February 20-23; Berlin, Germany; Day #1 Highlights – Draft

Hello from ATTD 2019 in Berlin – the 12^th edition of this annual gathering of technology and (increasingly) therapy. Day #1 highlights are enclosed below, and our preview of the next three days is posted here.

Diabetes Technology Highlights

1. Dr. Lutz Heinemann on Diabetes Tech in 2025: Lower Cost CGM (<$2-$3/day), More CGM in Type 2, Telemedicine, Decision Support; ~3,000 Patients on DIY AID Systems Globally

Science Consulting Neuss CEO Dr. Lutz Heinemann kicked off ATTD 2019 in fantastic fashion, headlined by his predictions for diabetes tech in 2025:

• For type 1, he anticipates: (i) the availability of cheap and reliable CGM with an <8% MARD and ~<$3/day; (ii) “affordable” AID systems at ~$11/day; (iii) “doc on demand” providers via telemedicine as part of patients’ standard care; and (iv) most therapeutic aspects of care facilitated by data download to the cloud and clinical decision support systems (CDSS). No surprises there, though we’d be interested to know the assumptions behind AID at $11 per day (~$330 per month, ~$4,000 per year) – if that estimate includes CGM and insulin, it’s a massive step down in costs relative to current systems.

• For type 2, Dr. Heinemann expects: (i) SMBG to be widely replaced by CGM with <10% MARD and ~<$2/day (implying a different lower-cost, slightly less accurate product than for type 1); (ii) increasing uptake of once-weekly basal insulins; and (iii) wide use of CDSS (clinical decision support systems – we’re trying to help everyone get used to this new-ish abbreviation).

• Supporting these claims, Dr. Heinemann gave several take-home trends:

  • Declining numbers of endocrinologists and diabetologists are at odds with the rising diabetes epidemic, necessitating the transfer of responsibility to machines and algorithms. 80% of diabetes-related procedures are routine tasks, which clinical decision support systems could primarily undertake, allowing physicians to add their own recommendations informed by their relationships with patients and patient circumstances. Notably, algorithms could also be used to detect the ~one-fifth of patients that require direct and fuller attention of a physician. As Dr. Heinemann pointed out, these algorithms aren’t necessarily intended to enable the treatment of more patients within the same period of time, but rather to empower providers with more time to talk to each patient. Given the trends in numbers of providers, this is still a concern – who is going to take care of everyone with diabetes?

  • While better devices have pushed major success in the ~$2.9 billion CGM market, Dr. Heinemann characterizes current CGM systems as still “miles off from ideal.” To this end, he labelled cost, sensor wear time, pain, and skin reactions as major areas of improvement, as well as the establishment of an accuracy standard such as that seen already with SMBG systems. (iCGM is sort of the de facto accuracy standard now, as we assume all companies will move to that over time given the regulatory and speed advantages. We also think that due to arrows, accuracy overall is less important to some patients.) Looking to the future, Dr. Heinemann was particularly excited about the Dexcom and Verily “G7,” slated to launch in late 2020, followed by a full rollout in 2021 (per JPM). However, he was skeptical that the project will stick to this timeline to launch it next year (he did not mention the broader rollout in 2021). At JPM, CEO Mr. Kevin Sayer shared that Dexcom expects to “finalize” G7 this year and provide “very clear timing” on the plan. With the amended Verily collaboration agreement and consistency between 3Q18 and the Investor Day, we think things are feeling clearer on this next major pipeline launch. Dexcom often gets products approved faster than expected, though given the massive organizational disruption for G6, there is a lot to get ready for G7. 

• Dr. Heinemann asserted that ~3,000 people globally are currently using DIY insulin systems (Loop, OpenAPS, or Android APS). We’ve previously heard an estimate of ~2,000 Loop users, and this sounds in the ballpark taking into account all three systems. It also shows the great desire for more advanced and personalized AID; as Dr. Heinemann put it, “people with diabetes won’t wait for innovation.” That said, the DIY movement has also started to make regulatory waves, with Tidepool and Jaeb beginning an observational, virtual study of Loop last month to support FDA submission. (Adam is in this study and just mailed back the A1c kit – very cool!)

