care, in the supplemental materials, the dosing of U-100 insulin glargine and U-200 insulin degludec were essentially identical.

Q: I presented a poster here of U-500 insulin in 15 patients who had their glucose tracked using continuous glucose monitoring before starting and six months later. In the CGM tracings, U-500 was clearly much better as a basal insulin, and not much for reducing postprandial glucose. Are there any studies utilizing GLP-1 analogs in combination with U- 500?

A: I’m sorry to have missed your poster, I’ll have to come by and see it. There is one case report on using U-500 in combination with liraglutide. In this case, U-500 was used more as the basal insulin, and liraglutide was used to control postprandial glucose. There were significant reductions in A1c in this one case report, but it’s a proof-of-concept idea. This person lost weight, and the dose of insulin actually decreased. There could be some promise there using the two together.


Thomas Donner, MD (Johns Hopkins University, Baltimore, MD)

Dr. Thomas Donner expressed optimism that ultra-long-acting and ultra-rapid-acting insulins in development could improve upon current insulin formulations. Specifically, he noted that there is evidence that ultra-long-acting basal insulins reduce nocturnal hypoglycemia and have less weight gain (or even can cause weight loss) compared to insulin glargine. Meanwhile, ultra-rapid-acting insulins could be more effective in reducing postprandial hyperglycemia than current rapid-acting analogs. Nonetheless, Dr. Donner noted that long-term studies are needed to confirm the efficacy and safety of these new candidates. During his presentation, he covered several specific ultra-long-acting insulins (insulin degludec, LY2605541) and ultra-rapid-acting insulins (BIOD-123, rapid-acting analogs plus hyaluronidase, and FIAsp).

  • Insulin degludec: Insulin degludec forms soluble multihexamers after subcutaneous injection, allowing for the gradual release of insulin monomers into circulation. It has a 25-hour half life, a duration of action of over 42 hours, and similar A1c-lowering efficacy when dosed either at a fixed time of day, or at intervals of 8-40 hours apart (Meneghini et al., Diabetes Care 2013). Insulin degludec’s profile appears flatter than current basal insulins. In a one-year, randomized, treat-to- target study in insulin-naïve patients with type 2 diabetes comparing insulin degludec with insulin glargine (BEGIN Once Long), the two insulins provided nearly identical glycemic control, but insulin degludec had a 36% lower incidence of nocturnal hypoglycemia (p=0.04) (Zinman et al., Diabetes Care 2012). Two-year data from the BEGIN Basal-Bolus trial for patients with type 1 diabetes showed a 25% lower incidence of nocturnal hypoglycemia with insulin degludec versusinsulin glargine (n<0.05), with insulin degludec bringing about similar glycemic control to insulin glargine, but with reduced insulin requirements (Bode et al., Diabetic Med 2013). Dr. Donner reviewed insulin degludec’s regulatory status in the US, noting that the FDA requested additional cardiovascular data from a dedicated cardiovascular outcomes trial prior to approval.
  • LY2605541: LY2605541 is insulin lispro, modified with a 20-kDA polyethylene glycol moiety. Its larger size delays absorption and slows clearance. In a dog model, LY2605541 displayed preferential hepatic uptake and greater lipolysis, suggesting potential for less lipogenesis, increased oxidation, and weight loss as opposed to gain. In a 12-week study in patients with type 2 diabetes, LY2605541 brought about similar effects on fasting glucose and A1c versus insulin glargine, but with less daytime glucose variability, significantly less nocturnal hypoglycemia (48% less), and weight loss as opposed to weight gain (Bergenstal et al., Diabetes Care 2012). LY2605541 increased triglycerides relative to insulin glargine, and was also associated with small increases in ALT and AST. In an eight-week crossover study in patients with type 1 diabetes of LY2605541 versus insulin glargine, LY2605541 decreased daytime glucose levels by approximately 10 mg/dl, reduced mealtime insulin dosing by 17%, had less daytime glucose variability, and conferred weight loss (Rosenstock et al., Diabetes Care 2013). Dr. Donner noted that both studies had two subjects with three-fold elevations in liver enzymes occurring four weeks after study end. In addition, Dr. Donner commented LY2605541 needs to be explored longer with regards to cardiovascular safety.
  • BIOD-123: BIOD-123 consists of insulin lispro with citrate and calcium EDTA; the chelating effects of the calcium EDTA leads to rapid dissociation of insulin hexamers, and inhibition of insulin monomer/dimer reassociation. Compared to insulin lispro alone, BIOD-123 has a much earlier peak action, and clears out more rapidly. A phase 2 study comparing BIOD-123 versus insulin lispro is expected to complete in 3Q13.
  • Hyaluronidase (PH20): Hyaluronidase has been shown to increase the dispersion and absorption of subcutaneously administered drugs, with no increased injection site pain. In a study in patients with type 1 diabetes, insulin pharmacokinetics were accelerated with co- administration of PH20 and prandial insulin versus prandial insulin alone (Hompesch et al., Diabetes Care 2011). In another study, co-administration of PH20 with rapid-acting analogs decreased time to 50% exposure from about two hours to 75 minutes, doubled early first-hour exposure, and halved exposure beyond two hours for all three rapid-acting analogs (Morrow et al., Diabetes Care 2013).
  • FIAsp: FIAsp is aspart insulin combined with the excipients nicotinamide (to help speed absorption) and arginine (to stabilize the insulin). Dr. Donner noted that there is no published human data of FIAsp. In pigs, subcutaneous injections of FIAsp were shown to reduce postprandial glucose. Phase 3 trials for FIAsp are planned to start in 2013 and 2014 in both patients with type 1 diabetes and patients with type 2 diabetes.

Questions and Answers

Q: In studies comparing insulin glargine and insulin degludec, dosing was quite different – glargine was dosed any time, and degludec dosing was fixed around the evening meal. Could you comment on whether you think that contributed to the differences observed in nocturnal hypoglycemia?

A: I don’t know how they made the decision to dose at different times, but you would expect to have less nocturnal hypoglycemia with glargine if it’s dosed in the morning.

Q: Do you really think we need a liver-specific insulin? I know it’s important in normal physiology, but we’ve already seen some side effects, and [a large proportion] of our patients have fatty liver disease.

A: Ideally you’d have a liver-specific insulin to help suppress hepatic gluconeogenesis. If you have insulin preferentially taken up in the liver, it would lower systemic insulin levels – there are some suggestions that systemic insulin levels may influence cardiovascular risk. You’re right though in that any insulin that has preferred hepatic action needs hepatic safety.

Q: Do you know anything about the status of smart or glucose-sensitive insulin?

A: That’s really our holy grail, isn’t it? Glucose-dependent insulin would only be activated when glucose is elevated. I know of at least two companies who are working on it. These insulins would typically have a moiety attached to the insulin that would dissociate when glucose becomes elevated, and become activated.


William Cefalu, MD (Pennington Biomedical Research Center, Baton Rouge, LA)

Dr. William Cefalu provided an excellent review of alternative insulin delivery systems, aptly commenting that 25 minutes was not enough to cover the entire field. To begin, he remarked that alternative delivery systems – transdermal, nasal, sublingual, buccal, oral, inhaled, and intraperitoneal – have a “huge hurdle to jump” since they must address the many significant barriers to insulin use. Turning first to transdermal delivery, he detailed the types of microneedles available (solid, coated, dissolving, hollow) and commented that the U-Strip Transdermal insulin is currently in phase 3 (developed by Transdermal Specialties). Dr. Cefalu’s subsequent discussion on buccal insulins centered on Oral-yn (phase 3), which he believes requires a better formulation to reduce the number of puffs per meal. Dr. Cefalu focused the largest portion of his talk on oral insulins and swiftly reviewed several candidates: Biocon’s IN-105, Oramed’s ORMD-0801 (with new data in poster 1054-P), Diabetology’s Capsulin, Novo Nordisk’s oral insulin candidate, and Diasome’s hepatic-direct vesicles (we recently published a review of oral insulins, available at Dr. Cefalu concluded his talk with a brief mention of inhaled insulin, noting that the only company still pursuing this approach is Mannkind (phase 1 data on Afrezza is being presented in poster 982-P).

Questions and Answers

Q: Regarding inhaled insulin, we’re all very hopeful. One of the limiting factors is the question about whether it has pulmonary effects and what happens in the long term. What is your take on this?

A: We’ll wait for the information from studies. We saw a small pulmonary effect that appeared to be maintained across time, and which stopped after drug discontinuation. I think that long term studies will be needed.

Q: I’m wondering about the viability of using insulin preparations or delivery systems that only have an efficiency of 5-10%, because this means that if you increase absorption through some physical change in the patient, then you could triple the dose. Is that going to be a limiting factor?

A: I don’t know. At this point, you’re talking about a buccal or oral insulin. For the buccal delivery, it’s going to take more insulin. For the oral insulin, you have to think about the liver effects. We don’t really know, and we don’t have enough data. We know that some oral insulin products work, but we need more studies on their efficacy and their systemic levels.

Comment: I want to advise that in the intradermal space, BD has been working in this area using a 150 micron steel microneedle and has published a number of studies showing reproducible accelerated kinetics of insulin by about 40%. I just wanted to mention that.

Q: Oral insulin is facing a number of obstacles. Do you think we’ll get by all the obstacles and really have a preparation?

A: I can’t predict the future; I don’t know. There are some tremendous hurdles. I’ve shown you the proof of concept but there are obviously a lot of hurdles. These are small studies in a limited number of patients. If we can get past those and prove proof of concept in larger studies, perhaps we’ll see. Time will tell and studies will tell.

Product Theater


Vivian Fonseca, MD (Tulane University, New Orleans, LA)

Dr. Vivian Fonseca addressed a standing-room only audience to present pooled data on J&J’s Invokana (canagliflozin)..He first reviewed the role of the kidneys in glucose homeostasis, highlighting Invokana’s mechanism of action as an SGLT-2 inhibitor: the drug lowers the renal threshold for glucose excretion (RTG) in type 2 patients, causing increased urinary glucose excretion. Dr. Fonseca next presented pooled data on the drug as mono-, dual-, and triple-therapy, as well as in an elderly patients. All studies had a primary endpoint of A1c reduction, though Dr. Fonseca noted that in these studies, canagliflozin also reduced plasma glucose levels (both fasting and post-prandial), body weight, and systolic blood pressure, with low rates of hypoglycemia. Dr. Fonseca explained the safety concerns associated with canagliflozin, addressing rates of renal and urinary disorders, as well as increases in LDL-C; on this front, he asserted, “this drug is not going to be used in patients with renal impairment. It’s not going to work, so why use it?”

  • Dr. Fonseca reviewed pooled data on the efficacy of canagliflozin, noting that the drug provided significant A1c reductions compared to placebo as both monotherapy and add-on therapy. In a study comparing canagliflozin monotherapy to placebo, canagliflozin 300 mg provided a 1.16% reduction in A1c over 26 weeks (A1c inclusion criteria: ≥7% to ≤10%; n=587). Regarding secondary endpoints, canagliflozin 300 mg was associated with a decrease in fasting plasma glucose of 43 mg/dl and a decrease in post-prandial glucose of 64 (baseline FPG: <270 mg/dl), in addition to a body weight reduction of 3.3% (placebo-adjusted) from a baseline of 192 lbs. Dr. Fonseca also mentioned a drop in systolic blood pressure, noting that the mechanism of this effect needs to be studied further. As add-on therapy, canagliflozin demonstrated greater A1c reductions across placebo-controlled studies where patients had a baseline of roughly 8%. Dr. Fonseca noted that improvements in A1c and weight loss also occurred in patients poorly- controlled on insulin and other oral agents (a group he acknowledged is difficult to manage), as well as in patients on pioglitazone (who are likely to gain weight). Dr. Fonseca emphasized that the incidence of hypoglycemia was generally low, though it increased when canagliflozin was evaluated in combination with insulin or an insulin secretagogue.
  • Dr. Fonseca addressed the adverse events associated with canagliflozin, highlighting the increased rates of hyperkalemia, genital infections, and LDL-C levels. Hyperkalemia adverse reactions occurred in 0.7% of the broad study population receiving canagliflozin 300 mg (n=3,085) compared to 0.5% in the control group (n=3,282) – Dr. Fonseca attributed this observation to the fact that many of these patients are also on drugs that cause hyperkalemia. Dr. Fonseca explained that the prevalence of urinary tract infections was similar between the placebo and canagliflozin 300 mg groups (4.0% and 4.3%) in four placebo-controlled 26-week population studies, but that genital infections were more commonly seen with canagliflozin compared to placebo (11.4% vs. 3.2%, respectively). Dr. Fonseca stipulated that genital infections rarely reoccur and can be resolved with routine treatment. Turning to the observed elevated LDL-C levels, he admitted that the mechanism behind this effect is not known.
  • Dr. Fonseca noted that canagliflozin is not recommended for patients with moderate renal impairment and mentioned that studies are ongoing to fully evaluate the drug’s effect on renal function. He explained that the canagliflozin’s mechanism of action relies on a normal glomerular filtration rate for maximal efficacy. Dr. Fonseca acknowledged the concerns about renal impairment, and noted that compared to patients with mild renal impairment or normal renal function, patients with moderate renal impairment (eGFR 30 to <50 ml/min/1.73 m2) experienced less glycemic efficacy, as well as a higher rates of adverse reactions related to reduced intravascular volume and decreased eGFR. , However, studies are ongoing and data has not been established in patients with severe renal impairment (eGFR <30 ml/min/1.73 m2) or end-stage renal disease. Dr. Fonseca concluded by emphasizing that renal function must be monitored in patients on canagliflozin.

Questions and Answers

Q: By using canagliflozin are you not altering the normal physiology?

