I gave a talk yesterday to a great crowd at the annual UCSF CME conference, Diabetes Update. The slides from my presentation, “The Future of Diabetes Management: Social Networking and New Technologies,” can be viewed on Slideshare.
Nearly every day in my practice, a patient with diabetes asks me whether he or she should switch from multiple daily insulin injections to an insulin pump. I often have a discussion with patients about whether or not they should be using a CGM (continuous glucose monitor) to help monitor blood glucose instead of just using SMBG (self-monitoring of blood glucose). As an endocrinologist, it is very important to be able to advise patients about specifically what these new technologies have to offer them. Do they decrease mortality? Do they decrease long-term diabetes complications? Do they improve glycemic control? Do they improve quality of life for patients? Do they lower costs? All new medical technologies need to undergo a rigorous evaluation and testing with these types of questions in mind. This is critical not just so that I can be honest and helpful to my patients, but also from the overall perspective of the healthcare system.
In that vein, Yeh et al recently published a meta-analysis in the Annals of Internal Medicine called “Comparative Effectiveness and Safety of Methods of Insulin Delivery and Glucose Monitoring for Diabetes Mellitus: A Systematic Review and Meta-analysis.”
This meta-analysis, funded by AHRQ, looked at the differences between:
- MDI vs CSII (multiple daily injections vs continuous subcutaneous insulin infusion)
- Type 1 vs type 2 diabetes
- SMBG (self-monitoring of blood glucose) vs rt-CGM (real-time continuous glucose monitoring)
What types of studies did they include in their meta-analysis?
- Studies of adults, adolescents, or children with type 1 or type 2 diabetes mellitus
- Studies from 1966-2012
- 19 studies comparing CSII with MDI (>3 injections per day of either basal/bolus insulin or NPH/regular)
- 10 studies comparing CGM with SMBG (>3 fingersticks per day)
- 4 studies comparing SAP (Sensor-augmented pump) use with MDI + SMBG
* Studies were excluded if regular insulin was used in the CSII (pump) group (they felt this to be a weakness of prior analyses)
Here is the key data table:
A few things pop out from this table:
- Overall, they assessed the strength of evidence as relatively weak.
- In children and adolescents, CSII showed no difference in clinical outcomes from MDI. CSII was better in terms of quality-of-life.
- In adults with type 1 diabetes, CSII led to more symptomatic hypoglycemia, but better hemoglobin A1c and quality-of-life.
- There were no differences between CSII and MDI in adults with type 2 diabetes.
- CGM, whether with an insulin pump or not, led to a benefit in glycemic control without any difference in hypoglycemia.
Some concerns and words of caution when interpreting these results:
- Meta analyses can always suffer from publication bias. That is, studies are much more likely to be published if they show positive results. So it is possible that studies have been done that generated results that would have shown no difference between the two methods being studied, but these may never have been published and thus cannot be included in the meta-analysis.
- These studies all had durations of 12-52 weeks. There were no studies reporting on long-term outcomes like micro or macrovascular disease.
- 24 of the articles (approximately 2/3) were supported by pharmaceutical companies
What does this mean?
According to this meta-analysis, CGMs did improve glycemic control. Insulin pumps did not appear to have a significant effect on clinical outcomes, but did positively effect quality of life. Remember that the studies included were all between 12 and 52 weeks, so one major limitation is that any longer-term effects would not be teased out.
While some may discount the quality of life improvements seen with the pump as being less important than clinical outcomes, I caution people from doing so. In a condition as omnipresent as diabetes, maintaining good quality of life for the patient is critical and a very important goal.
In the end, the decision about whether or not to use one of these devices comes down to a conversation with the patient and their family, based on their personal preferences and what each device might offer them in terms of benefits and harms. This meta-analysis adds some more information to that conversation.
Finally, this meta-analysis shows that we simply need more data to study so that more concrete conclusions can be drawn.
Published in an Online First this week by JAMIA was the extension of the original DiaTel study published in Diabetes Care in 2010. The original study ran from 2005-2007, and patients were randomized to an “Active Care Management” (ACM) arm or a “Care Coordination” (CC) arm. The ACM arm transmitted blood glucose values daily, with a nurse practitioner adjusting their medications every 24-72 hours following ADA guidelines. The CC group received a monthly care coordination phone call offering diabetes self-management education and a referral to their primary care provider for medication adjustment. At 3 months, A1c reductions in the ACM group were 1.7% versus 0.7% in the CC group and at 6 months this was sustained at 1.7% versus 0.8% (p<0.001 for each of these).
This DiaTel Extension study was designed to see if these initial improvements could be sustained with interventions of similar or lower intensity over a six month extension period. The study design is shown here:
Methods: The population studied was a VA (Veterans Affairs) population in Pittsburgh. It is notable that this population does not reflect the typical US civilian population, as they were nearly 100% male, over 80% caucasian, <20% college-educated, and more than half were retired. The primary outcome measure was HbA1c. The mean A1c (at original DiaTel randomization) for the two groups was around 9.5%.