• Dr. Heinemann also pointed to the environmental waste associated with diabetes products, showing a full trash bag from diabetes product waste accumulated in just two weeks. To this end, he highlighted that each Dexcom G6 inserter creates 80 g of plastic waste and each Abbott FreeStyle Libre sensor 71 g. For the latter, this equates to over 1 billion pounds of plastic created each year (!) – assuming 1.3 million users inserting two sensors per month. Further data from Dr. Heinemann on this topic are currently under review for the Journal of Diabetes Science and Technology.

• What about exciting therapy innovation? Dr. Heinemann specifically pointed to glucose-responsive, or smart, insulin (GRI) – while he doesn’t believe a product will reach the market soon, he does anticipate that GRI may pose a threat to diabetes technologies such as a fully closed-loop. We think the prospects of GRI are a bit long-term (10+ years out) to make a judgment call at this point. After the first-ever clinical candidate was discontinued by Merck due to inadequate phase 1 results, GRI has experienced somewhat of a renaissance with investment from JDRF and Novo Nordisk – Sanofi has also made some major investments. Still, development of an effective GRI does comes with wide-ranging technical challenges that are currently unsolved, as was highlighted in a 2016 JDRF/Helmsley Charitable Trust gathering on smart insulin. Perhaps most importantly, a molecule must be programmed sensitively toward a narrow and physiologically appropriate glucose range, which is no small feat; cost and insulin receptor kinetics are also key. We’d bet on no technology emerging for at least the next decade.

• Digitalization will continue to change our world dramatically. According to Rock Health, investment in digital health surpassed $8 billion in 2018, and with major companies such as Google and Apple beginning to venture even further, diabetes technology is ripe for disruption (as it has been for many years). For these companies, according to Dr. Heinemann, digital health is a market of the future.

2. MiniMed 670G Workshop: Simplicity for HCPs vs. Patient Complexity? Crystal Clear Goals: >70% TIR, >80% Time-in-Auto Mode, Focus on Meal Boluses

A standing-room only, practical workshop on using the MiniMed 670G highlighted an interesting dichotomy: simplicity and clarity for HCPs vs. complexity for patients. The workshop covered the system’s features and onboarding process, highlighting that healthcare providers do not have many knobs to turn in the first-gen hybrid closed loop – they can tweak insulin-to-carb ratio (the big one) and active insulin time (minimal effect). In 670G case after case, the recommended thought process was the same: (i) look for >70% time-in-range (70-180 mg/dl); (ii) look for >80% time-in-Auto Mode; and (iii) troubleshoot if either metric is too low. To get higher time-in-range, the solution was always tightening the insulin-to-carb ratio and/or encouraging pre-meal bolusing. To get more time in Auto Mode, HCPs must identify common exit reasons (usually SMBG calibrations; first picture below) and coaching patients to avoid them. Medtronic framed the 670G management process as pretty straightforward for HCPs – two metrics to watch and a small basket of solutions to fix them. “It’s a different job for us” said Medtronic’s Dr. Ohad Cohen (Director of Medical Affairs, EMEA) – this is particularly true in light of less needed focus on hypoglycemia. This was a key message to deliver to providers in the first hands-on workshop since the system’s launch last fall in Europe. Dr. Cohen also shared more real-world 670G data, covering time-in-range outcomes in n=55,000 patients and up to October 2018. Results (second and third pictures below) have impressively mirrored the pivotal trial at ~73% in 70-180 mg/dl and 2.4% in hypoglycemia. Real-world data in MDI users and no prior CGM experience are impressively similar, albeit in tiny subgroups.

• 670G users, however, must still cope with a lot of fingersticks, jargon, mode juggling, icons, and alarms. The one that immediately stood out was fingerstick calibration – Dr. Cohen said today that when the 670G first launched in the US, average fingersticks were six per day! The 670G launching internationally and “switching” over in the US moves this down to ~four fingersticks per day, presumably via the transmitter software upgrade that reduces unnecessary blood glucose requests (launched as of December). Missed calibration and prolonged high blood sugars were tied for the most common reasons for Auto Mode exit (15% of the time; see below), followed by prolonged max delivery (10%), sensor algorithm under-reading (10%), and minimum delivery timeout (9%). Dr. Cohen framed most of these as “safety” constraints for a first-gen system, which is a very fair point from our view (first generation is always far harder – many remember – but many don’t! – Dexcom’s STS, as one example) and will certainly improve in next-gens like the MiniMed 780G. But today’s workshop reminded us that a no-calibration AID system driven by G6 or FreeStyle Libre is going to eliminate much of the complexity and frustration in 670G. We also hope to see systems move away from “modes” (Manual Mode, Auto Mode, Safe Basal, Suspend Before Low, Suspend on Low, etc.), which should help with training and user experience. We were also reminded of some of the odd design decisions in the 670G: an inability to see the basal insulin profile at any given time (it’s only shown as little pink dots on a secondary screen), exiting Auto Mode precisely at the times where it may be most needed (extreme highs and lows), burying vital information in nested menus (e.g., the important Auto Mode readiness checklist and on button is three screens deep), correction bolus recommendations cannot be adjusted by the user, etc. Dr. Anna-Kaisa Tuomaala (Helsinki University Hospital) said three face-to-face visits are recommended for non-Medtronic pumpers to learn the 670G, and it takes some of her patients up to two months to learn how to use it. Obviously this is a first-generation product (CGM had those too, as noted, as did pumps!) and some 670G experiences are still extremely positive. Plus, the system is performing well on outcomes, which bodes well for next-gen less-burdensome options (including Tandem’s Control-IQ, Insulet’s Horizon, Bigfoot Loop, Tidepool Loop, and Medtronic’s own 780G).