A: Yes, to a great extent that is true, but remember that the renal threshold is actually higher in patients with type 2 diabetes. This is based on a small study, and recently, Dr. Ralph Defronzo has done a study on renal threshold in Diabetes Care. It is an abnormality that represents a maladaptive process that you’re reversing to some degree. We’ve tried drugs that improve insulin sensitivity and they work, but not enough to overcome the problem of diabetes. I’m not saying that canagliflozin is going to do that, but it offers an adjunct to those therapies and it is doing it with a completely insulin-independent mechanism.

Q: If you ingest more glucose, do you excrete more glucose?

A: The filtering of glucose is dependent on blood glucose levels. When you have more glucose in the blood, you have more excretion. So in fact, this is why it is even better in the post-prandial state than in the fasting state.

Q: What causes the increase in renal glucose threshold in diabetes?

A: I wish I knew. This is a maladaptive process. Any transport system tries to adapt when you overwork it. I don’t think it’s a fundamental defect of diabetes.

Q: In which patients would you use Invokana?

A: It’s been tested across the board. You choose your patients based on their characteristics and their needs.

Q: How long should I keep my patients on the 100 mg dose before moving to the 300 mg dose?

A: There’s actually very little data. There is a dose-response relationship. This not a drug that you titrate because of side effect issues; you titrated up to get the patient to goal. If your patient still has a higher fasting glucose level, you might want to go to the higher dose.

Q: How does sitagliptin compare to canagliflozin 100 mg?

A: That data is not available. The study was done with 300 mg. That is the max dose of both, so it’s a fair comparison.

Q: Can canagliflozin be used with all types of inulin?

A: Yes, it can.

Q: Why is there a weight loss plateau?

A: There are adaptive mechanisms to any weight loss therapy. Thank God, otherwise we would disappear. We really don’t know. This is not the primary reason why you’re using the drug. You’re using it for A1c reduction; everything else is a secondary endpoint.

Q: What side effects are most common?

A: Genital infections. When I first looked at the mechanism of action, I was concerned about urinary tract infections. But these are mycotic infections, so patients take an antifungal and they get over it. We need to explain this to our patients and get them back into the office for appropriate therapy. You may get a few patients where the infection reoccurs. This is not the medication for them.

Q: Of the patients who experience UTIs, how many are recurrent?

A: Recurrent infections were very low. If I saw patients with recurrent infections, I put them on a different medication

Q: Can it be used with other weight loss therapies such as Belviq (Arena/Eisai’s lorcaserin)?

A: It hasn’t been done; however, I’m sure the combination studies will be done in clinical practice, and it will be studied further.

Q: How can we prevent genital mycotic infections?

A: This has not been looked at, but we need to. They might need to drink more fluids or practice more hygiene as a precaution. I hope they will address this over time.

Q: Does it increase nocturia (the need to urinate at night)?

A: I showed you some reported increases in urination, so you might get some patients where this happens overnight.

Q: Can it be used in patients who are taking diuretics?

A: Dehydration occurs most in patients with diuretics. These patients are on hypertensives and need to be monitored for dehydration.

Q: What was the rate of dropout from the studies?

A: I showed you, and it was remarkably low.

Q: Does blocking the SGLT work in other systems like the GI tract?

A: This is an important point to clarify. SGLT-1 is prominent in the gut, while SGLT-2 is prominent in the kidney. SGLT-1 is also present in the kidney, but more distally. A long time ago, a drug called phlorizin was evaluated for type 2 diabetes and was shown to improve insulin sensitivity in rats. We wanted to try it in humans but there were a lot of GI side effects, because when you block SGLT-1 in the gut, you end up with a lot of glucose in the large bowel. This is why SGLT-2 inhibitors have been developed. It is very specific, and it doesn’t block the SGLT-1 co-transporter.

Q: Why do you get the side effect of increased LDL-C?

A: I can’t explain that. This clearly needs more investigation. You need to watch for it, and treat it appropriately.

Q: What do we know about the drug’s effects on the kidney in the short term and the long term?

A: There is a small drop of about 2 or 3 in eGFR when you first start treatment, which flattens out and stays down for the duration of the drug treatment. Long term, we don’t know. This will be monitored in the CVOT (CANVAS). I don’t think the drug is going to be used in patients with renal impairment; it’s not going to work, so why use it?

Q: Any fear of malignancy?

A: Dapagliflozin did have an excess of bladder and breast cancer that was small and unexplained, and that held up approval of dapagliflozin. It was not shown in canagliflozin, which is why it was improved.

Q: Any difficulty in subjects with solitary kidney?

A: This floored me. People with solitary kidney have the same renal function as someone with two kidneys.

Corporate Symposium: Impacting Type 2 Diabetes and Optimizing Patient Outcomes with GLP-1 Agonists (Sponsored by Novo Nordisk)


Lawrence Blonde, MD (Ochsner Medical Center, New Orleans, LA)

Dr. Lawrence Blonde, co-author of the new AACE guidelines, maintained that minimizing the risk and magnitude of hypoglycemia and/or weight gain should be a high priority for patients with type 2 diabetes. He presented data demonstrating that hypoglycemia may be more common and have a more profound impact on patient outcomes than providers might expect: a patient survey found that at least 60% of type 2 diabetes patients experience at least one episode of non-severe hypoglycemia/month, with 35% experiencing episodes once-daily to once-weekly (Brod M et al., Value Health 2011); in addition, hypoglycemia is associated with increasing healthcare costs and reduced long-term survival in type 2 diabetes (Williams SA, et al., J Diab Complications 2012; Hsu et al., Diabetes Care 2013). Dr. Blonde presented GLP-1 agonists and DPP-4 inhibitors as effective options for avoiding hypoglycemia and weight gain, highlighting their prominence in recent algorithms (e.g., ADA/EASD 2012 and AACE 2013). He presented data demonstrating that adding a GLP-1 agonist to metformin provides better glucose control and greater weight loss than adding a DPP-4 inhibitor. In addition, he argued that GLP- 1 agonists may “prime” a patient for eventual progression to insulin (he noted that most patients with type 2 diabetes will end up needing insulin). In DeVries et al. (Diabetes Care 2012), adding basal insulin detemir when people failed to achieve A1c goals on metformin plus liraglutide provided a further 0.5% improvement in A1c without causing patients to regain the weight they had lost by adding liraglutide to metformin. He interpreted this to mean that optimizing one’s own endogenous glucose excretion prior to adding exogenous insulin may have a benefit.

  • Notably, Dr. Blonde referenced results from a poster he presented earlier today suggesting that A1c reduction derived from Bydureon was independent of weight lost. He emphasized that even if patients do not lose weight on GLP-1 agonist therapy, they can still experience tremendous glycemic benefits.


Michael Nauck, MD, PhD (Diabeteszentrum Bad Lauterberg, Harz, Germany)

To begin the symposium, Dr. Michael Nauck discussed the use of GLP-1 agonists in the treatment of early-stage type 2 diabetes. After discussing incretin mimetics’ mechanism of action, he began discussing the efficacy of GLP-1 agonists compared to placebo, metformin, and DPP-4 inhibitors. Compared to (or in addition to) the three alternatives, GLP-1 agonists led to equal or better glycemic control and weight loss. He added that some studies even suggest that GLP-1 agonists are slightly more effective than basal insulins and have better effects on weight. Dr. Nauck noted that the most recent ADA/EASD treatment algorithm facilitates shared decision-making, allowing healthcare providers narrow down the list of therapy options depending on patients’ preferences and limitations. He used a case study to illustrate that GLP-1 agonists are optimal for those seeking to avoid weight gain or hypoglycemia. Dr. Nauck confronted concerns over GLP-1 agonists and thyroid tumors, noting that concerns arose from data from rodent models, which process GLP-1 differently in the thyroid. He cited a year-long human trial that showed that high doses of liraglutide did not lead to a significant increase in thyroid tumors. Dr. Nauck also allayed concerns over incretins and pancreatitis. He ended by proposing that GLP-1 agonists may have potential in individuals with only impaired glucose tolerance (IGT), citing data that demonstrated that GLP-1 administration improved insulin response in patients with IGT

Questions and Answers

Q: Given the concerns you mentioned, is it still appropriate to use GLP-1 agonists and DPP- 4 inhibitors earlier in the course of diabetes?

A: Those familiar with these studies say that there is no need to change the clinical practice regarding these drugs, and that they should be used as they have been. Psychologically speaking, the only reason to stop therapy is if the patient feels uncomfortable about using them. Otherwise, I would not be comfortable recommending that patients go off these medications.

Dr. Vivian Fonseca: I’d like to remind audience that these agents are not approved for use in prediabetes.


Vivian Fonseca, MD (Tulane University Health Sciences Center, New Orleans, LA)

In his presentation, Dr. Vivian Fonseca discussed the treatment of well-established type 2 diabetes patients. He noted that many such patients are already on basal insulin, and that if more intensive therapy is needed, providers generally need to choose between initiating the patient on a prandial insulin or adding another agent. Dr. Fonseca noted that prandial insulins require more careful management, are less convenient, and come with an increased risk of hypoglycemia. In contrast, he suggested that incretin mimetics can be effective and safe when added to basal insulins. He argued that basal insulin and GLP-1 agonists have complementary actions, with the former contributing more to fasting and nocturnal control and the latter acting more postprandially. He discussed experimental findings showing that combined therapy with a basal insulin and GLP-1 agonist results in better glycemic control (especially postprandially) and more weight loss. Notably, some companies are starting to explore head to head comparisons between adding a GLP-1 agonist or prandial insulin on top of basal insulin (Dr. Fonseca mentioned GSK’s albiglutide). He added that DPP-4 inhibitor/basal insulin combination therapy also resulted in improvements, albeit with less efficacy and weight loss than the GLP-1/basal insulin combination. Dr. Fonseca concluded that the joint use of incretin-based therapy and basal insulin is a potent combination, able to significantly and safely improve glycemic control. Looking to the future, he expressed optimism about co-formulations of GLP-1 agonists and basal insulins. He cited an early study demonstrating that IDegLira (a combination of insulin degludec and liraglutide) reduced A1c and provided 2 kg more weight loss than the insulin component alone, and expressed hope that future studies will confirm these promising findings.


Michael Nauck, MD, PhD (Diabetes Zentrum bad Lauterberg, Harz, Germany) Lawrence Blonde, MD (Ochsner Medical Center, New Orleans, LA), Vivian Fonseca, MD (Tulane University, New Orleans, LA)

Dr. Fonseca: Monitoring lipase and amylase – do either of you recommend that in clinical practice?

Dr. Nauck: Not at all. We now know a significant proportion of patients with type 2 diabetes have elevated lipase if you just do a random blood sampling. That does not predict pancreatitis. One must know that the positive predictive value of an elevated lipase concentration is really restricted to the ER setting when severe abdominal pain appears. In that situation you can count on a sever lipase concentration to diagnose. In the asymptomatic patient, it doesn’t tell you anything

Q: Is GLP-1 expressed in other tissues in humans?

Dr. Nauck: It certainly is. Mainly the brain and nervous system are equipped with GLP-1 receptors. Some important metabolic organs apparently are not, such as the liver, muscle, and adipose tissue. There have been occasional reports of binding sites if you look at radioactively labeled material, but no GLP-1 receptor has ever been identified in this tissue.

Dr. Fonseca: Larry, there are a lot of outcomes trials going on, all looking at the same composite endpoint for MACE, etc. Should we be a bit more adventurous in this area? Are there novel endpoints we could explore? What else would you like to see, especially now that SAVOR TIMI reported a neutral outcome?

Dr. Blonde: I’m hopeful these trials will in fact show whether or not there is an increased risk of pancreatitis. Other safety endpoints including pancreatitis are being adjudicated or collected. As SAVOR is reported, we may learn about these data. If individual trials are not enough, then we’ll pool data. I think we will learn more about safety in a rapid period of time than we have before.

Dr. Fonseca: The ADA has asked for patient level data for all of these trials to be pooled, or else individual trials will never show a signal because it is so rare. If there is an increase, what will the level be? From the data we have now, we can’t tell.

Dr. Blonde: I agree completely. In these discussions we lose any discussion of benefits vs. risk. There is a risk to not treating a patient. The absolute risk in the Singh study was relatively low, whether or not it was done correctly.

Q: In clinical trials comparing GLP-1 receptor agonists and insulin, what was the mean insulin dose?

Dr. Fonseca: In most studies I recall around 25-30 units.

Q: Dr. Nauck do you know what predisposes somebody to respond well to treatment? Are there genetic markers to look at?

Dr. Nauck: There is a publication on a variant of the GLP-1 receptor that at least determines response to an experimental administration of GLP-1. It could well be that such polymorphisms exist, but there’s no test you can order so it’s something for the future. It’s not applicable today.

Dr. Blonde: And as I showed before, there’s more consistency for A1c reduction than weight loss, though in that study most people had a reduction in both A1c and weight.

Q: How should you consider these agents for children vs. adults?

Dr. Nauck: Small trials have reported, and it works. But safety considerations are different from treating adult populations, so you need a large database to judge safety. The interference of growth in adolescents means we don’t have the data right now.

Q: A point of clarification on the thyroid issue – have there been primate studies of C-cell proliferation?

Dr. Nauck: There is some discussion. Some groups use antibodies or ligands for GLP-1 receptors that have been found to be not specific by other groups. There may be erroneous data out there claiming the existence of GLP-1 receptors where there are none. We’ll have to see with better methods. Regarding thyroid and primates, we know Novo Nordisk has published a large study looking at the pancreas. I would be surprised if they have not looked at the thyroid as well.

Dr. Fonseca: You did mention prediabetes, though it is obviously not an approved use right now. Is a trial being done? What kind of endpoints would be used in such a trial?

