Hello from Washington DC, where the AACE/ACE Consensus Conference on CGM just wrapped up. The one-day meeting gathered a who’s-who of CGM thought leaders and influencers on a Saturday at 8AM to discuss the evidence supporting the technology (“what’s settled?”) and to clarify areas of disagreement and where more data is needed (“what is not settled?”). The basis for the nuanced discussion was a very simple fact: CGM is a beneficial technology, but few patients are using it – why? Device cost and product shortcomings are the most obvious patient barriers to CGM uptake, though this meeting focused on broader issues related to healthcare providers and payers.
Dr. Bruce Buckingham’s comprehensive keynote on the state of CGM (see below) was the only formal lecture-style presentation; this meeting was all about discussion among patients, professional societies, industry, and payers/government. Below, we’ve enclosed key takeaways from the day’s commentary, including major needs in CGM, points of consensus, areas of debate, and our views on what consensus document home runs might look like. See the tables immediately below for quick highlights; the detailed discussion and commentary goes more in depth on each theme. Below that, you will find coverage of Dr. Bruce Buckingham’s keynote and our key questions.
AACE/ACE is expected to share a follow-up press release this week, and a more detailed statement will ultimately be published in Endocrine Practice. Our sincere thanks go to AACE/ACE for gathering such a valuable group and holding such a thought-provoking meeting. We hope this statement can make a real difference for CGM uptake – above and beyond what industry is already doing – and we look forward to the final publication.
Homeruns: How Can This Consensus Statement Make A Difference?
Major Needs in CGM
Points of Consensus
Areas of Debate
Homeruns: How Can This Consensus Statement Make A Difference?
- Provide a ringing AACE/ACE endorsement of CGM, motivating more providers to prescribe, more patients to use, and more payers to expand coverage. CGM should be standard of care for the average person with diabetes that experiences hypoglycemia. To date, guidance on using CGM from professional societies has been softer: “recommended.” We hope the language is much stronger in this statement.
- Clearly elucidate the research gaps AND give a prioritized list to drive the CGM research agenda over the next few years. What data, if it existed, would make a tremendous difference for driving CGM uptake? What studies would be easy wins? How can real-world data from T1D Exchange or cloud-connected devices drive uptake? How can more analyses be done like Medtronic’s interesting MiniMed 530G CareLink hypoglycemia analysis, shown at ATTD?
- Guide clinicians on how to optimally prescribe CGM; implement and train patients effectively; and get paid. Dr. Irl Hirsch said around 30% of adults in his practice are on CGM, including nearly 40% of his own patients. What can be learned from his expertise to scale CGM uptake?
- Push industry to decide on a standardized one-page CGM report (e.g., AGP). It doesn’t have to be perfect, but a one-pager will go a long way for clinicians (one of the biggest points of consensus throughout the day). While “not-invented-here” syndrome is always a barrier, industry can choose to provide proprietary reports on top of the standardized one-pager. We also wonder what can be learned from other therapeutic areas like the EKG in cardiology.
- Reimbursement for doctor time spent on CGM must improve – report standardization could help on this front, but we also hope to see AACE fervently advocate for reimbursement changes on this front. There are simply too many patients and not enough clinicians for the face-to-face diabetes care model to continue. Unfortunately, good reimbursement for remote care doesn’t exist either.
- Note that the main evidence-base for CGM is from old devices (3+ years ago), and new devices (Dexcom G5, Medtronic Enlite 3, Abbott FreeStyle Libre) are leaps and bounds more effective, useful, and easier to adhere to. Products can still get much better, but they need to do so when there’s a thriving commercial market. AACE will hopefully call for studies of new devices and remind payers that the evidence base is unable to keep up with changes in technology.
- Convey the importance of using CGM to transform our understanding of new drugs. “The honest broker to evaluate the benefit of innovative diabetes therapies” (Industry Pillar). We were elated to see several drug companies in attendance today: AZ, BI, Lilly, Lexicon, and Novo Nordisk (CMO Dr. Alan Moses was particularly vocal). Lexicon’s Dr. Paul Strumph noted that the FDA drug division hasn’t strongly supported use of CGM in drug trials, and we hope AACE encourages the agency to recognize CGM not only as “a tool” but “the tool” to monitor glucose. This is well understood in the device division, but the drug side is clearly lagging.
