The value of episodic, intensive blood glucose monitoring in non-insulin treated persons with Type 2 Diabetes: design of the Structured Testing Program (STeP) study, a cluster-randomised, clinical trial [NCT00674986]

Diabetes management intervention studies: lessons learned from two studies

Introduction

Several clinical studies investigated improvements of patient outcomes due to diabetes management interventions. However, chronic disease management is intricate with complex multifactorial behavior patterns. Such studies thus have to be well designed in order to allocate all observed effects to the defined intervention and to exclude effects of other confounders as well as possible.

This article aims to provide challenges in interpreting diabetes management intervention studies and suggests approaches for optimizing study implementation and for avoiding pitfalls based on current experiences.

Main body

Lessons from the STeP and ProValue studies demonstrated the difficulty in medical device studies that rely on behavioral changes in intervention group patients. To successfully engage patients, priority should be given to health care professionals being engaged, operational support in technical issues being available, and adherence being assessed in detail.

Another difficulty is to avoid contamination of the control group with the intervention; therefore, strict allocation concealment should be maintained. However, randomization and blinding are not always possible. A limited effect size due to improvements regarding clinical endpoints in the control group is often caused by the Hawthorne effect. Improvements in the control group can also be caused with increased attention paid to the subjects. In order to reduce improvements in the control group, it is essential to identify the specific reasons and adjust study procedures accordingly. A pilot phase is indispensable for this. Another option is to include a third study arm to control for enhanced standard of care and study effects. Furthermore, retrospective data collection could be a feasible option. Adaptive study designs might reduce the necessity of a separate pilot study and combine the exploratory and confirmatory stages of an investigation in one single study.

Conclusion

There are several aspects to consider in medical device studies when using interventions that rely on changes in behavior to achieve an effective implementation and significant study results. Improvements in the control group may reduce effect sizes and limit statistical significance; therefore, alternatives to the traditional randomized controlled trials may be considered.

Digital Diabetes Self-Management: A Trilateral Serial

The way diabetes patients cope with their disease in day-to-day routines is decisive for the development or the prevention of medical complications. Smartphones have created the ubiquitous environment to support health care with mobile applications (mHealth). This article comments on the publication by Offringa et al in JDST, which is one of few studies that tries to isolate the effects of a diabetes app. At the same time, it is a good example to discuss general aspects of mHealth in diabetes care. Treatment context, eHealth literacy, interoperability, and efficiency will determine the success of diabetes apps. The development has not yet reached its end. A triple quality feedback loop linking persons with diabetes, health care providers, and mHealth providers is suggested.

Psychological interventions for diabetes-related distress in adults with type 2 diabetes mellitus

BACKGROUND

Many adults with type 2 diabetes mellitus (T2DM) experience a psychosocial burden and mental health problems associated with the disease. Diabetes-related distress (DRD) has distinct effects on self-care behaviours and disease control. Improving DRD in adults with T2DM could enhance psychological well-being, health-related quality of life, self-care abilities and disease control, also reducing depressive symptoms.

OBJECTIVES

To assess the effects of psychological interventions for diabetes-related distress in adults with T2DM.

SEARCH METHODS

We searched the Cochrane Library, MEDLINE, Embase, PsycINFO, CINAHL, BASE, WHO ICTRP Search Portal and ClinicalTrials.gov. The date of the last search was December 2014 for BASE and 21 September 2016 for all other databases.

SELECTION CRITERIA

We included randomised controlled trials (RCTs) on the effects of psychological interventions for DRD in adults (18 years and older) with T2DM. We included trials if they compared different psychological interventions or compared a psychological intervention with usual care. Primary outcomes were DRD, health-related quality of life (HRQoL) and adverse events. Secondary outcomes were self-efficacy, glycosylated haemoglobin A1c (HbA1c), blood pressure, diabetes-related complications, all-cause mortality and socioeconomic effects.

DATA COLLECTION AND ANALYSIS

Two review authors independently identified publications for inclusion and extracted data. We classified interventions according to their focus on emotion, cognition or emotion-cognition. We performed random-effects meta-analyses to compute overall estimates.