Dr. Nauck: The kind of endpoint is under discussion. Is it just the prevention of diabetes? Is that sufficient to support clinical use of these agents? The answer is probably no. So you want so need long-term benefit to be proven. Also the bar is raised pretty high with regards to safety because basically then you would be treating “healthy” people.

Dr. Fonseca: But of course many of these people are obese, and you have an obesity trial ongoing.

Dr. Nauck: In the end it’s about the prevention of diseases that are associated with high glucose. So diabetic complications. You would have to do extremely large trials and observe patients from early stages of prediabetes to stages where you expect diabetes complications to draw conclusions that the event rate would certainly be much lower.

Corporate Symposium: Targeting the Kidney: A New Paradigm in T2DM Management – An Evidence-Based Expert Exchange (Sponsored by Boehringer Ingelheim and Eli Lilly)


Anne Peters, MD (University of Southern California Keck School of Medicine, Los Angeles, CA)

Speaking to a standing-room-only crowd in the Hilton Grand Ballroom, Dr. Anne Peters described the ADA/EASD position statement, which she co-authored (our report on the publication is available at In opening, she emphasized that the document is a position statement rather than a guideline or an algorithm. Dr. Peters explained that the co-authors of the document were especially concerned with the increased mortality observed in ACCORD, a finding that further underscored the need to avoid severe hypoglycemia. She then outlined the ADA/EASD’s patient-centered approach, which encompasses several points including individualizing treatment targets, promoting shared decision making, and recognizing the pros and cons of each drug class. After walking the audience through the position statement’s main figure, she highlighted the need for drugs that avoid both weight gain and hypoglycemia. Dr. Peter concluded with a high-level overview of the phase 3 programs for dapagliflozin (BMS/AZ’s Forxiga), canagliflozin (J&J’s Invokana), and empagliflozin (Lilly), noting that the drugs generally promote reductions in A1c, body weight, and blood pressure.


George Bakris, MD (University of Chicago Medicine, Chicago, IL)

In starting his presentation, Dr. George Bakris asserted, “If you want a drug that really relieves glucotoxicity, this is the class.” He focused the first portion of his talk on kidney impairment, beginning with a chart that stratifies the risk of chronic kidney disease by GFR and albuminuria (KDIGO 2012). After describing the general role of the kidneys in regulating glucose levels, Dr. Bakris provided background information on the SGLT proteins, highlighting that SGLT-2 is a low-affinity, high-capacity glucose transporter located in the proximal tubule of the nephron that is responsible for 90% of glucose reabsorption. He explained that people with type 2 diabetes have a greater expression of SGLT-2 and can thus reabsorb a greater amount of glucose back into the bloodstream before excreting it in the urine. SGLT-2 inhibitors lower the renal threshold for glucose excretion, thus limiting the body’s ability to reabsorb glucose and promoting the release of sugar into the urine.

  • Sodium glucose transporters (SGLT) are active transporters that use the sodium gradient produced by the NA+/K+ ATPase pumps at the membranes on the luminal side of the cell. Located in the first two sections of the proximal tubule, SGLT-2 has a low affinity but high capacity for glucose and is responsible for 90% of the tubular reabsorption of glucose. While mostly expressed in the intestines, SGLT-1 is also present in the ending portion of the proximal tubule and is responsible for the remaining 10% of glucose absorption. Unlike SGLT-2, SGLT-1 is a high-affinity, low-capacity glucose transporter.
  • Dr. Bakris outlined the rationale for SGLT-2 inhibition. Animal studies of phlorizin (“the prototype SGLT inhibitor”) showed that SGLT inhibition can normalize plasma glucose levels. Mutations in the SGLT-2 transporter linked to hereditary renal glycosuria have been found to be benign, showing potential for manipulating the protein. These observations suggested that selective SGLT-2 inhibitors could increase urinary glucose excretion and promote weight loss.


Paul Jellinger, MD (University of Miami, Coral Gables, FL)

Dr. Paul Jellinger gave a thorough review of the recently published AACE algorithm. Citing evidence from several studies, he voiced support for the AACE-recommended A1c goals – i.e., ≤6.5% for healthy patients with type 2 diabetes and >6.5% for patients with concurrent illnesses who are at risk for hypoglycemia. Referencing UKPDS, Dr. Jellinger noted that microvascular and diabetes-related endpoints, diabetes-related deaths, all-cause morality, and fatal and nonfatal myocardial infarctions all parallel a rise in A1c. In a meta-analysis of five randomized controlled trials, patients receiving intensive treatment were able to achieve an A1c of 6.6% compared to an A1c of 7.5% for those receiving standard treatment (Ray KK et al., Lancet 2009). Additionally, the intensive treatment led to a significant decrease in coronary events without an increased risk of death. Dr. Jellinger emphasized that the AACE glycemic control algorithm ranks incretin therapies and SGLT-2 inhibitors higher than TZDs and SFUs, since the former therapies have a more robust effect on post-prandial glucose PPG levels (as well as a more mild effect on fasting plasma glucose level). The DECODE study showed that lower PPG levels is important for decreasing the risk of cardiovascular events and mortality. Dr. Jellinger recommended that for patients such as the one presented in the case study below, a combination therapy including a GLP-1 agonist and an SLGT-2 inhibitor would be most effective. Finally, Dr. Jellinger concluded by arguing that treating obesity should be part of treating pre-diabetes and type 2 diabetes, referencing AACE’s obesity algorithm and CVD risk factor algorithm. For further details on the AACE comprehensive treatment algorithm, please see page 59 of our AACE report at and our April 24, 2013 Closer Look at


Om Ganda, MD (Joslin Diabetes Center, Boston, MA)

Dr. Om Ganda began the symposium with a case study of a 47-year-old Latino postal worker with undiagnosed diabetes, a prototypical scenario seen by many of the endocrinologists and diabetologists in the audience in their clinical practices. The fictional patient had a history of diabetes and cardiovascular disease, was a smoker and obese, and had high blood pressure, high cholesterol, normal renal function, and an A1c of 8.2%. When the audience was polled, 48% recommended that the patient make lifestyle changes, receive diabetes education, and take a combination of antihyperglyemic therapies. Dr. Paul Jellinger commented that beyond smoking cessation, the single most significant thing a person could do to reverse cardiovascular risk at this point would be to control glucose levels and begin a statin. The audience then learned that the patient was referred for education, provided a blood glucose monitor, and was prescribed TLC and a statin, which caused him to lose weight and experience reductions in A1c and LDL cholesterol. After this information, 49% of the audience recommended continuing lifestyle intervention and adding a combination diabetes therapy. The case study patient was given metformin, but could not tolerate it. Dr. Ganda concluded by asking the audience what they would recommend at this point, and the majority voted to replace metformin with a DPP-4 inhibitor.


Moderator: Om Ganda, MD (Joslin Diabetes Center, Boston, MA)
Panelists: Anne Peters, MD (University of Southern California Keck School of Medicine, Los Angeles, CA) ; George Bakris, MD (University of Chicago Medicine, Chicago, IL); and Paul Jellinger, MD (University of Miami, Coral Gables, FL)

Q: Dr. Peters, can you comment on the age threshold for setting an A1c target

Dr. Peters: The problem with not having a set age or set “anything” for getting to your A1c target is because it has to be done on a case-by-case basis. In a companion piece of the position statement, we were going to present cases to give you a better sense of how we would adjust the A1c. But we either ran out of time or money so that companion piece didn’t come. What I do for patients is that I write a chart for A1c and it’s mainly based on the risk for hypoglycemia. I don’t want to take a patient I’ve been treating for 20 years and say “you’re 80 years old, who cares what your sugar is.” So I think that you have to look at your patient specifically, and hypoglycemia is really the main risk to mitigate.

Q: Would an SGLT-2 inhibitor have any effect on renal function?

Dr. Bakris: The SGLT-2 inhibitors will affect renal function in the following way. They are diuretics. If you have a patient already on a diuretic and you don’t adjust the dose of the diuretic, you could potentially worsen the volume depletion and it will look like they lose kidney function. So you need to be aware that if the patient is on a diuretic or an ACE inhibitor or ARB, you have to back off the diuretic first and maybe also the other drugs because they will have an effect.

Q: What is the recommendation for using SGLT-2 inhibitors for someone with an eGFR less than 30?

Dr. Bakris: These won’t work because when it goes below 45, you’re filtering less glucose, and the amount of glucose reduction you get is going to be limited. In that range, you have to be very careful with diuretic doses.

Q: Where do the fixed-dose combination therapies (FDCs) fit in the position statement?

Dr. Peters: Just like every patient has different and individual needs, a FDC is something that different HCPs use differently. I had the experience were my patients were put on a glyburide/metformin FDC and we too often saw that patients would stop the drug due to side effects and then, they’ve stopped two drugs. So we took it off the formulary so that the patients would take two drugs singularly. In my own practice, I’ll use a FDC if I get a patient to his target on single drugs, because then I can find the right doses, and then I use the FDC, if it works. However, in my practice I often get patients that want me to fine-tune things. In primary care, there may be a greater need for simplicity, and so a FDC in the beginning could also be OK.

Q: Do you have any insight as to why the LDL-C goes up?

Dr. Jellinger: There is a small rise in LDL; it isn’t terribly significant and I’m not sure if it persists if the patient is on aggressive statin therapy. I don’t know why that happens. This class of drugs may not be suitable for someone whose LDL goal is difficult to achieve.

Dr. Bakris: When you look at the data for people with kidney disease, LDL does not go up and interestingly, in patients that do have normal kidney function, there is a correlation between LDL going up and HDL going up. Why should that be a mechanism? I’m not saying it is; it is an observation. I don’t understand it either.

Q: Does the use of SGLT-2 inhibitors affect the microalbuminuria test?

Dr. Bakris: Directly, it depends. If you’re measuring the albumin concentration, you bet there will be an affect. If you’re measuring the albumin:creatinine ratio, you will not have an affect on that or on 24 hour albuminuria.

Q: When you downplayed the role of ACE inhibitors and ARBs, did you consider their role in the metabolic syndrome?

Bakris: You have to look at all the data. If you’re looking at outcomes and you’re looking at the role of ACE inhibitors, in terms of kidney outcomes, there are zero data that support their use either in people IFG or people with early diabetes that are normotensive or that even have early stage hypertension and certainly that have no albuminuria- in this case, there is zero evidence that ACE inhibitors provide protection. The best example is a paper (NEJM 2009) where the patients are normotensive normoalbuminuria – they were biopsied and randomized to ACE, ARB or placebo and they measured the progression of diabetic nephropathy. At the end of study, there was no difference between the groups. So it’s all BS – smoke and mirrors and retrospective epidemiology studies. If you look at the prospective data, it’s nowhere near as compelling. The data for ACE inhibitors and ARBs for the kidney is that if a person’s eGFR is less than 60, and if they have proteinuria, then all the guidelines say that you have be on an ACE inhibitor or ARB. In impaired fasting glucose or early diabetes, there’s no need to use them.

Q: Do we know anything about the durability of weight loss with SGLT-2 inhibitors compared to GLP-1 agonist?

Dr. Jellinger: If you look at the data, the weight loss seems to be every bit as robust. For the early GLP-1 agonists, it may be a tad more; we’re seeing patients treated with GLP-1 agonists that have far more weight loss than that stated in the PI. Whether that plays out with SGLT-2 inhibitors, we will see.

Q: What is your perception of SGLT-1/SGLT-2 dual inhibitor?

Dr. Bakris: I think jury is out. The problem is that if you inhibit SGLT-1, you’ll have a GI nightmare because of the diarrhea and nausea. The magnitude of SGLT-1 inhibition added to the SGLT-2 inhibition is not that much. That’s assuming you can block SGLT-1 and get away with it clinically, which I don’t think you can.

Q: Do you have any insight into the effect of SGLT-2 inhibitors on beta cell preservation and insulin resistance?

Dr. Peters: it’s a complicated issue. You’re reducing glucotoxicity and weight and you’re restoring normoglycemia. I don’t know the specific effects, and it’s the holy grail to preserve beta cell function. I think it would be nice, but don’t think we can say that yet.

Dr. Bakris: I think there are some things that you can use to at least posit a hypothesis. Unless you’re doing specific CRC studies that test beta cell function in man, you won’t get a good answer. I would argue that if you catch diabetes early enough and you use these drugs, you probably would have beta cell preservation. If you’re catching it eight to nine years out, you won’t. That’s my hypothesis.

Dr. Peters: We’ll see.

Q: Why is SGLT-2 up-regulated in people with diabetes?

A: Now all of a sudden the tubule is flooded with glucose, and the transporters are not going to be able to handle that. The transporters, with increased synthesis, try to bring the glucose back up. That’s also the thought behind why the threshold goes up, because there’s a change in the homeostasis. That’s the best theory I can give you.

Q: What about the diuresis part? Should patients be worried about going to the bathroom more often?

Dr. Bakris: Well, when you first get diuretics you urinate often but after about three days, that initial diuresis goes away. So you still get diuresis, but its nowhere near as intense as the first three days. With this drug, I think the amount of diuresis is a function of your glucose excretion. I’m speculating about that.

Dr. Peters: Some studies say that it’s just one more time per day. They weren’t running to bathroom constantly. You also start canagliflozin on a lower dose. I tell people to try it on weekends. I’m pretty careful with patients when they start new drugs; I make sure that they’re hydrated and make sure that they’re not dehydrated. I also cut the dose of the diuretic in half so it kind of balances out. So you have to use your judgment for each patient.

Dr. Jellinger: Patients that have used SGLT-2 inhibitors have reported increased urination just for the first few days. It’s really not a big problem.

Q: We didn’t see much about insulin catabolism in terms of kidney failure, can you comment on this?

A: Of course with renal failure we need to reduce our insulin doses and you can’t use the SGLT-2, at least the existing one, so it’s not really pertinent. SGLT-2 is a non-insulin based mechanism. I’m most anxious to see the effect of SGLT-2 inhibitors in patients who are severely insulin resistant.