As you can see in the above diagram, some patients in the initial ACM group who had been transmitting glucoses daily were “stepped-down” in intensity to a “CCHT” intervention, where they continued to transmit glucose values daily but no longer had active medication management by the nurse practitioner. Other ACM patients were “stepped-down” to the CC intervention. Notably, no ACM patients were kept on ACM, and no ACM patients were sent all the way back to “UC” or usual care.
From the initial CC group (this is the group who got monthly phone calls), participants were randomized to continued CC, or “stepped-down” to usual care, UC. Usual care consisted of primary care visits every 3-6 months.
The results of the study? They did not show a benefit in continuation of the higher-intensity intervention, eg continued home telemonitoring. The authors write that this suggests that a lower intensity of contact can be used after the initial period to maintain the same level of improvement in glycemic control. Some of the results are shown below, from Figure 3 in the paper, and please note that the initial DiaTel study is indicated by months 0-6 below, with the extension period being months 6-12.
So what does this study mean?
Though a very interesting, necessary, and useful study, as with most studies, there are some limitations to it, many of which are pointed out by the authors. The population studied was a typical VA population, but this does not reflect the typical civilian US population. Because the extension trial could only be done in original study participants, the statistical power of the study was limited. This means that even if there was a true difference between groups, the study might not have been “powerful” enough to show it. Interestingly, looking at the graphic in Figure 3 above, you can start to visually see a worsening in A1c in the ACM to CCHT arm of the trial, however, there was no statistical significance seen (was the lack of significance only because of insufficient power?). The authors chose not to create an ACM to ACM group or an ACM to usual care group for the extension of the trial, so we don’t know how those would have stacked up. We do not know what the duration of A1c lowering from an intensive telemedicine intervention would be, and we also don’t know how long the initial intensive management period needs to be in order to achieve an improvement.
The authors point out that to generalize and disseminate a telemedicine intervention like this one will require a reimbursement mechanism and consideration of cost-effective ways of deploying it.
The bottom line is that a six-month long, intensive telemedicine intervention for diabetes management appears to improve A1c in this VA population, and that A1c improvement might be sustained even when the intensity of management is reduced.
I expect that this meter will be very popular, as it will allow people with diabetes to automatically record their glucose values on their iPhones, eliminating the arduous task of manual entry. I would love to hear from patients who are planning on using one or have already tried one about their experiences with them.
They will be sold not only at Walgreens but also the Apple store, which is proof about the growing and profound connection between consumer technology and healthcare. People want their healthcare devices to be designed just as elegantly as they want their smartphone or laptop or speakers designed. I’m hopeful that the days of unusable, obtuse healthcare devices will soon be behind us.
For those interested in seeing a review of three new glucose meters on the market, I recommend reading this blog post from Adam Brown(diaTribe). He reviews the OneTouch VerioIQ, Telcare, and Freestyle InsuLinx meters. Each of these new meters has different feature sets that try to differentiate it by doing more than “just checking a glucose level.”
There are two ongoing clinical trials to be aware of.
One is at the Univ of Maryland and is using the forementioned Telcare meter. This study is a 6-month pilot study taking 100 patients with diabetes (both types 1 and 2) and randomizing them to either typical glucose meter or the Telcare meter. The outcome measures will be to see if connecting the patients via the Telcare meter will improve self-monitoring of blood glucose (SMBG) compliance, to see if A1c is affected, and to see if patient satisfaction is improved.
The other is being sponsored by a company called Diabetech with a link to the trial information here. This study is using an investigational device designed by Diabetech that attaches a self-contained wireless accessory to a glucose meter, and then transmits data to a centralized data management system. The system then analyzes the data and either sends educational materials to the patient or alerts or reports to the healthcare team. The primary outcome measures in this study are glucose control and patient satisfaction. The secondary outcome measures are HbA1c, self-test frequency of glucoses, and standard deviation of HbA1c and SMBG.
I won’t review this meter, since I haven’t tested one, and there is a very thorough review already here at DiabetesMine. I do want to draw attention to it, however. The draw of this meter is that it purports to find patterns in a user’s glucose data and to then give the user feedback and recommendations about how to make changes based on those patterns. In theory, this sounds wonderful. Give feedback to a patient during a “teachable moment,” ie at the moment when the feedback is relevant and someone is most likely to learn from it. Unfortunately, according to the DiabetesMine review, the actionable recommendations are actually contained in a separate paper book that you have to request. This would significantly detract from the usefulness of the feedback given by the meter.
There is significant medical literature about decision support and how to make it successful. One BMJ systematic review from Kawamoto et al in 2005 noted that four key features are that “(a) decision support provided automatically as part of clinician workflow, (b) decision support delivered at the time and location of decision making, (c) actionable recommendations provided, and (d) computer based.” It sounds like the Verio IQ meter tries to achieve these goals but still falls short…