MAIN RESULTS

We identified 30 RCTs with 9177 participants. Sixteen trials were parallel two-arm RCTs, and seven were three-arm parallel trials. There were also seven cluster-randomised trials: two had four arms, and the remaining five had two arms. The median duration of the intervention was six months (range 1 week to 24 months), and the median follow-up period was 12 months (range 0 to 12 months). The trials included a wide spectrum of interventions and were both individual- and group-based.A meta-analysis of all psychological interventions combined versus usual care showed no firm effect on DRD (standardised mean difference (SMD) -0.07; 95% CI -0.16 to 0.03; P = 0.17; 3315 participants; 12 trials; low-quality evidence), HRQoL (SMD 0.01; 95% CI -0.09 to 0.11; P = 0.87; 1932 participants; 5 trials; low-quality evidence), all-cause mortality (11 per 1000 versus 11 per 1000; risk ratio (RR) 1.01; 95% CI 0.17 to 6.03; P = 0.99; 1376 participants; 3 trials; low-quality evidence) or adverse events (17 per 1000 versus 41 per 1000; RR 2.40; 95% CI 0.78 to 7.39; P = 0.13; 438 participants; 3 trials; low-quality evidence). We saw small beneficial effects on self-efficacy and HbA1c at medium-term follow-up (6 to 12 months): on self-efficacy the SMD was 0.15 (95% CI 0.00 to 0.30; P = 0.05; 2675 participants; 6 trials; low-quality evidence) in favour of psychological interventions; on HbA1c there was a mean difference (MD) of -0.14% (95% CI -0.27 to 0.00; P = 0.05; 3165 participants; 11 trials; low-quality evidence) in favour of psychological interventions. Our included trials did not report diabetes-related complications or socioeconomic effects.Many trials were small and were at high risk of bias for incomplete outcome data as well as possible performance and detection biases in the subjective questionnaire-based outcomes assessment, and some appeared to be at risk of selective reporting. There are four trials awaiting further classification. These are parallel RCTs with cognition-focused and emotion-cognition focused interventions. There are another 18 ongoing trials, likely focusing on emotion-cognition or cognition, assessing interventions such as diabetes self-management support, telephone-based cognitive behavioural therapy, stress management and a web application for problem solving in diabetes management. Most of these trials have a community setting and are based in the USA.

AUTHORS' CONCLUSIONS

Low-quality evidence showed that none of the psychological interventions would improve DRD more than usual care. Low-quality evidence is available for improved self-efficacy and HbA1c after psychological interventions. This means that we are uncertain about the effects of psychological interventions on these outcomes. However, psychological interventions probably have no substantial adverse events compared to usual care. More high-quality research with emotion-focused programmes, in non-US and non-European settings and in low- and middle-income countries, is needed.

Evaluation of a Behavioral Mobile Phone App Intervention for the Self-Management of Type 2 Diabetes: Randomized Controlled Trial Protocol

Background

Patients with type 2 diabetes mellitus (T2DM) struggle with the management of their condition due to difficulty relating lifestyle behaviors with glycemic control. While self-monitoring of blood glucose (SMBG) has proven to be effective for those treated with insulin, it has been shown to be less beneficial for those only treated with oral medications or lifestyle modification. We hypothesized that the effective self-management of non-insulin treated T2DM requires a behavioral intervention that empowers patients with the ability to self-monitor, understand the impact of lifestyle behaviors on glycemic control, and adjust their self-care based on contextualized SMBG data.

Objective

The primary objective of this randomized controlled trial (RCT) is to determine the impact of bant2, an evidence-based, patient-centered, behavioral mobile app intervention, on the self-management of T2DM. Our second postulation is that automated feedback delivered through the mobile app will be as effective, less resource intensive, and more scalable than interventions involving additional health care provider feedback.

Methods

This study is a 12-month, prospective, multicenter RCT in which 150 participants will be randomly assigned to one of two groups: the control group will receive current standard of care, and the intervention group will receive the mobile phone app system in addition to standard of care. The primary outcome measure is change in glycated hemoglobin A1c from baseline to 12 months.

Results

The first patient was enrolled on July 28, 2015, and we anticipate completing this study by September, 2018.

Conclusions

This RCT is one of the first to evaluate an evidence-based mobile app that focuses on facilitating lifestyle behavior change driven by contextualized and structured SMBG. The results of this trial will provide insights regarding the usage of mobile tools and consumer-grade devices for diabetes self-care, the economic model of using incentives to motivate behavior change, and the consumption of test strips when following a rigorously structured approach for SMBG.

Trial Registration

ClinicalTrials.gov NCT02370719; https://clinicaltrials.gov/ct2/show/NCT02370719 (Archived at http://www.webcitation.org/6jpyjfVRs)

Effects of self-monitoring of glucose on distress and self-efficacy in people with non-insulin-treated Type 2 diabetes: a randomized controlled trial

AIMS

To investigate the effects of self-monitoring of glucose in blood or urine, on diabetes-specific distress and self-efficacy, compared with usual care in people with non-insulin-treated Type 2 diabetes mellitus.