- Strongly encourage Medicare to adopt CGM: “The value of CGM does not depend on age.” The ball seems to be in industry’s court to obtain an insulin-dosing claim, but AACE can still add pressure for Medicare to reconsider its ridiculous policy.
Major Needs in CGM
- More studies with modern devices, hypoglycemia unawareness, MDIs, type 2s, pregnancy, in-clinic efficiency, professional and intermittent CGM. (Note: Medicare’s objection to CGM coverage is NOT data or lack of studies; it’s adjunctive labeling. The statement should not include “a need for more studies in Medicare patients” – it gives Medicare a justification to say, “Oh there’s actually not enough data supporting CGM in the elderly.” This is also why JDRF has not pushed harder for studies of CGM in older patients.)
- What metrics inform therapy adjustment? What metrics can patients use to make their own therapy adjustments? Providers need easy, clinical insights from data. We are optimistic about the direction Abbott, Dexcom, Medtronic, and Glooko have moved and are continuing to move. Everyone understands pattern recognition and algorithms can make data interpretation much easier; what’s less clear is how it should integrate into clinical practice, what the regulatory bar is, how automatic it can be made, and when it can be directly patient-facing (instead of just giving provider the insulin-dosing recommendations).
- More real-world data with healtheconomic outcomes – use of cloud-connected devices, registries to understand the real-world impact of devices. RCTs have limitations for assessing CGM vs. comparators (e.g., Abbott’s REPLACE data from ATTD is a case study; we believe the device is far more effective in the real-world, where there is no study effect). We need more real-world cost-effectiveness data on the benefits of CGM, particularly on key cost drivers like hospitalizations, ambulance calls, healthcare expenses.
- As one recent example, we were impressed with the CareLink analysis Medtronic Diabetes’ Annette Brüls showed at ATTD: a colored map of the US compared dangerous hypoglycemia episodes (>3 hours at <50 mg/dl) in patients with threshold suspend turned off vs. on. Patients with threshold suspend turned off experienced 6.1 such episodes per year vs. just 0.8 episodes per patient per year with threshold suspend turned on. The slide suggested the difference (5.3 episodes hypoglycemia) equates to $735 in emergency services per patient per year and $9,300 in patient services per year.
- Better provider education on how to interpret CGM data and implement the technology. We should be introducing medical students to CGM, just like they learn how to read an EKG! We continue to hear that medical education woefully underprepares doctors for diabetes, particularly diabetes technology. We hope that changes and wonder if AACE can spearhead such an educational effort.
- Reimbursement for telehealth and remote monitoring – providers need to be paid for their time. This could facilitate new models of care delivery and help time-pressed providers see more patients and prioritize those most at risk. Some of this should improve as healthcare shifts to value-based payment, but perhaps AACE can move the ball faster, or more studies could demonstrate the value of remote diabetes care.
- We need quality of life metrics sensitive to changes from diabetes technology (independent of someone’s general quality of life). Current type 1s who do not have long-term complications have really high quality of life at baseline, making it hard to show any improvement with current measures. That lack of change in quality of life is also used as a multiplier of number of life years gained, which grossly inflates the added cost of CGM.
- “We need to be fighting the next battle. And the next battle is getting artificial pancreas paid for.” JDRF is of course all over this right now, but it does remind us of the bifurcated pathway to commercialization: the studies necessary for FDA approval are not the same ones needed for reimbursement. A case in point is Medtronic’s MiniMed 670G pivotal study (single-arm, three months, n=100) vs. its planned outcomes study (n=1,000, six months, three arm).
Points of Consensus
- CGM can be beneficial for anyone with diabetes, and particularly those with type 1 and hypoglycemia. The ongoing challenge for the field is the word “can” vs. “is” – there isn’t enough data to ardently support widespread CGM use outside of type 1 (particularly for type 2, where Dr. Bob Vigersky’s successful 2011 study with the Dexcom Seven (!) is pretty much all there is). One attendee suggested abandoning the labels “type 1” and “type 2” and focusing on therapies: insulin-using vs. non-insulin-using. We certainly believe those with type 2 and an A1c not at goal may benefit from intermittent CGM use that helps providers detect problems and change therapy.
- Value, Value, Value! “This is all going to be fueled by cost.” The field must underscore the cost benefits of using CGM, both short-term and long-term. We hope much of those can be done outside of RCTs, where registry and claims data can hopefully build a case for cost savings.