• The 670G pivotal study in 2-6 years olds will be presented on Friday of ATTD.

3. LifeScan Symposium: Physician Focus Groups on Future of SMBG; Bastian Hauck Delivers a Patient’s Perspective on SMBG; Prof. Barnard’s Sage Advice for Manufacturers

In a LifeScan-sponsored symposium, UCSD’s Dr. Steve Edelman, Prof. Katharine Barnard, and dedoc’s Mr. Bastian Hauck overviewed the future of BGM: In short, it’s not going anywhere for most patients, and the future of fingersticks has to be based in consumer-centric design, seamless connectivity, and decision support. (That sounds a lot like CGM!)

• Dr. Edelman kicked off the presentations with a summary of findings from TCOYD-, CWD-, and ISPAD-sponsored focus groups that took part at ATTD and ADA 2018; participating clinicians (many with diabetes) were asked to ruminate on the future role of SMBG. Dr. Edelman hopes to publish these findings soon. Unsurprisingly, the clinicians expect that BGM will remain in high demand for individuals who can’t access CGM in the US, many type 2s who won’t need to rely on CGM 24/7, as well as the majority of the world – particularly countries like China and India – for many years to come. When asked what type of evidence they’d look for to justify the usage and reimbursement of connected BGM, respondents underscored a desire for real-world, pragmatic data, changes in patient behaviors/attitudes, as well as a slew of clinical/economic outcomes (A1c improvements reductions in hypoglycemia and/or ER visits/hospitalizations, and improvements in time-in-range). The clinicians emphasized a need for decision support tools, structured testing vs. “worthless testing,” highly usable technology for patients and healthcare providers, as well as adding minimal burden in terms of healthcare team time and staff. On this last point, Dr. Edelman commented, “A big mistake a lot of companies make is assuming physicians have a lot of time to learn new things.” Provider have less time than ever – alongside rising burnout – and the big hope is for clinical decision support tools to simplify visits. Alongside that is remote/virtual care “clinics” and coaches, which might be able to fill the gaps.

• Mr. Hauck, speaking only from notes and without slides, rattled off a list of desires for BGM in the era of CGM.

  • “Make blood glucose meters sexy. I want one I really like to carry around…. If you were producing cellphones the way you produce BGMs right now, everyone in here would be out of business, because I wouldn’t buy it…design matters.” At the outset of his talk, he recalled a 2012 talk in which he warned manufacturers in attendance, “If you don’t watch out, if you don’t design your next BGM with consumers in mind, my next BGM will be my iPhone.”

  • “For me it’s really about open data; data that goes flawlessly, fluently, seamlessly from users to payers, to providers, and back. From hardware, software, to the cloud and back … I have an appointment with my diabetologist every three months here. That’s not because I need to see her every three months – maybe I do in two months, or not for next six months. I only go to get insulin. It’d be much smarter to have a pattern recognition algorithm that calls me when an algorithm detects something is not quite right with my blood glucoses.”

  • He wondered why we don’t have automatic bolus calculators for MDI, whereas we do for pumps. Of course, Companion Medical’s InPen is available in the US and CE marked, with a planned 2019 launch, but only ~2,000 people are using InPen in the US. It’s still early days for MDI dose capture, though Lilly’s and Novo Nordisk’s entries in the near-term could change that in a hurry.