METHODS

One hundred and eighty-one participants with non-insulin-treated Type 2 diabetes mellitus [diabetes duration ≥ 1 year, age 45-75 years, HbA1c ≥ 53.0 mmol/mol (7.0%), self-monitoring frequency < 3 times in the previous year] were randomly assigned to blood self-monitoring (n = 60), urine self-monitoring (n = 59) or usual care (n = 62). Primary outcomes were between-group differences in diabetes-specific distress [Problem Areas in Diabetes scale (PAID)] and self-efficacy [Confidence in Diabetes Self-Care questionnaire (CIDS-2)] after 12 months. Secondary outcomes included changes in HbA1c , treatment satisfaction and depressive symptoms.

RESULTS

There were no statistically significant between-group differences in changes in PAID and CIDS-2 after 12 months. Mean difference in PAID between blood monitoring and control was -2.2 [95% confidence interval (CI) -7.1 to 2.7], between urine monitoring and control was -0.9 (95% CI -4.4 to 2.5) and between blood monitoring and urine monitoring was -2.0 (95% CI -4.1 to 0.1). Mean difference in CIDS-2 between blood monitoring and control was 0.6 [95% CI (-2.0 to 2.1), between urine monitoring and control was 2.8 (95% CI -2.3 to 7.9)] and between blood monitoring and urine monitoring was -3.3 (95% CI -7.9 to 1.3). No statistically significant between-group differences in change in any of the secondary outcome measures were found.

CONCLUSIONS

This study did not find statistical or clinical evidence for a long-term effect of self-monitoring of glucose in blood or urine on diabetes-specific distress and self-efficacy in people with moderately controlled non-insulin-treated Type 2 diabetes mellitus. (Current Controlled Trials ISRCTN84568563).

Translating What Works: A New Approach to Improve Diabetes Management

BACKGROUND

The most efficacious strategies to improve diabetes control include case management, health care team changes, patient education, and facilitated transmission of patient data to clinicians ("facilitated relay"), but these strategies have not been translated to permit general use in clinical practice.

METHODS

A web-based decision support program was developed to include these features, and assessed in patients who had A1c ≥7.0% despite using metformin with/without sulfonylureas or insulin. Staff entered patients' glucose data, obtained management recommendations, reviewed the plan with a clinician, and discussed the new plan with patients.

RESULTS

113 subjects were 96% male and 32% black, with average age 65.6 years and BMI 32.8. During prior primary care, A1c averaged 8.32 ± 0.16% (SEM). In all patients, baseline A1c was 8.18 ± 0.11%, and decreased to 7.54 ± 0.12%, 7.16 ± 0.13%, and 7.54 ± 0.16% at 3, 6, and 12 months, respectively, all P < .001. In 42 subjects who provided glucose data and made requested changes in medications, A1c was 8.12 ± 0.09% at baseline and fell to 7.29 ± 0.11%, 6.98 ± 0.10%, and 7.05 ± 0.10% at 3, 6, and 12 months, respectively, all P < .001. Chart review of 16 subjects followed for 12 months demonstrated that hypoglycemia (symptoms and/or glucose <70 mg/dl) averaged less than 1 episode/patient/month, and there was no severe hypoglycemia.

CONCLUSIONS

A novel decision support program improved A1c with little hypoglycemia. Use of this approach should allow primary care teams to keep patients well controlled, and reduce the need for specialist referrals.

Impact of social determinants of health on outcomes for type 2 diabetes: a systematic review

Social determinants of health include the social and economic conditions that influence health status. Research into the impact of social determinants on individuals with type 2 diabetes has largely focused on the prevention of or risk of developing diabetes. No review exists summarizing the impact of social determinants of health outcomes in patients with type 2 diabetes. This systematic review examined whether social determinants of health have an impact on health outcomes in type 2 diabetes. Medline was searched for articles that (a) were published in English (b) targeted adults, ages 18 + years, (c) had a study population which was diagnosed with type 2 diabetes, (d) the study was done in the United States, and (e) the study measured at least one of the outcome measures-glycemic control, cholesterol (LDL), blood pressure, quality of life or cost. Using a reproducible strategy, 2,110 articles were identified, and 61 were reviewed based on inclusion criteria. Twelve were categorized as Economic Stability and Education, 17 were categorized as Social and Community Context, 28 were categorized as Health and Health Care, and three were categorized as Neighborhood and Built Environment. Based on the studies reviewed, social determinants have an impact on glycemic control, LDL, and blood pressure to varying degrees. The impact on cost and quality of life was not often measured, but when quality of life was investigated, it did show significance. More research is needed to better characterize the direct impact of social determinants of health on health outcomes in diabetes.