- A1c is useful, but it is not enough. Some useful reporting metrics for CGM: time-in-range, hypoglycemia, high and low pattern recognition, and glycemic variability. On the latter, many argued that standard deviation (SD) is good enough – even though %CV is statistically better – since clinicians are very familiar with SD.
- CGM download report standardization will help clinicians and facilitate CGM adoption. AGP was mentioned frequently as an example, and we heard more enthusiasm than ever for it going forward. Ease of data downloading and interpretation in the clinic is CRITICAL, and standardization should play a big role in efficiency. A standardized output could be followed with proprietary industry outputs on page two, three, etc., which could differentiate products. Many argued that report standardization is more of an HCP problem; for people using CGM, it’s all about real-time data. Clinicians also emphasized that report standardization will not hamper innovation; we think there is a good case to bolster this point from standardization in other industries (e.g., banking, Internet protocols, communication, etc.).
- Adding more data and graphs to CGM reports will not be helpful. There is already too much data; we need to simplify and create an actionable output that both providers and patients can understand together. We think data management is moving in the right direction, though we’re reminded of Antoine de Saint-Exupery, “A designer knows he has achieved perfection not when there is nothing left to add, but when there is nothing left to take away.” What would a CGM report look like when there is nothing left to take away?
- CGM devices have reached a point safe for dosing insulin. Though the FDA still hasn’t approved a dosing claim, speakers like Dr. Bruce Buckingham made one thing clear: patients are dosing insulin off CGM anyways. An insulin dosing claim is critical not just for Medicare coverage, but for better cost-effectiveness modeling of CGM (reduced fingersticks). This is a matter of “when,” not “if,” and we look forward to Dexcom’s 4Q15 call tomorrow for an update. We’re not sure what Abbott stands on this regulatory discussion with FreeStyle Libre (consumer version), or if the company will opt for an adjunctive label to get a faster review.
- We should individualize device choice and glycemic targets by patient type. What is less clear is how to do this effectively and whether data exists to guide decisions – e.g., intermittent vs. continuous CGM; SMBG vs. FreeStyle Libre vs. CGM; 70-140 mg/dl vs. 100-180 mg/dl.
- Passive data acquisition is ideal; manual entry is highly discouraged, given the additional burden and danger it imposes. Multiple speakers, particularly Dr. Bruce Buckingham, highlighted the downsides of fingerstick calibration (e.g., real-world accuracy is always much worse than in-clinic YSI accuracy). Many lauded FreeStyle Libre’s factory calibration as a major advance. Though not discussed extensively, cloud-connected devices will clearly facilitate passive data acquisition; the challenge will be integrating many outputs (e.g., glucose, insulin, activity, sleep) and making actionable sense out of the consolidated report.
- CGM interpretation should not require certification, but clinicians should receive adequate training on device use, reports, and interpretation. Speakers universally agreed that a formal certification step will add more hassle than value. What was not discussed was who should provide CGM download interpretation training; presumably industry will do this, though we wonder if there is a role for the medical system.
- Factory calibration will play a huge role in eliminating patient-induced error and bolster FDA confidence for approval of non-adjunctive CGM use. Everyone who mentioned FreeStyle Libre did so with excitement; we wonder how Dexcom and Medtronic are thinking about this competitively.
- Providers should communicate with other clinicians (CDEs, dieticians, RNs), and share patient data. The “solo HCP without a team” was frequently cited, though there was little actionable to say beyond, “CGM should be easy enough for solo doctors to prescribe.” No argument there.
Areas of Debate
- Blinded vs. real-time – is there ever a role for blinded CGM? “Blinded CGM is immoral,” argued patient advocate Bennet Dunlap and many clinicians. A minority felt masked professional CGM has some value, since patients can wear it intermittently with less hassle than real-time CGM (e.g., no need to carry a separate device or take fingersticks with FreeStyle Libre Pro). We believe both approaches have a role to play, though we hope more patients get to experience the transformative power of real-time data.
- Many noted that professional CGM can be used in a real-time fashion, contrary to the belief that such devices are always blinded. Going forward, we expect publications to clarify the semantics with more precise terminology – “professional blinded” or “professional real-time” vs. “personal real-time” use; professional vs. personal simply refer to ownership of the device and the business model for using them. Medicare does cover professional CGM (not personal), so there is an avenue to get intermittent CGM reimbursed for those over 65 years.