  • “EHR; I don’t understand why it’s not working. All of this data should be in the EHR, along with all kinds of other data.”

  • “The interface of tomorrow will not be an app, something you click on, look at and push buttons. It’ll be something between cloud and messenger, Siri and Alexa…maybe a  reminder on the fridge, on the TV when I sit down to watch a movie, or maybe on my alarm clock if it’s something I need to do when going to bed. The great thing about open data is it’s kind of everywhere. The idea of a ‘Homespital’ – a mix of being in the home and in hospital all the time, 24/7. That’s the perfect integrated solution for diabetes management.”

  • “I don’t see why we couldn’t do something like trends/curves/alarms/reminders in something as simple as BGM. It won’t be as good as CGM, but it could be better than what we have now.”

• Prof. Barnard reiterated many of Dr. Edelman and Mr. Hauck’s points, and added a few particularly poignant musings. For one, she noted the absurdity in the fact that when we have a new tool that promises to reduce burden for patients, “we make them jump through all kinds of hoops to get it…it’s a bit weird. We shouldn’t be making people jump through hoops to take care of their healthcare needs.” Prof. Barnard also advised manufacturers that “one size fits nobody very well, but a single device with a broad range of functionality fits many, many people.” (FreeStyle Libre is probably the best recent example of the latter.)

• Head of Portfolio Strategy Mr. David DeJonghe and Clinical Affairs Director Dr. Mike Grady doubled down on their presentations from the EASD symposium, highlighting the CE-marked One Touch Verio Reflect (with the Blood Sugar Mentor; launched in France and Germany) and recent data supporting One Touch strip accuracy and outcomes data. To his talk, Mr. DeJonghe added that the One Touch Reveal app is approaching two million downloads. The Mentor meter’s messages are basic pattern recognition, but they are far better than most people get (since most don’t download or look at data). For example, if the meter finds that a user has been high each of the last four days in the evening, it will notify her and her healthcare provider, and ask her if anything has changed (i.e., eating high-carb lunches, eating late lunches, large/unnecessary mid-afternoon snacks, less activity than before, etc.). If it detects hyperglycemia, it might suggest a walk, and if it detects a low or near-low, it will recommend juice and offer to set a reminder to re-check blood glucose in 15 minutes.

• According to Dr. Grady, LifeScan makes five billion strips per year – ~33% of the world’s annual production!

4. Real-World FreeStyle Libre Data: Published on ~50,000 users; Majority of Reductions in Hyperglycemia Achieved within First Two Months; Highest Libre Scanners Achieve 40% Greater Reduction in Time ≤54 mg/dl vs. Lowest Scanners

University of Leeds’ Dr. Ramzi Ajjan shared a slew of published and unpublished real-world data on FreeStyle Libre, continuing a trend (and much of the same data) from ATTD 2018 and ATTD 2017. It’s great to see Abbott churning out real-world data publications from the largest CGM user base in the world – all of it emphasizes that more frequent glucose data leads to better outcomes.

• Real-world FreeStyle Libre data – first shown at ATTD two years ago – has finally been published in Diabetes Research and Clinical Practice from 50,831 readers (i.e., users) and 279,446 sensors, totaling 63.8 million glucose readings. This was notably smaller than the 250,000-user data shared at ATTD 2018; still this is a big data set that is great to get in print. The average user scanned 16 times per day, with those in the highest scanning group scanning 48.1 times/day (three per waking hour!) vs. the lowest scanning group performing just 4.4 scans/day. Scanning frequency was significantly associated with lower time ≤54 mg/dl, lower estimated A1c, and higher time-in-range. Those in the highest scanning group achieved a 40% decrease in time ≤54 mg/dl (26 minutes vs. 43 minutes) and a 1.3 percentage point decrease in estimated A1c (6.7% vs. 8.0%) as compared to those in the lowest scanning group. Per the paper, time-in-range increased from 50% to 70% in the low vs. high scanning groups – a staggering 4.8-hour/day difference. These patterns were consistent across countries too.

• Unpublished real-world FreeStyle Libre data showed that the majority of reductions in time in hyperglycemia (>240 mg/dl and >180 mg/dl) occur gradually over the first two months of sensor wear (first picture below). Sample size was not included. By contrast, the majority of reductions in hypoglycemia are achieved within the first two days of FreeStyle Libre wear (n=14,617 users; second picture an shown at ATTD 2018). This trend for hypoglycemia was consistent at glucose <70 mg/dl and <55 mg/dl, but especially at glucose <45 mg/dl, for which 74% of the total reduction was observed within the first two days. That said, users in this data set were still spending 82 minutes per day under 70 mg/dl; quite a lot and we wonder how that improves over longer duration wearing the sensor. Still – we’ve heard many KOLs suggest less than 4-5% time less than 70, which itself is still about an hour.