Q: What is the effect of SLGT-2 inhibition on the myocardium?

Dr. Bakris: To my knowledge, none. SGLT-2 is exclusively in the kidney. SGLT-1 is in the gut and the kidney.

Dr. Jellinger: Want to make a comment: in choosing an antidiabetic agent, what has emerged is the quest for agents that don’t cause hypoglycemia or weight gain. I want to point out that in 2011, the CDC did a very thorough analysis of drug-related emergency room visits across the country. Forty percent of these visits resulted in admission. Out of the top four drugs that caused these visits, two of them were for diabetes. So hypoglycemia is a huge problem in terms of cost as well. I would urge you to keep that in mind. Agents that don’t cause hypoglycemia and weight gain are really the holy grail. And now we have more of them available.

Q: What is the increase in blood pressure due to?

A: It’s not related to weight, because the effect on blood pressure occurs before you lose substantial amounts weight. The other thing is that they’ve looked at people with relatively low glucose levels, and you still get blood pressure reductions. The argument is that it’s working like an osmotic diuretic. That’s probably what’s going on with the blood pressure effect. The effect is similar to a low dose diuretic.

Q: What is the role of these agents in type 1 patients?

Dr. Peters: The study that was presented yesterday was looking at dapagliflozin in patients with type 1 diabetes – it was a two-week proof-of-concept study. So you won’t see an A1c reduction. But they did see a reduction of glucose levels over the course of the time; the drug seemed fairly well tolerated. So now we can move on to longer studies. I personally am looking forward to using them in patients with type 1 diabetes because I think they’ll play an important role. We’re just beginning to assess if they are truly safe and efficacious.

Dr. Bakris: I agree. I think that in type 1 patients, especially in the older ones that are getting a little plump, it will be good.

Dr. Ganda: Now we’re seeing more weight gain in type 1 diabetes – we saw this in DCCT. So theoretically, I think it makes sense. This should work. Obviously those studies had not been done in type 1 diabetes. These drugs are approved for type 2 diabetes.

Corporate Symposium: Practical Strategies for Improving Outcomes in T2DM: The Expert Course (Sponsored by Sanofi)


Silvio Inzucchi, MD (Yale University, New Haven, CT)

Dr. Silvio Inzucchi opened the evening with a review of the ADA/EASD guidelines for managing hyperglycemia. He noted that a dramatic rise in available anti-hyperglycemic agents since the 1990s has provided novel options for addressing the complex pathogenesis of diabetes, but has also presented new challenges for providers. New guidelines were necessary due to this increase in choices, new efficacy and safety data, new data regarding the benefits and risks of tight glycemic control, and a renewed focus on patient-centered care. Dr. Inzucchi emphasized the guidelines’ patient-centered approach, exemplified by their glycemic targets that depend on patient attitude, life expectancy, disease duration, comorbidities, vascular complications, and support systems. He also explained that in drafting the guidelines, the committee tried to emphasize intensity of approach rather than specific numeric targets. Dr. Inzucchi concluded by asserting that personalization of therapy will be achieved not only by physicians using the new guidelines, but also by their choosing add-on therapies based on anticipation of drugs’ efficacy, patient- concerns about adverse effects, and how advantages of certain drugs meet patients’ current needs (i.e. weight loss).


Samuel Dagogo-Jack, MD (University of Tennessee Health Science Center, Memphis, TN)

Dr. Samuel Dagogo-Jack began his presentation with a question: When two oral agents fail to control type 2 diabetes, would you: 1) add a third oral anti-diabetic medication? 2) start insulin? or 3) start a GLP-1 receptor agonist? He admitted that there are no right answers, because different patients are in different stages in the evolution of the disease. Dr. Dagogo-Jack strongly encouraged the use of insulin therapy to correct the defects present in type 2 diabetes: a depletion of endogenous insulin reserves due to beta-cell failure and increasing insulin resistance. Of the three landmark trials analyzing methods of reducing microvascular complications, the DCCT, Kumamoto, and UKPDS trials, Dr. Dagogo-Jack noted that only DCCT and Kumamoto achieved lasting reductions in A1c. He attributed this distinction to the use of insulin dosing titrated by self-monitoring of blood glucose. Dr. Dagogo-Jack also reviewed the results of the ORIGIN trial to assure the audience that there is no excess risk of cancer with glargine therapy. (Notably, 79% of the audience was already convinced that there was no excess cancer risk prior to Dr. Dagogo-Jack’s review of ORIGIN.) Consequently, physicians considering initiating insulin therapy are left with five key questions:

  1. When in the course of type 2 diabetes is it appropriate to routinely use insulin?
  2. How do we determine that time or stage in any given patient?
  3. What is the ideal initial insulinization strategy?
  4. How should insulin therapy be intensified once initiated?
  5. Do recent data demonstrating the efficacy and benefits of GLP-1 receptor agonists alter traditional approaches to the timing and deployment of exogenous insulin therapy?


Paresh Dandona, MD, PhD (University at Buffalo, Buffalo, NY)

Dr. Paresh Dandona noted that with the traditional three meal per day schedule, patients can spend a great deal of the day in postprandial hyperglycemia. Postprandial hyperglycemia is the major contributor to overall hyperglycemia for many patients with A1c levels below 8.5%, and thus presents an appealing therapeutic target. Dr. Dandona noted that GLP-1 agonists may help bring down postprandial glucose by restoring the incretin effect; he specifically suggested that adding GLP-1 receptor agonists to basal insulin can provide additional glycemic control without hypoglycemia, and may lead to weight loss. He then reviewed other advantages of GLP-1 agonists, including their glucose- dependent actions and their positive effects on visceral body fat. To differentiate the available GLP-1 agonists, he noted that short acting GLP-1 receptor agonists – exenatide and liraglutide – have a greater effect on postprandial glucose, while the long-acting exenatide-LAR has a greater effect on fasting plasma glucose levels. In the spirit of the symposium, Dr. Dandona suggested that these differences offer the potential for individualized therapy.


Paresh Dandona, MD, PhD (University at Buffalo, Buffalo, NY); Silvio Inzucchi, MD (Yale University, New Haven, CT); Samuel Dagogo-Jack, MD (University of Tennessee Health Science Center, Memphis, TN); Davida Kruger, MSN (Henry Ford Medical Center, Detroit, MI)

Q: I don’t think you addressed patients who have uncontrolled A1c, like 13% or 14%. What strategies do you think would be good for these patients? What about a patient who failed two oral medications and has an A1c of 13? Or someone who has just failed metformin, with an A1c of 13%?

Dr. Inzucchi: The answer is different based on where we start. According to ADA/EASD guidelines, you should consider aggressive insulin strategies from the get-go. Once the A1c is 10-11%, you can consider other oral anti-diabetics, once the glucose toxicity is removed. Until glucose toxicity is eliminated, these drugs might not exert their best effect. So, in summary, I would use insulin in these patients. I would consider metformin, depending on renal activity. I don’t know if I would go on basal insulin immediately, or use a basal/bolus approach. I might use the more aggressive approach – it might take months to get anywhere near control on basal alone.

Ms. Kruger: We have to distinguish between a patient who is newly diagnosed vs. a patient who has failed metformin. If the A1c is 13%, sometimes they’ve been symptomatic long enough that they don’t even realize it anymore. But I think the basal/bolus approach is very aggressive. Once you see the glucose toxicity reduced, then you can scale back the insulin and let the beta cells rest. At that point, you can see where you are at so the orals can kick in. Sometimes patients do well on one oral agent, after a long period of time. I would still choose insulin that instance. But, I think those are different scenarios.

Dr. Dagogo-Jack: Patients are heterogeneous. Somebody’s A1c of 13% might indicate chronic undiagnosed diabetes, or it might indicate poorly managed diabetes of many years. While it’s academically very necessary to try to bring glucose toxicity down by using the most potent therapy before testing whether oral agents work, I have had push back from some newly diagnosed patients with double digit A1cs. When I suggest the i-word, they are terrified. But I have also had success with patients on metformin, sulfonylureas, and TZDs. I have seen as high as six point decreases of A1c, from 14 to 8%, within a couple of months. One cannot be too prescriptive in this matter.

Dr. Dandona: As you can see, this is a common enough problem at the general practice level, but it rarely arrives at the academic center level. And clearly, there are differences in opinion about how to handle it. But I think all of us agree that initially at that level, a little basal insulin would be of enormous help to get the A1c to normal levels, and the beta cells can rest, and then you can add different pieces, apart from metformin.

Q: I’d like to know if you can comment on the cost-effectiveness of GLP-1 agonists, for example in a patient with a reduction of 0.6% A1c. I’m wondering the value of a person spending up to $350 a month for an agent, and if that’s really cost-effective.

Dr. Inzucchi: Some people have criticized sulfonylureas for the risk of weight gain. But pound for pound, their ability to reduce A1c is without comparison. Physicians practice in two worlds: one where patients pay out of pocket, and one where someone else is covering the costs. We tend to prescribe differently if someone else is covering the costs. I think there are additional costs – some side effects of medications, besides hypoglycemia, so it’s a complex calculus. But I do agree that in the circumstance of patients of limited means that GLP-1 receptors are often out of reach.

Ms. Kruger: I’d also point out that if you choose insulin, and you don’t use human insulin and choose analog insulin, that two vials of analog insulin is the same cost as a GLP-1. So if you’re thinking about the benefit to the patient in terms of lack of hypoglycemia and weight loss, your average vial of insulin is $125-150 as well unless you go for human insulin, which is about $25.

Q: Could you talk about the use of GLP-1s in patients with gastroparesis?

Ms. Kruger: It’s contraindicated in gastroparesis because those patients have delayed gastric emptying, so you don’t want to further delay it. In terms of pancreatitis and cancer, the verdict is out. In Diabetes Care you’ll see articles come out – an article and a rebuttal out this week – and I think that will clear things up. The important thing is to monitor carefully, and not use them with people who have a personal family history of thyroid cancer, and that people need to be able to recognize the symptoms of pancreatitis. In the next two weeks, there will be more information to make these judgments.

Dr. Dagogo-Jack: In general, patients with mild or any form of gastroparesis will have a greater tendency to complain about the gastrointestinal effects of just about every drug that has gastrointestinal side effects. So, I would have a low threshold to divert to another class.

Dr. Inzucchi: Last week, the NIDDK and the National Cancer Institute put together a workshop, where the high level conclusion was that they could not find convincing evidence between GLP-1 receptor agonists, DPP-4s, and pancreatic cancer. However, they could find no evidence to refute this connection. Pancreatitis can occur – these cases are hard to dismiss, so there may be a low level of risk of pancreatitis. I’ve personally not seen a case. A recent paper from JAMA showed that a twofold risk was concerning, but there are other papers that don’t seem to find this link.

Dr. Dandona: I have had many patients on GLP-1s and DPP-4s over the past 8 years, and we’ve seen only one case of acute pancreatitis, which was resolved. So I don’t think the incidence in clinical practice is that high. But, only time will tell as we learn more information in patient registries.

Dr. Inzucchi: Also, large cardiovascular studies, which are beginning to close out now, or within the next few months, will show whether or not there is a real risk of pancreatitis.

Q: Quite often, I’ll have patients who are well controlled with metformin, sulfonylureas, and pioglitazones. But they’ll come to me with a press report saying that pioglitazones are banned in two countries. Do I listen to the patient’s fear of bladder cancer? Do I reduce the dose? This is a real-world question.

Dr. Inzucchi; I’ve tended to practice with the motto of “If it ain’t broke, don’t fix it.” If a patient is doing well, then I tend to not like the change. The bladder cancer issue has been eroded into the use of pioglitazone. I think we all agree that it is otherwise a well-tolerated medication. This is a very complex issue. I’ve looked at the databases that have been analyzed and I’m personally not convinced of an association. Specifically, the study that raised this question from Kaiser Permanente in California has reanalyzed their data with many more accumulated patient-years and they find no association. Unfortunately, the analysis was never published for a variety of reasons, which I’m not aware of. We know that this study will conclude with a ten-year analysis that will hopefully provide a definitive answer. But unfortunately, that won’t be published until 2014. So I think that this question still haunts this drug class. There’s a fear of edema, bone fractures, and wounds. In the end, sometimes your patient just wants a discussion with the physician, and they want to see what clinical data has been published.

Dr. Dagogo-Jack: Remember, we have an agency that oversees all food and drugs, and they have very qualified researchers. And drug companies are required to share their safety information. So I don’t think the FDA is shy to sanction a product. The current advisory of the product is to not use pioglitazone with a patient with bladder cancer family history, and to discuss the signs. As they have said, they have not made a judgment about whether there is a causal relationship. But I think its safety is responsible interim advice that we can follow. The moment that this is no longer the case, it will be taken from the market.

Dr. Dandona: Even the lowest doses are effective. I’d love to get some data about effects based on dose- response relationships. Because that’s totally missing – we’re talking about generic side effects.