- Is AGP the best one-page standardized CGM download report? There was broad consensus that a standard CGM report is a critical need, and most clinicians referred to AGP as the example to move forward with. However, there was definitely disagreement in the industry pillar on this topic – for example, Dexcom’s Dr. David Price wondered if a simpler report than AGP was needed. Some wondered, for instance, whether a primary care provider would understand AGP’s use of 10/90th percentiles. We believe AGP is reasonably clear and a good starting point, but it’s clear that Medtronic, Dexcom, and data platform providers (Diasend, Glooko, Tidepool) still need to adopt it. What is holding them back?
- Abbott was also the first to integrate AGP (with FreeStyle Libre), meaning the output is sometimes construed as an Abbott product. We hope industry can move beyond that – not every company is going to get what they want with a standardized report, but the field will benefit significantly from consensus. Dr. Richard Bergenstal and the entire team at IDC has worked tremendously on AGP, and we hope it is a good starting point for getting all the companies to agree on something.
- Industry also disagreed on what time-in-range thresholds to use – 70-140, 80-160, 70-180, etc.? This seems like a solvable problem in the scheme of all the challenges in CGM. We are fans of 70-140 or 70-180 mg/dl. Perhaps these should be part of the handful of customizable features in the one-page download (the other obvious one being the definition of nighttime).
- What is the value of retrospective downloads for patients – are they ever going to download? Or are retrospective reports really designed for physicians? Device downloading has long been very tough, so it’s no surprise that patients have not widely downloaded in the past. Products that make it easier to download – or automatic with a cloud connection – will unquestionably help patients, but nowhere close to 100% of patients are ever going to download.
- We believe the future of CGM downloads will move from retrospective examination on a PC to automatic pattern recognition notifications (e.g., phone notification, email, text) – e.g., You are consistently low from 2-4 pm; consider changing X, Y, Z; Change your 12-4am basal rate from 0.95 u/hr to 0.8 u/hr due to pattern of nighttime hypoglycemia. These capabilities exist now; the limitation is most devices are not cloud-connected, so this analysis cannot typically happen passively. This is possible for those using the Dexcom G5 mobile app and MiniMed Connect; we’re not sure about the capabilities with Abbott’s FreeStyle LibreLink.
- What specific metrics, thresholds, and targets should be used and how should they be standardized? Speakers emphasized that metrics should incorporate quality of glycemic control and quality of life.
- How do we define hypoglycemia? Should <70 mg/dl be used as the cutoff for hypoglycemia? What’s the right cutoff for dangerous hypoglycemia?
- Variability: CV or SD? Variability metrics are highly correlated, and physicians understand SD – should we use that? On the other hand, mathematician Dr. Boris Kovatchev argued that SD is a useless metric, voicing support for his low blood glucose risk index.
- Compound metrics and indices can be confusing for patients, but they also have value. What’s the right balance?
- Stratification – we want to know how devices perform in different groups, but looking at subgroups can restrict coverage. Where is sub-grouping useful and where is it harmful? It will be interesting to see how Abbott talks about the REPLACE type 2 data going forward – the study showed a significant A1c reduction in patients <65 years old, but an inferior reduction in those >65 years.
- Adding automatic patient labels (“Hypoglycemia unaware”) as part of CGM reporting could be useful, but can be hard to define, and patients may feel belittled or singled out. These might be useful for obtaining CGM coverage (this patient has hypoglycemia awareness), but they could also be used as a justification against coverage.
- What degree of training should be required for interpreting CGM reports? Who should receive this training, who will deliver it, and how will it be updated? How will training keep pace with new devices? Is industry responsible for training providers on interpreting CGM data? Could companies band together and develop universal training for a single standardized CGM download report?