• Unpublished FreeStyle Libre real-world data also indicated that scanning frequency sees an initial decline and then stabilizes around the second or third sensor. From the graph below, it appears that users scan roughly 15 times/day, nearly one per waking hour. Sample size was not included, so we’re not sure if it’s from the larger 250,000+ data set. As expected with FreeStyle Libre’s factory calibration, SMBG drops to <1 fingerstick/day and remains there – a good sign of confidence in the accuracy and reliability.

• Real-world FreeStyle Libre data (n=4,793) over six months (12 sensors) demonstrated a similar reduction in time <70 mg/dl as compared to that observed during the IMPACT trial (n=119). It’s encouraging to see such strong correspondence between clinical trial and real-world data – something Medtronic has also shown with the MiniMed 670G. Again, we’d note that in either data set, users were still spending ~2 hours per day (~10%) below 70 mg/dl – far too much. This was also shown at ATTD 2018.

SGLT in Type 1 Highlights

1. Prof. Mathieu Sees Promise in SGLTs for Type 1, But Advocates for Conservative Safety Measures: Prioritize Patient Education; Only Prescribe to Type 1s Looking to Lose Weight

In reviewing the available phase 3 data on SGLT inhibitors in type 1, Professor Chantal Mathieu took a conservative stance, framing these agents as “promising adjunct therapies” while cautioning that “we have to strike the right balance between benefits and side-effects.” She walked through key findings from DEPICT (for AZ’s SGLT-2 dapagliflozin), inTandem (for Sanofi/Lexicon’s SGLT-1/2 dual inhibitor sotagliflozin), and EASE (for Lilly/BI’s SGLT-2 empagliflozin). As a lead investigator for the DEPICT program, Prof. Mathieu described how all trial participants received extensive education around DKA – certainly more than the average type 1 patient receives in the real world. For evidence that this education paid off, she pointed to exceptionally low rates of DKA in the placebo arm of DEPICT 1 (0% after 24 weeks and 2% after 52 weeks), which came in well below the ~8% DKA incidence seen in the T1D Exchange. There were 27 total episodes of DKA in DEPICT 1 (22 on dapa vs. 5 on placebo), and although several of these were attributed to pump failure or a missed insulin dose, Prof. Mathieu emphasized that many events were unexplained. She seemed to suggest that comprehensive DKA education is critical before any patient with type 1 diabetes starts SGLT treatment, and the question remains, how can regulators enforce this?

• Prof. Mathieu underscored that SGLT inhibitors should be used very carefully in type 1s where weight loss is undesirable, though in many patients weight loss will be a positive outcome. She presented this as a safety consideration, as preventing undesired weight loss could also decrease risk for DKA (ostensibly by maintaining insulin requirements) and unpredictable glucose fluctuations. Early in February, CHMP recommended AZ’s dapagliflozin (Forxiga) for EMA approval in type 1s, noting that “this treatment should only be initiated and supervised by specialist doctors” and that patients “should be educated about risk factors for DKA and how to recognize its signs and symptoms.” Moreover, CHMP endorsed an indication only in type 1s with overweight/obesity (BMI ≥27 kg/m²), likely because AZ enforced a lower-level BMI cutoff in enrolling the DEPICT trials (we suspect that higher baseline body weight comes with greater insulin requirements, and maintaining sufficient insulin doses while avoiding hypoglycemia is an important protective factor against DKA). The inclusion/exclusion criteria for inTandem1 make no mention of BMI, though ultimately, baseline BMI was ~28 kg/m² on average (indicating overweight) in both clinical programs. We were somewhat surprised to learn of CHMP’s BMI-based decision, since there was no consideration of a weight-based indication at the FDA Advisory Committee for sotagliflozin just a couple weeks prior, though we’re now wondering whether the BMI criterion was something explicitly put forth in AZ’s regulatory application but not Sanofi/Lexicon’s. Overall we think it’s a very smart place to start, because it means that the fear of “opening the floodgates” as expressed by some wont’ happen. We’re awaiting FDA’s regulatory ruling on sotagliflozin by March 22, 2019. Using dapagliflozin exclusively in type 1s with overweight/obesity is a more conservative approach than approving for all BMIs, and as the new indication is rolled out in Europe, we’ll be looking to see if this has a positive impact on population-level DKA rate. While some might’ve been disappointed by a more conservative regulatory approval for this new class of adjunct type 1 therapy (given the tremendous unmet need), we’ve become increasingly aware of the population-level threat of DKA (a major theme at the sotagliflozin Ad Comm) as have most and we have only characterized the approach as a very smart one (since it’s also modifiable). It’s smart to proceed with caution, and to this end, we appreciated Prof. Mathieu’s suggestions for exercising the utmost safety in prescribing SGLT inhibitors to people with type 1 diabetes as a starting point. As Dr. John Buse put it at ADA, “I’d rather that some people just not get SGLT inhibitors based on our recommendations, rather than see an epidemic of DKA after these drugs are approved. I’d rather the 20% of patients who could really benefit get this drug.” We do think many will want it who do not “need” to lose weight so this may be an ongoing check.