Special Lectures and Addresses: Kelly West Award for Outstanding Achievement in Epidemiology Lecture (Supported by Merck)


Edward Boyko, MD (University of Washington, Seattle, WA)

Dr. Edward Boyko discussed the current evidence surrounding the role of visceral adiposity in the pathogenesis of type 2 diabetes and the metabolic syndrome. Dr. Boyko began his talk by noting that the risk for diabetes in the US is increased in many ethnic groups in comparison to Caucasians. Further, while diabetes prevalence rates generally correspond with the prevalence of obesity in many countries, select countries (including India, Japan, and Singapore) show markedly elevated rates of diabetes relative to their national obesity prevalence rates (defined as BMI > 30 kg/m2). To help understand the basis of these findings, Dr. Boyko reviewed evidence from a number of studies that demonstrated inconsistency between currently used measures of adiposity and degree of visceral fat adiposity between different ethnic groups. For example, a body fat of 34.9% was shown to be equivalent on average to a BMI of 25 kg/m2 in Caucasian women, but a BMI of 27.0 kg/m2 in Pacific Islander women and 20.3 kg/m2 in women from India. Similarly, for a given waist circumference, Japanese men possessed elevated stores of adipose tissue on average vs. Caucasian men. Given findings of differential adipose stores per given BMI measurement among different ethnic groups, Dr. Boyko discussed data from the Japanese American Community Diabetes Study, which examined the risk for diabetes, hypertension, insulin resistance, metabolic syndrome, and IGT associated with various measures of body adipose stores. For each of the above conditions, 10-year risk was only predicted by visceral fat area or five-year change in visceral fat area. Subcutaneous fat area and waist circumference were not associated with increased risk. Despite these results, evidence suggests that visceral adiposity does not entirely explain ethnic differences in risk for diabetes. In particular, a multivariate analysis failed to eliminate the increased risk for diabetes observed in Filipino and African American women vs. Caucasian women after controlling for visceral fat stores. In conclusion, Dr. Boyko argued that visceral adiposity might represent a potential cause for type 2 diabetes and the metabolic syndrome and could help explain ethnic risk differences, but that more research was needed.

Oral Sessions: Navigating the Spectrum–Obesity, Insulin Resistance, and Type 2 Diabetes in Youth


Solveig Cunningham, PhD (Emory University, Atlanta, GA)

From 1998 to 2007, the incidence of obesity was 11.9% among American children five to 14 years old, according to Dr. Cunningham’s analysis of the Early Childhood Longitudinal Study Kindergarten Class (ECLS-K). Overall, the incidence of obesity did not increase in the cohort during the studied time period. Among children who were a normal weight in kindergarten, obesity incidence was low (1.2 to 2.4% annually) and largely constant with age. In contrast, obesity incidence was high and decreased with age among children who were overweight at five years old (from 19.7% in kindergarten to 3.7% in middle school). Children who were overweight in kindergarten were found to be 5.3 times more likely to be obese in 8th grade and accounted for 45% of the obesity incidence between kindergarten and 8th grade. Thus, Dr. Cunningham pressed that prevention efforts must focus on promoting healthy weight in preschoolers and reversing overweight among older children. Notably, sociodemographic factors (i.e., ethnic/race identification and socio-economic status) were not as robustly associated with a child becoming obese by age 14 years, if the child was overweight or obese in kindergarten. This finding suggested that to address pre-kindergarten obesity, addressing birth weight and other health factors might be more important than targeting socioeconomic factors.

  • The analysis found that 11.9% of American children between the ages of five years and 14 years were obese between 1998 and 2007.

Obesity prevalence (95% CI)


Age five years

Age 14 years


14.9% (13.08-17.01%)

17.08% (15.06-19.31%)


12.4% (11.2-13.7%)

20.8% (19.1-22.5%)

  • Children who were overweight in kindergarten were found to be 5.3 times more likely to be obese later in life. These children accounted for 45% of the obesity incidence between kindergarten and 8th grade.

Cumulative incidence of obesity


All children not obese in Kindergarten

Normal weight in Kindergarten

Overweight in Kindergarten


11.9% (10.6-13.3%)

7.9% (6.7-9.0%)

31.8% (26.9-36.7%)


13.7% (11.9-15.5%)

9.1% (7.5-10.6%)

36.6% (29.7-43.4%)


10.1% (8.2-12.0%)

6.6% (4.9-8.3%)

26.9% (20.3-33.4%)

  • Dr. Cunningham used the National Center for Education Statistics’ data set, ECLS-K. This data set follows a nationally representative cohort from kindergarten to eight grade and therefore includes people ranging in age from five to 14 years old. For this analysis, data from 1998 to 2007 were used – including 7,738 children and 69,642 participant-years.

Questions and Answers

Q: Did you have any information on whether or not the children attended preschool?

A: We did not use those data, though they are available. That is something that we will get.

Product Theater


James Gavin III, MD, PhD (Emory University School of Medicine, Atlanta, GA)

An incredible thinker and orator, Dr. James Gavin detailed the label and phase 3 data for Vivus’ Qsymia (phentermine/topiramate ER). Reflecting on the product theater, we felt the program had a more competitive undercurrent against Arena/Eisai’s Belviq (lorcaserin) than we detected at Vivus-sponsored events before Belviq’s launch earlier this month. For example, when reviewing AACE’s comprehensive diabetes management algorithm, Dr. Gavin highlighted that Qsymia is the “only” pharmacotherapy referenced for the treatment of overweight and obese people with type 2 diabetes with low, medium, or high risk of complications. Additionally, when describing obesity’s pleiotropic etiology, Dr. Gavin remarked that such a complex disease requires a combinatorial approach, such as phentermine and topiramate ER (implying lorcaserin monotherapy might not suffice). Reminding attendees of the prevalence of depression among overweight and obese people, he underscored that Qsymia’s phase 3 program included people with depression, demonstrating that Qsymia is safe in this group. This contrasted with other phase 3 programs (i.e., Belviq’s) that excluded this population. In this vein, Dr. Gavin also focused on Qsymia not being a serotonergic drug. Indeed, this contrasts with Belviq, a serotonin-2C receptor agonist. Dr. Gavin emphasized that since Qsymia is not serotonergic, people with depression who are on SSRIs can take the medication.

Questions and Answers

Q: Has valvulopathy been seen with Qsymia?

A: No that has not been seen in clinical trials to my knowledge. Qsymia is not a serotonergic drug.

Q: Why should you choose Qsymia over the individual generic drugs?

A: Remember I showed you that Qsymia has doses of those compounds at lower doses than is available in the generic form. With a pleiotropic disease like obesity you need multiple agents. This is not immediate- release topiramate; it is extended-release topiramate, so it is not the same as you would get from the generics.

Q: Should Qsymia be used as a chronic therapy?

A: We are talking about a chronic condition, obesity, where the expectation is that you would need long- term management. Is there a point at which people could be graduated from this therapy? It is not clear; we do not have 10-year data. For the most part, we are talking about chronic conditions that require chronic therapy.

CME Event: Beyond the Basics: Addressing Obesity in Your Patients with Type 2 Diabetes (Supported by Vivus)

Ralph DeFronzo, MD (University of Texas Health Science Center, San Antonio, TX)

Dr. Ralph DeFronzo’s presentation on the pathological link between obesity, type 2 diabetes, and other complications marked the first time we have heard his present at an obesity-focused event. Dr. DeFronzo detailed how the “triumvirate” (pancreas, liver, and muscle) is involved in all these conditions through insulin resistance. The presence of fat in the liver and muscle drives insulin resistance in these organs, and beta cell failure (in part due to fat depots in the pancreas) can lead to type 2 diabetes. He presented data demonstrating that a lean person with type 2 diabetes and an obese person with normal glucose tolerance have the same level of insulin resistance, as measured by clamp studies of hepatic glucose production and glucose uptake by the muscles. (This data was from the late 1980s; Dr. DeFronzo remarked that he had to use an old study, since it is becoming increasing difficult to find people with type 2 diabetes who are lean). Thus, Dr. DeFronzo argued that the transition from a person being obese without type 2 diabetes, to having type 2 diabetes is due to beta cell failure preventing the pancreas from compensating for the insulin resistance. Looking to the other complications of obesity, Dr. DeFronzo argued that metabolic syndrome should actually be called the “syndrome of insulin resistance,” since he thinks the underlying issue is insulin resistance.

  • Dr. DeFronzo closed his presentation arguing, “a calorie, is a calorie, is a calorie.” He described the overflow hypothesis, which describes adipocytes as a storage depot for fat. According to the theory, when the capacity of adipocytes to store fat is exceeded, there is an overflow of fat into the muscle (leading to insulin resistance), the liver (increasing insulin resistance and hepatic glucose production), and the pancreas (decreasing insulin secretion).


Steven Smith, MD (Sanford-Burnham Medical Research Institute, Orlando, FL)

Dr. Steven Smith expressed concern that 5-10% weight loss is an underutilized clinical tactic for improving glycemic control in people with type 2 diabetes despite it being recommended by the ADA. Reflecting on different lifestyle interventions, Dr. Smith argued that the key is caloric restriction. He emphatically countered the notion that any one diet or macronutrient ratio is supreme. Ultimately, Dr. Smith believes the best diet is the one the patient can understand and maintain. Switching to the other side of the anti-obesity treatment spectrum – bariatric surgery – Dr. Smith described these approaches as being an option for patients who meet the appropriate criteria . He presented data from the Swedish Obesity Subjects study showing that bariatric surgery can reduce mortality (by 29% at a 15 year follow-up), and cause diabetes remission.

  • A number of diet interventions can facilitate caloric restriction and improve glycemic control. Portion control diets (i.e. Nutrisystem) have been shown to lead to an A1c decline of -0.88%, compared to. 0.03% in the control group (p<0.001; baseline A1cs not provided). He stated that meal replacements can also be effective, with studies showing an A1c decline of 0.49% (p<0.05). The Y has implemented what Dr. Smith calls a “DPP-lite” programthat can help patients follow-through their behavior modification (we believe he was referencing the National DPP, for which the Y is partnering with the CDC).
  • Though bariatric surgery appears to have a “magical effect” on diabetes remission one-week post operation, Dr. Smith demonstrated that an extremely low calorie diet (600 kcal/week) can also spur rapid diabetes remission and improve beta cell function. From a baseline A1c of 7.4%, a very low calorie diet was found to produce a decline to 7.1% at week 1, 6.5% at week 4, and 6.0% at week 8. This corresponds to a weight loss of 3.9% atweek 1, 9.3% at week 4, and 15.1% at week 8.
  • Dr. Smith closed his presentation by focusing on whether weight loss without exercise or exercise without weight loss is better for glycemic control. Citing a re- analysis of the Dr. Smith suggested that though exercise can be beneficial, weight loss is more important for glycemic control. Of course, he stated that exercise with weight loss is ideal. To Dr. Smith, this reinforced the notion that “calories are king.” He remarked that exercise is perhaps more important for weight maintenance than any other function.


Samuel Klein, MD (Washington University School of Medicine, St. Louis, MO)

Dr. Samuel Klein focused his discussion of anti-obesity pharmacotherapy primarily on the three currently available agents for long-term use: orlistat (Roche’s Xenical and GSK’s Alli), phentermine/topiramate ER (Vivus’ Qsymia), and lorcaserin (Arena/Eisai’s Belviq). Dr. Klein underscored the necessity of not thinking about anti-obesity therapies as “getting patients over the hump,” instead framing obesity as a chronic disease with lifelong treatment. Dr. Klein reiterated that no one should be given medication without some form of behavioral therapy. If patients are just given an anti-obesity medication, he explained, they are at risk for a drug’s side effects without receiving the full benefits of the potential weight loss. Acknowledging how difficult behavioral interventions can be (and physicians’ general lack of training to conduct them), Dr. Klein wryly added, “Don’t even try diet or lifestyle therapy if you haven’t been trained [to do so] or tried it before. Everything you say will be wrong. Refer them to a dietician or a nutritionist or another specialist first.”

  • Dr. Samuel Klein began his presentation on anti-obesity pharmacotherapy in people with type 2 diabetes by reminding attendees that many antiglycemic agents can cause weight gain. These include insulin, sulfonylureas, thiazolidinones, and meglitinides. Prescribing these agents to people with type 2 diabetes can help spur weight loss but is difficult avoid, according to Dr. Klein, due to the minimal pharmacotherapy options.
  • Phentermine/topiramate ER’s phase 3 program included EQUIP and CONQUER. Dr. Klein noted that phentermine and topiramate, in their generic form, are typically used at doses of 30 mg and 400 mg, higher than they are found in Qsymia .
  • Lorcaserin, a selective 5-HT-2C receptor agonist produced a dose-dependent relationship between taking the drug once or twice a day in patients without diabetes. The BLOOM-DM study (in people with type 2 diabetes) demonstrated that A1c is reduced significantly for both once-a-day and twice-a-day doses, as well as improved fasting plasma glucose. Dr. Klein believes this is due to weight loss, but may also be due to some weight- loss independent effects currently not understood.


Moderator: Robert Eckel, MD (University of Colorado Denver, Denver, CO)
Panelists: Ralph DeFronzo, MD (University of Texas Health Science Center, San Antonio, TX); Samuel Klein, MD (Washington University School of Medicine, St. Louis, MO); Steven Smith, MD (Sanford-Burnham Medical Research Institute, Orlando, FL)

Dr. Robert Eckel: The Institute of Medicine recently made a statement saying that obesity is not a disease and the AMA just two days ago said that obesity is a disease. Is obesity a disease?

Dr. Steven Smith: I think that it is the wrong question. I think the important question is what we are going to do about it. If we do not call it a disease it is harder to get people to do anything. I think it was an important step to have the AMA call it a disease but we really need to figure out what we are going to do in our clinics.

Dr. Ralph DeFronzo: I agree with that. There are so many complications that go with obesity. Rather than treating each of these individually – if we treat obesity, they might all get better.

Q: When will obesity agents be used in patients with diabetes, early or late in the progression?

Dr. Klein: We really underutilize them in the weight loss paradigm – they should be begun aggressively in the natural history. In addition to improving glycemic control, weight loss will also benefit the complications of obese patients.

Q: Can you provide more details on your thoughts about lorcaserin?

Dr. Smith: An important thing about lorcaserin is that not everybody is going to respond to it. I think that it is important for us to remember that a therapeutic trial is a possibility. For those who did complete the trial weight loss was around 10%. Not everybody will respond to lorcaserin but if they do they have nice weight loss.

Dr. Klein: Would you do the recommended dose or double the dose?