State-of-the-art in CGM
Bruce Buckingham, MD (Stanford University, Palo Alto, CA)
Legendary Dr. Bruce Buckingham delivered a comprehensive and thoughtful overview of the state of the CGM field, highlighting the drastic improvements (accuracy, reliability, connectivity) and remaining challenges (report standardization, healthcare provider uptake, improved integration, factory calibration). He remarked on the incredible evolution in sensor accuracy, referencing impressive MARDs around 10% in most devices, including Dexcom’s Software 505 (9% - “a major, major step forward to be less than 10%”), Abbott’s FreeStyle Libre (11% with factory calibration), Medtronic’s Enlite 3 (~11% - “a lot better”), and Senseonics’ 90-day Eversense system (~11%). Dr. Buckingham highlighted the G5’s Bluetooth-enabled remote monitoring capabilities (a “no-brainer) and lauded FreeStyle Libre’s gamechanging factory calibration feature (“this is absolutely huge”). In terms of CGM data visualizing software, Dr. Buckingham criticized the lack of standardization across manufacturers and the poor quality of some systems; he did, however, compliment Medtronic’s CareLink software for its clarity and convenience. Dr. Buckingham also praised the ambulatory glucose profile (AGP) display, encouraging companies to adopt it across the board. His talk cited other barriers to widespread clinician acceptance of CGM: download inconvenience (he showed a terrifying Medusa-like tangle of wires), unbelievable difficulty with insurance coverage, and hellacious issues with documentation, billing, and reimbursement. Dr. Buckingham stressed the value of real-time CGM data for patients (“I don’t believe in blinded CGM”), and advocated for patient education on interpreting CGM trends and insulin-on-board information. Looking ahead, Dr. Buckingham asserted that “the future of CGM is closed loop,” and one slide showed a picture of the MiniMed 670G and “2017” – we love that he is holding Medtronic to the ambitious timing first announced at JPM 2015 and reiterated in January. We appreciated Dr. Buckingham’s thought-provoking review of CGM, which served as an excellent framing of the day’s discussions; indeed, we heard many of the same topics raised in various break-out groups throughout the day and expect to see many of these ideas in the final consensus statement.
- Dr. Buckingham expressed strong enthusiasm for the ambulatory glucose profile (AGP) display of CGM data, noting that everyone at the previous IDC-Helmsley consensus meeting agreed it is “the way to go”. On this front, he encouraged conference attendees to consider the value of standardizing reports across all manufacturers.
- As a reminder, IDC’s Dr. Richard Bergenstal and team developed the AGP using feedback from an expert panel convened on the issue in 2012 – see our in-depth review of the report from the subsequent publication in JDST and DT&T. The one-page report includes relevant glycemic metrics at the top, followed by a simple visualization of glucose patterns. To date, Abbott is the only sensor company using this method, though this meeting showed growing consensus that some form of a one-page AGP should be adopted by all manufacturers as the standard method of data visualization.
- Despite no personal experience using the device, Dr. Buckingham expressed enthusiasm for Abbott’s FreeStyle Libre, highlighting the factory calibration as a gamechanging advantage – “this is absolutely huge!” Dr. Buckingham asserted that factory calibration removes the foremost method of error in CGM data – patients entering fingerstick calibrations.
- Showing camp data, Dr. Buckingham reminded attendees that real-world CGM performance is significantly less accurate than research center CGM performance – “dirty hands” and comparisons to fingersticks meaningfully elevate MARD values. For Dexcom’s G4 Platinum, MARD was 10.4% relative to YSI in the clinic vs. 17.5% relative to fingersticks at camp. For Medtronic’s original Enlite, MARD was 15% in the clinic vs. a dismal 19.2% at camp. For Medtronic’s next-gen Enlite 3, however, MARD was a consistent 10.8% relative to YSI at the clinic vs. 12% with fingersticks at camp. Enlite 3 is of course a much better sensor, though study protocol also improved real-world performance: organizers instructed campers to wipe off the first drop of blood and use the second. The risk of fingerstick calibration is an important consideration for CGM, especially as the field moves toward closing the loop and relying on CGM data for insulin dosing. We wonder if this could make Abbott’s case stronger at the FDA with FreeStyle Libre.
- Dr. Buckingham highlighted Dexcom G4/G5’s Bluet00th-enabled data sharing feature – a “no brainer” in his eyes. He explained how data sharing has been shown to significantly reduce hypoglycemic events through remote monitoring, citing a ~35% reduction in hypoglycemic episodes from a camp study of the G4+DiAs phone. He also praised the utility and convenience of Dexcom’s CGM data displayed on the Apple Watch – a slide showed a picture with current glucose value and trend on the Watch home screen, though we assume this was a Nightscout iteration. G5 still does not have an Apple Watch app (though you can “Follow” yourself with Dexcom Follow; use the G4 Share app; or receive G5 app notifications with the glucose trend and value).