• During her discussion of EASE 3, Prof. Mathieu shared measured enthusiasm for the 2.5 mg dose of empagliflozin. This very low dose of SGLT-2 inhibitor was not associated with heightened DKA risk (2 events in the 2.5 mg empa arm vs. 3 events in the placebo arm), but Prof. Mathieu warned that these numbers were collected over only six months. She reminded the audience that there was no significant DKA signal in six-month DEPICT 1 data either, but the risk appeared by the one-year mark. She highlighted the persistent DKA signal with 10 mg and 25 mg empagliflozin. Perhaps most importantly, Prof. Mathieu explained how lower risk also means fewer benefits: 2.5 mg empagliflozin was “at the edge of showing enough of an effect on glycemic control and body weight” (i.e., A1c drop and weight loss were more muted with 2.5 mg empa vs. the higher doses of Jardiance). This comment captured Prof. Mathieu’s overarching theme of needing to balance benefits and side-effects. After all, if a low dose of empagliflozin doesn’t bring about clinically-meaningful changes in A1c, time-in-range, or weight, is it worth any chance of elevated DKA? This is still very much an open question in our view (especially because the data certainly did not show no impact at a low dose), and even as SGLT inhibitors for type 1 approach the market, we see big opportunities for further research ahead. We keep coming back to, for example, cardiovascular outcomes trials in type 1 and how terrific it would be to see this approach take hold.

2. Renal Protection in Type 1? Dr. Groop Cautiously Points to Renal Hemodynamic Changes – Also Observed in Type 2 – as Early but Promising Suggestion of SGLT-2 Mediated Nephroprotection

University of Helsinki’s Dr. Per-Henrik Groop offered mechanistic data indicating that the renal protection of SGLT-2 inhibitors well-established in type 2 diabetes could quite possibly translate to both type 1 diabetes and non-diabetic CKD, with the caution that clinical outcomes data are still to come. Most importantly on the type 1 front, Lilly/BI’s EMPA-KIDNEY renal outcomes trial (n=~5,000) is now enrolling all comers with kidney disease, including type 1s, type 2s, and those without diabetes who meet the CKD criteria (expected completion is June 2022). While it remains to be seen how large the study’s type 1 cohort will be, the expansive inclusion criteria are undeniably exciting, will offer the best evidence to date on long-term outcomes with SGLTs in type 1, and stand in contrast to both (i) J&J’s completed CREDENCE renal outcomes trial (type 2 diabetes only) and (ii) AZ’s ongoing Dapa-CKD trial (CKD with or without diabetes, but no type 1) – see below for a rundown of renal outcomes trial designs, including eGFR criteria. Kudos to Lilly for figuring out how to have type 1s in these long-term outcomes trials.