Dr. Smith: I am a label guy. I will do what the label suggests. Dr. Klein: Ok, so you won’t go with what the data shows.

Q: Why didn’t you recommend discontinuing TZDs?

Dr. DeFronzo: That drug, along with GLP-1 analogs, are the only ones the work in the long run. The more weight you gain, the better the improvements in A1c and insulin sensitivity. The key is starting with the triple therapy all the time. We clearly need to change and start treating the pathophysiology.

Dr. Klein: What about endoscopic approaches to fill the gap?

Dr. Klein: There are several of these approaches being tested right now in the US. The results of those studies will determine which is approved and used in the US. There is a question specifically about the balloon. The balloon is not used in the US and there is a studying ongoing here. There was a study showing that people had the same weight loss with the balloon and the sham. Another study showed that people had more weight loss with the balloon. I think that the US trial will be the determining factor on that one.

Q: Can you comment on the combination naltrexone/bupropion?

Dr. Smith: Naltrexone/bupropion – on the heels of sibutramine, the FDA asked them to do a CVOT, which should be released next year. If that proceeds well, it could be approved by the FDA in 2014.

Q: Why do we “lose the cure” and get recurrence eight to ten years after bariatric surgery?

Dr. DeFronzo: People have to remember that this is not a cure, you have created a pathophysiological disturbance that overrides the basic underlying disturbance – it just happens to be a good disturbance. The only way to cure diabetes is to go back and get different parents and genes. There is always going to be a genetic predisposition to gain weight. If you have a heavy dose of bad genes you will gain weight despite the bariatric surgery.

Additional Topics

Special Lectures and Addresses: President, Medicine & Science Address and Banting Medal for Scientific Achievement Award Lecture


John Anderson, MD (The First Clinic, Nashville, TN)

After opening with a personal narrative on the struggle of caring for patients with diabetes in a primary care setting, Dr. Anderson delivered a fantastic address on the disparity between the growing diabetes epidemic and the number of practitioners who deliver diabetes care. Primary care physicians work with the majority of people with diabetes in the country. Unfortunately, their numbers are declining and medical students and residents are entering general medicine at lower rates. Dr. Anderson argued that this loss of practitioners will negatively impact diabetes care as the epidemic grows. He also expressed concern at the fact that the US also has too few endocrinologists to meet an ever-increasing demand. He concluded with a series of recommendations to address this problem, including graduate medical education reform, reimbursement reform, lobbying, and the new Pathway to Stop Diabetes program.

  • Although primary care providers deliver approximately 90% of diabetes care, the number of primary care physicians is declining and fewer students are entering general internal medicine. Dr. Anderson noted that 21% of primary care physicians boarded in the 1990s are now leaving practice, compared to 5% of those in a subspecialty. In 1998, 54% of third year internal medicine residents expressed plans to enter general medicine, but only 11 years later that has dropped to 21%, with many choosing to go to a hospitalist or subspecialty career. Dr. Anderson pointed to the average medical school debt of $133,000 ($150,000 when excluding those with no debt) and the heavier workload as possible reasons for these career decisions. Dr. Anderson argued that the lesser number of people entering general medicine will negatively impact diabetes care going forwards. He also expressed alarm at the number of nurse practitioners and physician assistants who have moved into more lucrative specialties as well, eroding a substantial source of diabetes care.
  • Additionally, Dr. Anderson expressed concern at the disparity between the number of adult endocrinologists and the burden of diabetes in the country. He noted the demand is expected to exceed supply by 15% by 2019, and assuming a completely perfect geographic distribution, there is still only one endocrinologist for every 400,000 people with diabetes. Additionally, there has been only a 35% increase in the number of first yearendocrinology fellowship slots since 2002, although the percent of people with diabetes has increased by nearly double that rate.
  • Dr. Anderson concluded with a series of recommendations to address the need for more general practitioners, endocrinologists, and diabetes research. He proposed graduate medical education reform that would increase funding for training primary care residents and expand loan repayment options. He also argued for reimbursement reform that would focus on value-based incentives, enhance reimbursement for non-procedural specialties, and expand nurse practitioner prescribing capabilities. Additionally, he encouraged lobbying efforts aimed at increasing funding for diabetes research, as NIH funding per affected person is currently only $41.71 for diabetes compared to $2,549.17 for HIV/AIDS research. Finally, Dr. Anderson announced the launch of the Pathway to Stop Diabetes Program. This program aims to make a career commitment to diabetes research an attractive and rewarding prospect for young scientists by identifying promising individuals and supporting them through grants and mentorship.


Graeme Bell, PhD (University of Chicago, Chicago, IL)

Dr. Bell began his acceptance speech by telling the story of his decades spent discovering diabetes-linked genes. He gave thanks for the friends, colleagues, and institutions that made his work possible, and paid tribute to fellow researchers who are no longer with us today. He then discussed two of the most prominent families of genetic diabetes: maturity-onset diabetes of the young (MODY) and neonatal diabetes. He noted that both terms encapsulate a diverse set of diseases with different genetic causes, each of which has different treatment requirements. For example, HNF2A-related MODY requires sulfonylurea treatment, whereas glucokinase-related MODY requires little to no intervention. He mentioned that the frequent misdiagnosis of genetic forms of diabetes complicates the treatment process. He argued that early genetic testing for diabetes-linked genes can lead to better outcomes and can potentially be cost-effective if patients are properly pre-selected for testing. He also mentioned a new Drosophila model his lab is currently using to clear the fog of genetic variability and discover new diabetes-linked genes. Echoing the sentiments of the Banting Award’s namesake, he ended by saying that genetics is not a cure for diabetes but can lead to better treatment.

  • Dr. Bell has enjoyed a long career discovering genes that cause certain types of diabetes. He spoke of working alongside other well-known researchers such as Drs. Kenneth Polonsky and Nancy Cox, also of the University of Chicago. He noted that his group’s discovery of the first MODY genes was a significant technical accomplishment, especially given that there was no map of the human genome to guide their efforts. He also mentioned more recent work in his lab to study individuals from diverse genetic backgrounds to find new variations in diabetes- related genes and proteins.
  • Not all genetic forms of diabetes are created alike. Dr. Bell presented data on the different glycemic profiles seen in different forms of MODY and neonatal diabetes. He highlighted glucokinase-related MODY, noting the minimal loss of glycemic control its patients experience and even arguing that it might not be a true form of diabetes. He mentioned that monogenic diabetes can stem from a variety of sources, including endoplasmic reticulum stress, ion channel disorders, or epigenetic changes.
  • Genetic testing for inheritable forms of diabetes can be worthwhile in terms of both patient outcomes and costs. Dr. Bell, who has long been concerned with the economics of healthcare, presented an analysis demonstrating that genetic testing for MODY can be cost effective if the cost of the test drops from $2,500 to $700, or if there is at least a 31% pick-up rate. He suggested that such a rate could be achieved through proper pre-screening. In his view, such testing would benefit patients tremendously, as both MODY and neonatal diabetes are frequently misdiagnosed as type 1 or type 2 diabetes.
  • The rate of discovery of new diabetes genes has slowed, but a new Drosophila model could help accelerate the search. Dr. Bell noted that genetic variation might be covering up certain milder genetic forms of the disease. The novel Drosophila model, currently being utilized in Dr. Bell’s lab, can help identify modifier genes that mediate this phenomenon. Dr. Bell stated that it could be used to study the pathophysiology of misfolded human proinsulin, as well as other proteins and pathways that could be involved in diabetes.

Oral Sessions: Improving Health Care Delivery


Sandra L. Jackson, MPH (Emory University, Atlanta, GA)

Dr. Sandra Jackson presented the results of MOVE! (Managing Obesity and Overweight in Veterans Everywhere), a VA program modeled after the Diabetes Prevention Program (DPP) that was designed to evaluate whether lifestyle change programs such as the DPP could be effective in large, real-world settings. Of the 402,693 participants included in MOVE!, three-year follow-up data was available for 135,686 patients; of these, the 8.7% participants deemed to have “active participation” showed significantly greater weight loss than those less involved (-2.7% vs. -1.1%; p<0.001), with non- participants demonstrating no weight change. Overall, weight loss was more pronounced in the 38% of patients that had diabetes at the time of the first visit (-1.7% vs. -0.9%; p<0.01). In participants without diabetes at baseline, incidence was 18.7%, with a relationship between incident diabetes and weight change. While only observational, these results support that success can be achieved in the real-world setting, even amongst veterans who are typically older and sicker with less access to robust support systems (three-quarters of veterans are known to be overweight or obese). We will be eager to see further efforts to determine what qualities defined motivated participants and what measures could be taken to increase participation.

  • Since its inception in 2005, MOVE! has included 402,693 participants, making it the largest lifestyle change program in the US. Though modeled after the DPP, the program made certain departures, including using weight-based eligibility (>30 kg/m2 BMI or >25 kg/m2 with a weight-related condition, such as diabetes) versus prediabetes status, reducing the number of visits (8-12 vs. 16), and including multiple providers with individualized patient-determined goals (vs. single coaches using standardized program goals). At first visit, mean age of the participants was 57 years, with 88% men, and 67% white; all were patients in the VA healthcare system.
  • Three-year follow-up data was available for 135,686 patients; of these, the 8.7% participants deemed to have “active participation” (at least eight sessions within six months and at least 129 days between first and last sessions) showed significantly greater weight loss than those less involved (-2.7% vs. -1.1%; p<0.001). Dr. Jackson noted that this weight loss was only slightly less than that observed in the DPP (-4% at threeyears), suggesting satisfactory real-world translation. Both groups overall demonstrated no evidence of weight regain over the three-year follow-up, and non-participants demonstrated no weight loss. Weight loss for all participants, regardless of level of participation, was -1.3% (BMI from 36.3 to 35.8 kg/m2).
  • Thirty-eight percent of patients had diabetes at the time of the first visit. Dr. Jackson indicated that those with diabetes were more likely to participate actively (9.6% vs. 7.8%; p<0.01) and lost more weight than those without diabetes (-1.7% vs. -0.9%; p<0.01). In participants without diabetes at baseline, incidence was 18.7%; Dr. Jackson noted a relationship between incident diabetes and weight change, with the relative risk of three-year incidence in those losing or maintain their weight versus those gaining weight at 0.84 (p<0.001). Overall, each additional pound lost at six months was associated with a 1% lower likelihood of developing diabetes at three years.
  • In order to gauge the relative benefit, ongoing analyses are comparing MOVE! participants to eligible non-participants (n=1.5 million). Dr. Jackson indicated early results have been favorable.

Questions and Answers

Q: Do you have data on medication initiation or use that could drive weight change? Or how the number of sessions related to weight change?

A: We haven’t yet done the analyses on the number of sessions attended, only that dichotomous variable of active vs. inactive we presented, but the analysis is planned. We did include a control for medications with risk of weight gain or weight loss in our analyses.

Q: The originality of the studies here I think it was not for prediabetes like the DPP, but weight. How did you modify the program for those groups?

A: Well, I think in terms of practical logistics it’s important for the VA to allow all comers. They don’t have to do an OGTT test to determine prediabetes, so it worked well from a logistical standpoint. In terms of making it more accessible, they used that idea of motivational interviewing – asking them how they wanted to change their life in the sessions versus giving standardized goals like in the DPP.

Q: Do you think the LOOK AHEAD study should have been stopped as it was?

A: This is not really a randomized, controlled trial; it’s more observational, and we’ve just started analyzing outcomes so it’s hard to compare.


Brett Hauber, PhD (RTI Health Solutions, Durham, NC)

In a discrete-choice experiment sponsored by Merck (n=923 people with type 2 diabetes surveyed), Dr. Brett Hauber found that out-of-pocket cost and glucose control were the first- and second-most important attributes of oral type 2 diabetes medications. Dosing frequency, weight change, and adverse event rates (including hypoglycemia, chance of mild-to-moderate “stomach problems”, and additional congestive heart failure) were moderately less important to patients though still significant. Looking more specifically at dosing frequency, Dr. Hauber found that 67% of patients, particularly those who were young (<45 years old) or treatment naïve, preferred once-weekly to daily administration. The average respondent was willing to pay $5.86 more per month for a once-weekly pill than a once-daily pill (holding all else constant) – a margin we found to be surprisingly small and potentially of import ascompanies decide on whether or not to invest in developing once-weekly basal insulin, DPP-4 inhibitors, etc. During Q&A, Dr. Hauber noted that people taking multiple once-daily medications might prefer to another once-daily rather than once-weekly treatment, in order to limit day-to-day changes in their medication regime. Still, Dr. Hauber hypothesized that once-weekly dosing might provide an additional incentive to initiate and adhere to a given treatment for many patients, particularly those who are young or drug-naive. We are curious if these sub-population findings might lead Merck to target these groups when it launches its once-weekly DPP-4 inhibitor MK-3102 (phase 3). We suspect that Merck supported this research, in part, to help develop strategies for introducing MK-3102 to the market in a manner that does not cannibalize Januvia (once-daily sitagliptin) sales. For more details on MK-3102 and Januvia, please see our Merck 1Q13 report at

  • Participants (n=923) were recruited by Knowledge Networks. Knowledge Networks is a nationally representative web panel of US households. Dr. Hauber acknowledged that the diabetes sample might not be nationally representative, however. People were included if they were 18 years or older, residents of the US, and self-reported being diagnosed with type 2 diabetes by a physician. They were excluded if they were currently using either insulin or a GLP-1 receptor agonist. We think this latter exclusion could have negatively biased people’s stated concerns with GI adverse events, since people with diabetes might not be on a GLP-1 receptor agonist due to this concern.
    • The researchers invited 2,262 people to participate in the study, of which 940 eligible people consented to participate. Four people were excluded since they did not answer any choice questions and 13 were excluded because they had no variation in responses to choice questions, raising concerns about the honesty of their responses.
  • The sample was not representative of age, race/ethnic identity, or insurance status. It also had slightly more women than men.