- He also highlighted Medtronic’s evolution, showing MiniMed connect and the future picture of the standalone Guardian Connect mobile CGM. We saw the latter for the first time at ATTD; it is currently under CE Mark review and expected to launch next year in the US.
- Dr. Buckingham remarked on the drastic evolution in sensor accuracy, stating that patients are now relying on real-time sensor trends to dose insulin: “FDA if you’re here, that’s what’s going on now.” He noted that the continued improvement of sensor accuracy has enabled the CGM field to move forward by bringing MARD around 10% in most devices.
- Dr. Buckingham shared results we’d never seen from a 14-day study of participants (n=60) that wore Dexcom’s G4 for twice its approved length. Sensors maintained similarly high accuracy for two weeks; adhesive was the major limiting factor, however, with 48% of sensors that did not make it. Sensor accuracy for days 9-14 was similar to that for days 2-7 (~10-11%). Day eight mirrored day one, as expected, since the calibration scheme had to restart after the seven-day sensor session ended. Only 52% of participants could maintain the sensor inserted for the full 14 days; the primary reason for early termination was that the sensor fell off due to weakening of the adhesive. There was a very small rate of sensor failure and only one infection observed during the study: “the sensors can do it, it’s the adhesive that’s the problem.” As a reminder, Dexcom plans to go with a 10-day wear for G6, catching up to Abbott’s 14-day FreeStyle Libre sensor.
- On Medtronic’s Enlite 3 sensor, Dr. Buckingham noted that the “accuracy on this system has gotten a lot better.” As a reminder, data from ATTD showed an MARD of 11% vs. YSI for this sensor, which looks far better than the original Enlite. A
- Dr. Buckingham marveled at FreeStyle Libre’s factory calibrated MARD of ~11% and 14-day wear time. He acknowledged he has no personal experience with the device, though we imagine many in the US are very interested in doing studies.
- Dr. Buckingham also mentioned the 90-day accuracy of Senseonics’ implantable Eversense: a MARD of 11-12%, except for the hypoglycemia range. He spent only two slides on Senseonics and did not offer any opinion on the device or implantable advantages.
- Dr. Buckingham asserted that software for CGM data visualization should be physician-oriented, as patients are much more focused on real-time than retrospective data. He called the software a “huge advantage,” but acknowledged that it still has potential to improve so providers no longer worry about time constraints: “It can get much quicker, much more effective, and much more efficient.” He noted that reports’ value is diminished due to lack of standardization, subpar report quality, and time-consuming download process.
- Dr. Buckingham had positive views on Medtronic’s CareLink. He liked CareLink’s integration of pump and sensor data, which allows for a clear look at meals, aligning glucose values directly before and after mealtime boluses.
- Dr. Buckingham showed Dexcom’s web-based Clarity software, lamenting that each of the four download report PDFs must be individually downloaded (e.g., overview, patterns, daily, compare). He wants a batch PDF download. Dexcom has said they are developing a clinician and payer version of Clarity, and we look forward to seeing if reviews improve once those roll out.
- Dr. Buckingham called Diasend “pretty bleak in terms of quality” from a user point of view. He noted that at his clinic he receives black and white printouts of Diasend reports, which are tough to interpret. He did not elaborate further on quality. From a patient perspective, we have found Diasend to be pretty challenging too – it has the least problem identification and pattern recognition relative to other options.
- Dr. Buckingham expressed enthusiasm for Tidepool, commenting that it has already arrived in Silicon Valley and will hopefully expand. He referenced several Tidepool feature: (i) combining Dexcom CGM and Medtronic pumps; (ii) patients can add notes to their data to add deeper insight to reports; (iii) patients own their data and Tidepool is a non-profit.
- On the blinded vs. unblinded CGM debate, Dr. Buckingham was clear: “I don’t believe in blinded CGM.” He emphasized the value in having patients see their CGM data in real-time, though acknowledged that patients should receive education on how to interpret insulin-on-board information and prevent “stacking” of insulin doses. All things equal, we agree with Dr. Buckingham that unblinded CGM data is the way to go for education. Of course, if the option is blinded CGM or no CGM at all, the choice is clear. We think many flavors of glucose sensors have a role, depending on what patients need, what providers like, and what will get paid for.