Despite his assertion that “we actually don’t know” what SGLT-2s will do to renal function in type 1s, Dr. Groop reviewed preliminary but compelling clinical data offering strong support for Lilly/BI’s decision to include this population in EMPA-KIDNEY. Namely, in type 1s, eight weeks of empagliflozin treatment has been shown to both (i) improve renal hyperfiltration (i.e., reduce glomerular filtration rate); and (ii) reduce interglomerular pressure by ~6-8 mmHg, in patients with existing hyperfiltration during both euglycemia and hyperglycemia (p<0.01 and p<0.0001 vs. baseline, respectively). No negative renal effects have been observed in type 1s with normal renal function. Moreover, Dr. Groop continued, it seems the reduction in renal hyperfiltration is driven by a significant reduction in renal blood flow and an increase in renal vascular resistance (both p<0.001 vs. baseline at 8 weeks). These last two effects are key, he showed, because they’re “consistent with afferent arteriole vasoconstriction” – the key mechanism of the “Tubular Hypothesis” proposed by Drs. Hiddo Heerspink, David Cherney, and others in a key 2016 paper in Circulation – see the full cascade of effects outlined in the second figure below. As such, it seems that SGLT-2s have a similar effect on the renal physiology of people with type 1 diabetes as they do on those with type 2, lending promise to the use of SGLT-2s to slow the progression of renal disease in type 1s.

• For the most recent data on SGLT-2s for renal protection in type 2 diabetes, see this meta-analysis of all three completed CVOTs (EMPA-REG OUTCOME, CANVAS, and DECLARE) in The Lancet, plus this compelling commentary from Drs. Subodh Verma and Javed Butler at AHA 2018. Additionally, we point you to recent post-hoc analysis of pooled DEPICT data (dapagliflozin in type 1), which demonstrated a dose-dependent reduction in urinary albumin creatinine ratio (UACR) in patients with albuminuria (defined as UACR ≥30 mg/g) at baseline (n=251) – preliminary and short term data, but promising nonetheless.

3. Dr. Tadej Battelino Criticizes EMA Indication for Dapa in Type 1s Only if BMI ≥27 kg/m²; Explores Potential CV Benefits to SGLT Therapy in T1D

Conference co-chair Professor Tadej Battelino was critical of the EMA’s potential new indication (if accepted) for SGLT-2 inhibitor dapagliflozin (Forxiga), which authorizes its use in type 1s only if they have a BMI above 27 kg/m². He argued that the entire type 1 diabetes population could benefit from an adjunct therapy that offers additional A1c-lowering, improved time-in-range, and weight loss – not to mention possible cardioprotection. We would not disagree but just might point out that to start, a smaller group is advised to get the therapy. To illustrate the substantial unmet need for CV risk reduction among type 1s, Dr. Battelino displayed data (image below) on greater all-cause death, CV death, and hospitalization for CV events compared to matched controls. Prof. Battelino established the relationship between glucose variability (and especially postprandial glucose variability), oxidative stress and endothelial dysfunction, and elevated CV morbidity/mortality. The jury’s still out on the precise cardioprotective mechanisms of SGLT-2 inhibitors (in type 2 or type 1 diabetes), but Prof. Battelino outlined one hypothesis in which these drugs reduce glucose variability, thereby alleviating oxidative stress and endothelial dysfunction, which brings down CV event rate, though other well-regarded hypotheses focus on other mechanisms – though, surely, these are not mutually exclusive. He added, explicitly, that glucose variability is not correlated with obesity, so limiting dapagliflozin’s use to type 1s with BMI ≥27 kg/m² is an oversight of the most meaningful benefit an SGLT-2 inhibitor could have for type 1s – CV risk reduction. Prof. Battelino acknowledged the uncertainty around mechanism of CV benefit, but focused attention on what is certain: “If you ask about the SGLT’s cardiovascular mechanism, the honest answer is ‘we don’t know,’ but we do know that people with type 1 diabetes are only getting worse with metabolic control and consequently CV outcomes.” While many say the exact reasoning behind the committee’s decision isn’t clear to us, it seems likely that it was motivated by safety considerations rather than efficacy considerations – we believe it is a very smart starting point and presumably could broaden if all goes well. We’ve heard from thought leaders that insulin sensitivity declines at higher BMI, which could protect against DKA. Insulin requirements are also greater at high BMI, and taking sufficient insulin alongside an SGLT-2 inhibitor (while avoiding hypoglycemia) is certainly important in preventing DKA.

• Prof. Battelino touched on several other hypotheses for the mechanism underlying an SGLT-2 inhibitor’s CV benefit as well: shifting energy metabolism to increase circulating ketones; reducing cardiac afterload; relieving inflammation; decreasing blood pressure; and providing nephro-protection, which is closely tied to CV health. We are very excited to hear more interest in outcomes trials and type 1.