Have health insurance


Currently being treated with an oral antihyperglycemic drug


Mean age, years (SD)

63 (11)

- 18-44


- 45-64


- 65 or older


Treatment Status


- Currently on treatment


- Treatment naive


Time since diagnosis


- ≤ 3 years


- > 3 years


  • The direct-choice experiment presented participants with pairs of hypothetical oral- agent profiles and asked them to select the drug they would prefer to take. The profiles were defined by seven attributes: dosing, cost, and five clinical endpoints. These endpoints included average glucose reduction, GI adverse event risk, weight change, and congestive heart failure risk, and hypoglycemia frequency. Implicit preference weights weredetermined for each treatment attribute based on a participant’s pattern of choices. Data was analyzed using a limited dependent variable model.
    • The study included four dosing frequencies (once-weekly, once-daily, two bills once a day, and one pill twice a day).
    • Values for average reduction in glucose (from a baseline of 206 mg/dl) included 20, 30, 40, 50, 60, and 70 mg/dl.
    • The chances of mild-to-moderate stomach problems included were 10%, 23%, 25%, and 30%. The frequencies of hypoglycemia tested were none, 1-2 hypos per year, 1-2 hypos per month, and more than 2 hypos per month.
    • The amount of weight change tested ranged from six pounds of weight gain to six pounds of weight loss (baseline not provided).
    • Additional chances of congestive heart failure included no additional chance, additional 1% chance, and additional 3% chance.
    • The monthly out-of-pocket cost ranged from $0 to $200.
  • The most important attribute for an oral drug was its monthly out-of-pocket cost and the second most important reduction to average glucose (from a baseline of 206 mg/dl). Based on a graph displayed it appeared that people went from preferring a drug due to cost to disliking a drug due to cost, when the monthly out-of-pocket cost was more than $25 and less than $100.


Mean relative importance score

Monthly out-of-pocket cost


Reductions in average glucose (baseline 206 mg/dl)


Hypoglycemia risk


Weight change


Chance of mild-to-moderate stomach problems


Additional chance of congestive heart failure


Dosing schedule


  • Overall, 67% of the cohort preferred once-weekly to daily treatment (either one or two pills a day). People who were drug naïve were more likely than their on-treatment counterparts to prefer once-weekly treatment to daily treatment (75% vs. 65%; p=0.012). Similarly, people who were younger than 45 years old were more likely than those 45-64 years old or at least 65 years old to prefer a once-weekly treatment to a daily option (78% vs. 66% vs. 66%). However, the variation in preference by age was not statistically significant (p=0.065 for the comparison of <45 years to 45-64 years, and p=0.074 for the comparison of <45 years to ≥65 years). Dr. Hauber believed this insignificance was because of the low enrollment of younger people. People who had been diagnosed within three years had essentially same preference for a once-weekly treatment as those who had diabetes for at least three years (66% vs. 67%).
  • People’s willingness to pay was greatest for the transition from a two-pill once-a-day dosing schedule to a one-pill once-a-week option ($13.88 a month). The least financially valued dosing change was going from one-pill twice a day to one-pill once a day ($3.34).

Change in dosing schedule




Willingness-to-pay per month (95% CI)

One pill once a day

One pill once a week

$5.86 ($0.79, $12.47)

Two pills once a day

One pill once a week

$13.88 ($8.06, $22.83)

One pill twice a day

One pill once a week

$9.50 ($3.36, $17.96)

Two pills once a day

One pill once a day

$8.03 ($2.56, $15.21)

One pill twice a day

One pill once a day

$3.34 ($0.20, $10.21)

Two pills once a day

One pill twice a day

$4.38 ($0.31, $10.94)

  • Dr. Hauber did not detail his findings for parameters other than dosing frequency. He did, however, mention that a 13-percentage point reduction in GI risk (from a baseline risk of 23%) was about equally important to the cohort as a two-percentage point reduction in cardiovascular heart failure risk (from a baseline risk of 3%). Not particularly surprising was his finding that a 13 percentage point reduction in GI risk (from a baseline of 23% risk) was more preferred by the cohort than a five percentage point reduction (from 30% risk).

Questions and Answers

Q: Do you have any information on these patients? For example do you know what they were treated with at baseline? Their prior experiences undoubtedly impact how they view these questions.

A: We do not know the specific drugs that they were on. In a previous study we did, we found that people who had a relatively high pill burden placed little value on lowering the frequency with which they took one medication. We probably could look at the same thing here; we have that data. We often find that serious events that impact you in some major way (such as severe hypoglycemia) tend to impact your preferences over that event. The smaller events you learn how to adjust to.

Q: Is there any information on the preferences of patients on vitamin D? Vitamin D can be given once a day to once a month. In my anecdotal experience, it is much less likely that they will take it once a month vs. taking some amount of vitamin D every day.

A: That is correct. I do not know about vitamin D in particular but there is evidence that gets exactly to that point. From my reading what I see is that people prefer for it to be a part of a regular routine – daily is obviously the easiest for that, weekly is possible, monthly is also possible. Every other day does not appear to work. Monday, Wednesday, and Friday appears to work but every other day doesn't.

Q: Why do some people not prefer daily dosing?

A: I think that the previously raised point gets to the idea that it is not unambiguously better to take a pill once weekly than once daily. People who are already taking something once a day might want to just add another once a day drug than to do something different once a week. That is a hypothesis on my part.


Ping Zhang, PhD (Centers for Disease Control and Prevention, Atlanta, GA)

Dr. Ping Zhang presented an analysis of the costs associated with the intensive and standard treatment regimens for glucose, blood pressure, and lipid levels used in the ACCORD trial. Of the 10,251 patients in the ACCORD trial, cost data was available for 4,311 participants. In the glucose intervention, annual costs per participant were roughly $5,500 in the intensive arm versus $4,000 in the standard arm; this compared with $5,000 versus $4,400 in the blood pressure trial and $5,200 versus $4,400 in the lipid trial. While useful for predicting the pattern of resources necessary for achieving various targets, we would also be interested to see how costs compare in a more real-world setting. Additionally, given the ACCORD trial demonstrated no overall benefit, it is difficult to assess how much value was created per dollar spent.

  • Of the 10,251 patients in the ACCORD trial, cost data was available for 4,311 participants, used in this sub-study. As a reminder, goals in the intensive group versus the standard care group for glucose were <6% versus 7-7.9%, for blood pressure <120 versus <140 mmHg systolic, and the use of a lipid and statin versus statin alone for lipid levels. Average annual intervention costs per participant by the study arm and intervention year were analyzed, with costs broken into four categories (personnel, medications, devices and supplies, and lab tests).
  • In the glucose intervention, annual costs per participant were roughly $5,500 in the intensive arm versus $4,000 in the standard arm. Differences between the groups were$1,585 in year one, $1,491 in year two, $1,558 in year three, and $1,427 in year four. Spending in all of the four categories was significantly different between the groups except for laboratory tests.
  • Annual costs per participant were roughly $5,000 with intensive care versus $4,400 with standard care in the blood pressure intervention. Differences between the groups were $646 in year one, $745 in year two, $802 in year three, and $815 in year four. Spending in personnel and medication costs were significantly different between the groups, with most of the overall spending difference due to medication.
  • In the lipid intervention average annual costs per patient were roughly $5,200 with intensive care versus $4,400 with standard care. Differences between the groups were$778 in year one, $730 in year two, $641 in year three, and $584 in year four. Spending only differed significantly in the medication costs category.

Questions and Answers

Q: Do you have any idea of cost offsets for specific treatments and complications?

A: I think the bottom line with a negative trial overall is that it’s hard to justify the intervention, so while we will do those calculations we probably won’t have use for that data.

Q: In real patients, we don’t only treat diabetes or hypertension or lipids. The clinician has to control all three more or less. So my first question is have you calculated the total cost for more intensive or less intensive control. Next, much of the difference in cost is seemed to be due to the cost of drugs. I know certain programs can negotiate for lower costs, so were these retail or negotiated for lower costs? Next with relationship to the outcome of the study, it showed a benefit if the A1c was under 7%. Did you consider calculating benefit for patients achieving A1cs under 7% and real benefit?

A: Yes, you’re right for the first one. We do have patients that received all three, but I don’t have the slides for that. So you won’t need the cost of a visit twice if you’re seeing them for all things at once, and it will be less than the two separate components. The costs of the drug was the price from the Red Book; we picked the median price. For subgroup analysis, we did not tie the cost to the effect yet. But we do have individual level data. We will do that.

Q: Why do this analysis if the study was negative?

A: We tried to take advantage of this data for a sub-economic study. I think you’re right in the real world you do not need to do it, but if we need to know how much it will cost me to reach a particular goal it’s important to make estimates.

Oral Sessions: Gastrointestinal Regulation of Glucose Metabolism


Kristian Mikkelsen, MD (University Hospital, Gentofte, Copenhagen)

Dr. Kristian Mikkelsen presented data from a small human study that examined the impact of eradication of intestinal bacteria on post-prandial glucose metabolism. 12 males with NGT were administered 500 mg vancomycin, 40 mg of gentamicin, and 500 mg meropenem once daily for four days. The study participants underwent a four-hour meal test prior to the initiation of treatment (day zero), following termination of therapy on day four, and 42 days following initiation of therapy. Postprandial gallbladder emptying was determined using ultrasonography. At baseline, the participants had an average age of 23 years, BMI of 23 kg/m2, and A1c of 5.1%. Fecal cultivation on day four demonstrated no bacterial cultivation in samples from six patients, significantly reduced bacterial cultivation in the remaining six patient samples, cultured yeast in all 12 patient samples, and measurable antibiotic concentrations in all 12 patient samples. A significant decrease in both incremental (p=0.04) and total area under the curve (p=0.02) for postprandial glucose was observed between day zero and day four. However, there was no significant decrease in either metric between day zero and day 42. Postprandial insulin response also decreased from day zero to day four, but this difference was not statistically significant (p=0.06). Additionally, there were no statistically significant differences observed in gallbladder emptying or gastric emptying between any of the time points. Thus, Dr. Mikkelsen concluded that a four-day course of a broad-spectrum antibiotic cocktail was associated with a small, brief, and reversible increase in glucose tolerance and a decrease insulin secretion. He suggested that these results provide additional supportive evidence for an important role for intestinal bacterial in human glucose homeostasis.

Oral Sessions: Advances in the Pathogenesis and Treatment of Diabetic Retinopathy


William Mieler, MD (University of Illinois, Chicago, IL)

Dr. William Mieler presented three-year data from the RISE/RIDE trials, which assessed Lucentis (ranibizumab) for diabetic macular edema (DME). Lucentis 0.3 mg became the first FDA-approved pharmacotherapy for DME in August 2012 based on two-year data from these trials (see our report at for detailed two-year results and more on the approval). In these trials, 759 patients were randomized to ranibizumab 0.3 mg, 0.5 mg, or sham injections for two years. In the third year, people in the sham group could cross over to monthly 0.5 mg group. At the end of three years, the percent of patients who were able to read ≥3 additional lines on a standard vision chart was 21%, 44%, and 41% in the sham, 0.3 mg, and 0.5 mg groups, respectively (this compared to 15.2%, 39.2%, and 42.5%, respectively). Those who were initially on sham treatment and then switched over to mg after two years had three-to-four times lesser vision gains than those in the ranibizumab groups.

Symposium: Islet Autotransplantation Following Total Pancreatectomy for Chronic Pancreatitis–State-of-the-Art


Timothy Gardner, MD (Dartmouth University, Lebanon, NH)

Dr. Timothy Gardner delivered an excellent a clear and very thoughtful presentation on genetic mutations that affect the acinar and ductal cells of the exocrine pancreas, leading to chronic pancreatitis. After reviewing the basic physiology of the exocrine pancreas’ secretion processes, he discussed the implications of mutations in the PRSS1 and CFTR genes, highlighting that these are the major genetic causes of chronic pancreatitis. However, he cautioned that there is no clear link yet between genotype and phenotype, as multiple mutations that differentially affect the transport process have been identified for each gene. He concluded that while genetic testing can help inform clinical practices, much more work needs to be done. In the meantime, genetic counseling should accompany all genetic testing so patients understand the implications and limitations of the tests.

  • Mutations in the PRSS1 gene are associated with premature activation of the digestive enzyme trypsin, and subsequent pancreatic destruction. While the acinar cells of the exocrine pancreas typically secrete inactive digestive enzyme precursors that are activated upon entering the small intestine, about 20-30% of the pro-enzyme trypsinogen is activated in the pancreas to become trypsin. Normally, this prematurely activated trypsin is eliminated. However, autosomal dominant mutations in the PRSS1 gene (which encodes trypsin-eliminate this fail-safe mechanism, resulting in trypsin activation, pancreatic autodigestion,and subsequent pancreatitis. Dr. Gardner explained that about 80% of people with this mutation have one episode of acute pancreatitis, 50% develop chronic pancreatitis, and the risk of adenocarcinoma is as high as 40% by age 70.
  • Mutations in the CFTR gene lead to chronic pancreatitis by disrupting the secretion of bicarbonate by pancreatic ductal cells. The cystic fibrosis transmembrane conductance regulator (CFTR) protein acts as an ion channel for chloride, creating an electrochemical gradient that favors bicarbonate secretion. Mutations in CFTR are now known to be associated with a loss of bicarbonate secretion and chronic pancreatitis. There are over 1,600 known mutations in CFTR, resulting in a wide array of phenotypes based how much residual function there is left in the transporter. Manifestations of CFTR mutations range from asthma to pancreatitis to classic cystic fibrosis. Dr. Gardner estimated that 40% of chronic pancreatitis patients most likely have a CFTR mutation.
  • Dr. Gardner emphasized that even though sequencing a patient’s genome and identifying potential mutations may be relatively easy, it is not clear yet which mutation matches which chronic pancreatitis phenotype. Due to the wide availability ofgenetic testing, clinicians may have access to a patient’s gene sequences, but this knowledge cannot conclusively predict pancreatitis (although it can be informative in people with a family history of the disease). Dr. Gardner thus questioned whether there is enough known about the specific genetic causes of pancreatitis to offer testing, and to what degree testing should change management of chronic pancreatitis.