- Dr. Buckingham said low provider acceptance of CGM is a major factor inhibiting widespread uptake. He asserted that clinicians do not have clear guidelines on (i) how to document CGM analyses in the EMR; (ii) how to bill for CGM review; and (iii) how to be reimbursed for CGM review. Further, it is time consuming to get patients’ insurance to cover CGM, and downloading CGM reports is a hassle during patient visits. We wonder how companies are prioritizing provider vs. patient barriers to CGM uptake – which are most addressable near-term, and which will expand uptake longer-term?
- Dr. Buckingham lamented the absence of smart pens for downloading insulin data in MDIs. Indeed, with the majority of insulin-users on MDI (vs. pumps), downloadable pens could dramatically increase the data available for driving therapeutic change. What were less sure of are the tradeoffs that would accompany smart pens (larger, more expensive, reusable); how low-hassle they will be for users (e.g., you have to open an app to get each dose); and how interoperable pharma companies would make them. Dr. Buckingham shared the encouraging T1D Exchange data (last shown in Dexcom’s ATTD session) that CGM can significantly reduce A1c regardless of insulin delivery method. As more MDI patients get on CGM – the fastest growing segment in Dr. Irl Hirsch’s clinic – tracking and integrating injection data will be key.
- For context, there are a handful of companies we are aware of developing Bluetooth-enabled insulin pens: VigiPen has several smart insulin pens and attachments in the R&D stage (we saw them at IDF); Lilly has invested in smart pen developer Companion Medical; Ypsomed is working on smart pens for pharma clients; Sanofi has a partnership with Google that could go in this direction, though no specifics have been offered on this front. Other companies we are aware of are Pendiq (launching in Spring 2016, according to its website); Common Sensing (no recent updates on its website); and Emperra (raised $3 million in December).
- Looking forward, Dr. Buckingham stated “the future of CGM is closed loop.” A slide showed a picture of the MiniMed 670G and “2017,” reminding everyone of Medtronic’s ambitious timeline. Dr. Buckingham noted that the field is moving toward less hassle and less burden for patients, highlighting hybrid closed loop’s role in improving overnight glucose control and simultaneously lowering A1c and risk of hypoglycemia.
- Dr. Buckingham listed additional opportunities for future improvement, including widespread insurance coverage of CGM, elimination of fingerstick calibration, remote monitoring capabilities for all systems, integrated insulin delivery data for MDI users, integration with consumer devices and EMR, and standardized customizable reports.
Close Concerns’ Questions
- What is most holding the CGM field back that AACE can tackle with this document? What can professional societies do to accelerate CGM adoption beyond what industry is already doing on the product front? How can sensors make clinicians lives easier?
- What are the three biggest factors preventing CGM from being on a majority of patients with type 1 and a meaningful percentage of insulin-using type 2s? What percentage of patients that want to use CGM can’t access it? Is low adoption driven to a greater degree by lack of patient interest, awareness, access barriers, or HCP issues? In which US clinics is CGM penetration exceedingly high? What can be learned from those clinics and patients?
- Can Abbott, Dexcom, and Medtronic agree on a one-page standardized report?
- What would the JDRF CGM trial look like with modern systems? Would anyone fund such a trial? Would industry band together and fund it? Would it even move the needle?
- Will anyone conduct a very large CGM trial in those with hypoglycemia unawareness, powered to show reductions in hospitalizations? What will Dexcom’s ongoing DiaMond study (results in 2H16) add to the CGM evidence base? How can T1D Exchange data on CGM users vs. non-users be better leveraged? What clinical efficacy would payers want to see to put CGM on an equal footing with BGM?
- What metrics could inform therapy adjustment? What metrics can patients use to make their own therapy adjustments? What metrics and pattern recognition would be gamechanging for clinicians?
- What will REPLACE BG show? Assuming CGM receives approval for non-adjunctive use for insulin dosing, to what degree will it replace SMBG in the coming years? Will this indication radically increase patient migration to CGM?
- How will the launch of closed loop systems impact CGM uptake and the regulatory and reimbursement environment? How many MDI patients will move to pumps once closed loop is available?
--by Adam Brown, Varun Iyengar, Ava Runge, and Kelly Close