• He also pushed for a pediatric indication for SGLT inhibitors as adjuncts to insulin, citing evidence to show that adolescents and children are “a very vulnerable group in type 1 diabetes.” As far as we’re aware, no large-scale clinical trials have been launched yet to investigate these agents in type 1s under 18 years-old. We imagine manufacturers are waiting to see how the drugs perform on the market for adults, especially considering the safety concerns surrounding DKA.

4. Prof. Danne Throws Weight Behind Blood Over Urine Ketone Testing, Highlights Need for Outcomes Data Supporting CGM-Based Metrics; Casts Potential of Closed Loop + Adjunct Therapy in Positive Light

Professor Thomas Danne made a case for the adjunct use of SGLT inhibitors for type 1 in the presence of appropriate technology, also giving a nod to the future consolidation of adjunct therapies with closed-loop insulin delivery. In the wake of the publication of the landmark consensus on DKA risk mitigation with SGLT inhibitors in type 1 diabetes (see Diabetes Care), Prof. Danne – who led the consensus effort with ATTD – was tasked with addressing the intersection of SGLT-2s and technology, a talk he opened by asserting that the field can make adjunct therapy work through technology. Two threads of this argument emerged during Prof. Danne’s presentation:

• Continuous glucose monitoring can be used to demonstrate the full benefit of adjunct SGLT use, and it may even drive the use of adjunct therapy. With the rise of CGM, patients have 24-hour data on their blood glucose levels and are increasingly looking for ways to avoid postprandial spikes and hypoglycemia. The reductions in glucose variability offered by SGLTs are a huge draw for patients, and Prof. Danne emphasized the potential of adjunct therapy to help – “if we can do it wisely.” To be sure, there’s a strong relationship between the outcomes beyond A1c movement and the push for adjunct SGLT use in type 1, and Prof. Danne posited that considering just two values – time in range and time below range – could “to some degree … explain the whole glycemic profile.”

  • On balance, Prof. Danne was far less optimistic about the “uncharted ground” the field stands on with regulatory agencies and payors. Despite high-profile analyses (specifically, Drs. Roy Beck, Rich Bergenstal, et al.’s recent DCCT analysis) that have linked derived measures of time-in-range to long-term microvascular complication risk, he said, the field still needs to make a concerted effort to ensure CGM-derived metrics considered most valuable by the field are shown to be valuable at the level required by other stakeholders. As he put it, “Today we don’t have the data, and there’s a desperate need for the scientific community to prove this.” He didn’t elaborate on this point, but we imagine Prof. Danne envisions a DCCT-like, outcomes based study using CGM.

• Ketone monitoring technology, with a strong preference for blood ketone monitors, can make the use of SGLTs in type 1 safer. While some preference for blood over urine ketone monitoring has emerged over the past year, Prof. Danne’s weighing of the pro/con profile of each (see image below) laid bare the superiority of blood ketone testing. Still, he admitted, there is no scientific data showing that one can’t safely use an SGLT inhibitor with urine ketone testing alone (just as so many questions in this arena haven’t been answered in a data-driven way). However, the greater precision of blood testing translates to much clearer direction on what to do at any given ketone level. If cost is not a barrier, blood ketone monitoring should always be chosen not only for on-treatment monitoring, but also for establishing a baseline ketone level and ensuring the patient knows how to measure ketones. Ultimately, he said, “We have to use the technology and move away from urine ketones.” While we do understand this view, the access aspect can be challenging; one patient we know recently paid $600 for 100 blood ketone strips.

• On a final note, Prof. Danne looked toward the future of type 1 care, “We can’t be here at ATTD and not talk about closed loop,” referencing the single-day DAPA-DREAM pilot study originally presented at IDF 2017 (also see this EASD 2018 poster). As background, the crossover study combined DreaMed’s fully closed loop with twice-daily dapagliflozin or placebo, testing unannounced mixed meals in 15 young adults (ages 18-20). The data show an additional very compelling 2.8 hours per day in range (70-180 mg/dl), 100% time in range overnight, and a 40% reduction in bolus insulin with dapagliflozin, though in an admittedly very small and short study (see full results just below). Larger studies will be needed to determine how closed loop use might impact DKA risk (pump use is a well-recognized risk factor from phase 3 programs of SGLTs in type 1) and whether new, unique algorithms would be beneficial in this use case – but it’s certainly encouraging to see that SGLTs can likely further improve the advances poised to come with closed loop.

-- by Adam Brown, Ann Carracher, Brian Levine, Payal Marathe, Peter Rentzepis, Maeve Serino, and Kelly Close