Questions and Answers

Q: With regards to the CFTR mutations, you said one in 20 Caucasians had mutations. What percentage will have a clinical presentation of pancreatitis?

A: That’s a great question, but we don’t know yet. In my world of pancreases, about 40% of my patients with pancreatitis have a mutation of CFTR.

Q: What’s the consequence of genetic testing? We don’t even know the clinical associations, so right now it seems like its more interesting scientifically.

A: I think that’s a very fair point, and I like the conservative nature of that approach. We can do a lot of things to patients when we don’t know why they have chronic pancreatitis, things that are very invasive and damaging. We even do things like taking out their pancreas and transplanting their islet cells. I think that when you don’t know the etiology of a patient’s pancreatitis and you’re considering such a dramatic surgery, giving a genetic test may help sway treatment decisions a little bit one way or the other.

Q: Would you really base a surgery on genetic testing?

Absolutely not, it’s all done with clinical signals in mind.

Q: Are any of these mutations involved in type 1 diabetes?

A: No, not that I know of.

Symposium: NDEP Symposium–New Science–Implications for Diabetes Care


Ann Albright, PhD (Director, Division of Diabetes Translation, CDC, Atlanta, GA)

Dr. Ann Albright introduced the session with a high-level review of the National Diabetes Education Program (NDEP). The program is a collaboration between the CDC and NIH (with over 200 partners!). Launched at ADA 16 years ago, NDEP was formed to translate diabetes science into tools, strategies, and messages to address diabetes management and diabetes prevention. NDEP is currently working to develop its strategic plan for 2014-2019. There is so much need in diabetes and so much that can and should be done, said Dr. Albright. The intent of NDEP’s plan, she explained, is to hone in on where the gaps are and think very carefully about where to put its energy and research and talents.


John Buse, MD, PhD (University of North Carolina School of Medicine, Chapel Hill, NC)

Dr. John Buse shared his expert perspective on three major studies investigating diet and/or lifestyle interventions on health. In preparation for his presentation, Dr. Buse spent a month reviewing ~350 papers on weight management and diabetes published after ADA 2012. “This exercise of reading a huge number of abstracts and a very large number of papers cemented the notion that we have many preconceived ideas about the effectiveness or lack of effectiveness of lifestyle intervention; but in fact, most of these preconceived ideas are not very well backed by science.” Diving right in to the review…

  • Look AHEAD: Drawing on data from the myriad publications on Look AHEAD, Dr. Buse remarked, “As opposed to the medical interventions we use where we provide a tablet for each of the many problems a person with diabetes may have…intensive lifestyle intervention provides very broad benefits to many patients when the intervention is done in patients with diabetes.”
    • For background, Look AHEAD compared intensive lifestyle intervention (ILI) to diabetes support and education. The study was terminated in September 2012 after showing no difference in the primary outcome (CVD event rate) after 10 years of follow up. Said Dr. Buse, “I think many people have forgotten the vast number of publications to date [on Look AHEAD] that show the benefit of lifestyle intervention on BMI, CVD, and A1c…” In particular, he highlighted data on the positive benefits of ILI on mobility and disability (Rejeski et al., NEJM 2012) and sexual dysfunction in women (Wing et al., Diabetes Care 2013).
  • Translating the DPP Lifestyle Intervention for Weight Loss Into Primary Care (Ma et al., JAMA Intern Med 2013): For background, the study randomized patients to a coach-led intervention given in a group format, a home-based intervention, or usual care. The home- and group-based interventions were adapted from the DPP lifestyle program. Dr. Buse showed fifteen- month weight loss from the study, commenting that the impressive responses to the DPP-based interventions suggest that interventions are being successfully translated to provide meaningful weight loss in the clinic and non-clinic environment.
  • Primary Prevention of Cardiovascular Disease with a Mediterranean Diet (PREDIMED; Estruch et al., NEJM 2013): Dr. Buse described PREDIMED as “arguably the study that rocked my world the most this past year.” He remarked that the study findings suggest diet composition and quality do have important influences on health.
    • In this randomized control trial, 7,441 people with no CV disease at enrollment but a high CV risk, were assigned to three dietary interventions: a Mediterranean diet supplemented with nuts, a Mediterranean diet supplemented with extra-virgin olive oil, or a control diet (in which they were given advice on a low-fat diet). The primary endpoint assessed was a composite of myocardial infarction, stroke, and death from CV causes. Participants had a median follow up time of 4.8 years (7% drop out rate).
    • Compared to the control diet, the multivariable-adjusted hazard ratio was 0.72 in the Mediterranean plus nuts diet and 0.70 in the Mediterranean plus oil diet (p=0.01 and 0.03, respectively). When considering both Mediterranean groups, the adjusted hazards ratio was 0.71 compared to control (p=0.005). Further, explained Dr. Buse, given that the baseline diet was similar to the Mediterranean diets, the Mediterranean diet intervention could potentially have even greater benefit in individuals currently eating a Western diet.


Linda Siminerio, PhD (University of Pittsburgh, Pittsburgh, Pennsylvania)

Dr. Linda Siminerio addressed the important topic of provider-patient communication. She evidenced that physician empathy was critical to patients’ care satisfaction. Of note, a study in patients with diabetes by Del Canale et al. suggested that patients of physicians with higher empathy scores had a lower rate of acute complications. Further, physicians’ understanding of patients’ beliefs was positively associated with better self-care practices, including improved diet and self-monitoring of blood glucose (Academic Medicine 2012). Dr. Siminerio also presented data highlighting the discordance between what patients want in their relationship with providers and what they actually receive (Alston et al., Institute of Medicine Discussion Paper 2012): 1) eight in 10 people say they want their health care provider to listen to them, but only six in 10 say this happens; 2) less than half of people say their provider asks about their goals and concerns for their health; and 3) nine in 10 people want their providers to work together as a team, but only four in 10 say this happens. Her presentation underscored that effective physician-patient communication doesn’t just transfer information; it does so in a way that engages the patient in shared-decision making. Said Dr. Siminerio, “Health information knowledge doesn’t necessarily translate to action. If that were true, there wouldn’t be a single physician in the world with a high BMI…”

Symposium: Education Recharged–Diabetes and Technology


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

Dr. Satish Garg began his talk by reviewing the growing health and cost burden of diabetes. “The disease is exploding,” he said. “…If you really look at the data, it really shows the majority of the cost is not with the drugs or the devices. It is with the services and taking care of the complications.” Dr. Garg commented that many patients do not meet ADA’s A1c target and attributed this, in part, to a failure to limit hypoglycemia. He believes that more patients would accept intensive insulin therapy in the absence of hypoglycemia risk. Dr. Garg next explored available technologies that have the potential to improve glycemic control and reduce hypoglycemia, paying particular attention to CGM. He evidenced that CGM can benefit both patients with type 1 and 2 diabetes in both good and poor control (Garg et al., Diabetes Care 2006); however, he recognized that there are barriers to use, including the lack of proper patient education and the cost of CGM. As to the latter, he pressed that organizations need to rally to gain a CMS reimbursement code for CGM. Transitioning to emerging technologies, Dr. Garg discussed the day-old publication of the ASPIRE In-Home study, which showed that low glucose suspend (now called threshold suspend) decreased nocturnal hypoglycemic events. See our write up of Medtronic’s ASPIRE In-Home poster for detail. The importance of downloading data and the need to improve diabetes curriculum in medical school and primary care residency were also weaved into Dr. Garg’s presentation.

  • Ninety percent of patients with diabetes are not being seen by doctors like us, said Dr. Garg. He explained that PCPs often lack the proper knowledge about diabetes technology and displayed a number of disheartening responses from PCPs in Colorado and Utah when asked about CGM (Bhide et al., DT&T 2013): “I don’t think it’s evidence based”; “I have never seen it”; and “I don’t have documentation to prove it’s accurate and I don’t know about the cost.” Dr. Garg suggested that improving CGM implementation starts with revising the diabetes curriculum in medical school and primary care residency.
  • There is no way we can improve care by spending double the time with patients, he remarked. PCPs spend on average just 21 minutes per visit and in the best-case scenario, explained Dr. Garg, patients will spend four hours per year with an endocrinologist. This pales in comparison to the 8,756 hours of self-management. He believes that this difference underscores the need to find technologies that patients can use to reach their goals.

Questions and Answers

Dr. Ken Ward (Oregon Health & Science University, Portland, OR): I am equally concerned about the problems with knowledge in terms of PCPs. One of the things we do at OHSU is use nurse practitioners trained in diabetes.

A: That’s excellent. Three of the universities – ourselves, Minnesota, and Joslin – we are thinking of creating a one year diabetes fellowship starting next year. There is a huge need in this area, but I agree 100%, the answer lies with the nurse educators.


Lora Burke, PhD (University of Pittsburgh, Pittsburgh, PA)

Dr. Lora Burke talked about how technology can promote self-monitoring of diet and physical activity. Previous studies have shown that when adherence rates decline dramatically over time, though adherence seems higher with technology-based diaries rather than paper logs (Burke et al., Am J Prev Med 2012). Dr. Burke and her colleagues are currently studying a smart-phone-based self-monitoring software in people who are trying to maintain weight loss. The study’s first 18 patients had relatively high rates of adherence at one year: 66-100%. Several dozen more patients will be studied before the grant ends in two years. Dr. Burke plans to use this study’s data to augment the self-monitoring software with automated feedback – a feature that has been shown to enhance behavior change (Burke et al., Am J Prev Med 2012). We are curious to see how these technologies might ultimately be related back to changes in health, which does not seem to be an emphasis of the study so far; during Q&A, Dr. Burke said that the researchers have focused on adherence to self-monitoring rather than actual weight loss.

Questions and Answers

Q: What is the timeline of the study you are working on?

A: The first group just finished. There are 150 patients total, but we are doing relatively small groups at a time because the intervention is so intense. The grant ends in two years. However, because every group is so different, we plan to start publishing reports this fall. There is a lot of data. It’s not an efficacy trial, so we are adjusting as we go.

Q: For the 18 patients who completed the study in the first year, what was the weight loss?

A: We have looked at that, but we are so focused on the ecological momentary assessment [phone-based self-monitoring], that I can’t tell you here.


Erin Poetter Siminerio, MPH (Office of the National Coordinator for Health Information Technology, Washington, DC)

Ms. Erin Poetter Siminerio spoke passionately about advancing consumers’ use of electronic health tools. She focused especially on Blue Button, a program that allows patients to electronically access their clinical and claims data. Since it was begun in 2010 by the Department of Veterans Affairs, Blue Button has been adopted by other federal organizations (e.g., Department of Defense, CMS) and major private insurers (e.g., Aetna, United), so that 88 million Americans can now download their data. Blue Button is now run by the Office of the National Coordinator for Health Information, and an updated iteration (Blue Button Plus) was launched in February 2013. Ms. Siminerio and her colleagues are working creatively to encourage the use of Blue Button and other electronic health tools by patients, healthcare providers, and major healthcare companies: one ongoing effort is to develop open-access graphical templates so that health data can be viewed in more user-friendly formats. We appreciated Ms. Siminerio’s emphasis on empowering patients with their healthcare data (emphasis hers), and we resonated strongly with the Eliot Joslin quote on her conclusion slide: “The patient who knows the most lives the longest.”

Questions and Answers

Q: It is extremely challenging to get information about insurance companies’ formularies. Will there be a way for patients to get this information?

A: We are not quite there yet; our current focus is still driving adoption of the current system.

Q: There are a lot of companies in this building that view device data as their strategic advantage and have put up a lot of walls on giving patients this data. How might we make better progress on getting this data into developer’s hands, so that we can have actionable information?

A: There is a growing movement from many patients. I have heard a lot of interest, and I think some institutions are opening up. Consumers play a powerful role.


Ruth Weinstock, MD, PhD (SUNY Upstate Medical University, Syracuse, NY)

In this presentation on telemedicine for diabetes management, Dr. Ruth Weinstock reviewed several studies in which her clinic has used phone- and computer-based interventions to improve patients’ health. With the randomized, controlled IDEATel study, Dr. Weinstock and colleagues used a simplified computer interface to hold videoconferences with patients in underserved areas of New York City (n=775) and upstate New York (n=890). Encouragingly, the telemedicine intervention helped these old, ethnically diverse patients to meet personal health goals, reduce their A1c, and improve across a variety of other health and psychosocial outcomes (Weinstock et al., Diabetes Care 2011). Dr. Weinstock’s most recent effort has been the SHINE Study, results of which were announced earlier at ADA 2013. In SHINE, the Syracuse team found that phone-based implementation of the Diabetes Prevention Program led to significant two-year weight loss, with better weight-loss maintenance in patients who received group-based calls rather than individual calls. In her conclusion, Dr. Weinstock suggested that future telehealth efforts should identify which patients are likely to benefit most from telemedicine, focus on people with the highest burdens and barriers to care, shape technologies to match patient needs, determine cost-effectiveness, and integrate telehealth into routine electronic medical records.

-- by Adam Brown, Eric Chang, Hannah Deming, Jessica Dong, Sam Haque, Stephanie Kahn, Kira Maker, Hannah Martin, Rajiv Narayan, Nina Ran, Lisa Rotenstein, Joe Shivers, Tony Thaweethai,