Use of an insulin bolus advisor facilitates earlier and more frequent changes in insulin therapy parameters in suboptimally controlled patients with diabetes treated with multiple daily insulin injection therapy: results of the ABACUS trial

BACKGROUND

We assessed the impact of using an automated bolus advisor integrated into a blood glucose meter on the timing and frequency of adjusting insulin therapy parameter settings and whether the availability of this technology would increase blood glucose test strip utilization in diabetes patients treated with multiple daily insulin injection (MDI) therapy.

SUBJECTS AND METHODS

The Automated Bolus Advisor Control and Usability Study (ABACUS) trial, a 26-week, prospective, randomized, controlled, multinational study that enrolled 218 type 1 and type 2 diabetes patients, demonstrated that use of an automated insulin bolus advisor helps improve glycemic control in suboptimally controlled, MDI-treated patients. Patient data were assessed to determine when and how often changes in insulin parameter settings occurred during the study. Patient meters were downloaded to determine blood glucose monitoring frequency.

RESULTS

One hundred ninety-three patients completed the study: 93 control arm (CNL) and 100 intervention (experimental) arm (EXP). Significantly more EXP (47.5%) than CNL (30.7%) patients received one or more changes in their insulin sensitivity factor (ISF) settings during the study (P=0.0191). Changes in ISF settings occurred earlier and more frequently in EXP than CNL patients throughout the study. A similar trend was seen in changes in insulin-to-carbohydrate ratios. There were no differences in daily self-monitoring of blood glucose frequency [mean (SD)] between CNL and EXP patients: 4.7 (1.5) versus 4.6 (1.3) (P=0.4085).

CONCLUSIONS

Use of an automated bolus advisor was associated with earlier, more frequent changes in key insulin parameters, which may have contributed to subsequent improvements in glycemic control but without increased glucose test strip utilization.

Prospective, randomized trial on intensive SMBG management added value in non-insulin-treated T2DM patients (PRISMA): a study to determine the effect of a structured SMBG intervention

Self-monitoring of blood glucose (SMBG) is a core component of diabetes management. However, the International Diabetes Federation recommends that SMBG be performed in a structured manner and that the data are accurately interpreted and used to take appropriate therapeutic actions. We designed a study to evaluate the impact of structured SMBG on glycemic control in non-insulin-treated type 2 diabetes (T2DM) patients. The Prospective, Randomized Trial on Intensive SMBG Management Added Value in Non-insulin-Treated T2DM Patients (PRISMA) is a 12-month, prospective, multicenter, open, parallel group, randomized, and controlled trial to evaluate the added value of an intensive, structured SMBG regimen in T2DM patients treated with oral agents and/or diet. One thousand patients (500 per arm) will be enrolled at 39 clinical sites in Italy. Eligible patients will be randomized to the intensive structured monitoring (ISM) group or the active control (AC) group, with a glycosylated hemoglobin (HbA1c) target of <7.0%. Intervention will comprise (1) structured SMBG (4-point daily glucose profiles on 3 days per week [ISM]; discretionary, unstructured SMBG [AC]); (2) comprehensive patient education (both groups); and (3) clinician's adjustment of diabetes medications using an algorithm targeting SMBG levels, HbA1c and hypoglycemia (ISM) or HbA1c and hypoglycemia (AC). The intervention and trial design build upon previous research by emphasizing appropriate and collaborative use of SMBG by both patients and physicians. Utilization of per protocol and intent-to-treat analyses facilitates assessment of the intervention. Inclusion of multiple dependent variables allows us to assess the broader impact of the intervention, including changes in patient and physician attitudes and behaviors.

Association of self-monitoring of blood glucose use on glycated hemoglobin and weight in newly diagnosed, insulin-naïve adult patients with type 2 diabetes

BACKGROUND

Clinical trials have shown that self-monitoring of blood glucose (SMBG) combined with patient education and medication titration can lead to improved glycated hemoglobin (HbA1c) and reduced weight in recently diagnosed non-insulin-treated type 2 diabetes mellitus (T2DM) patients. This retrospective matched cohort study assessed the association of SMBG with achieving long-term clinical outcomes in these patients in a real-world clinical setting.

METHODS

Using electronic medical records (2008-2011), we selected a population of adult patients recently diagnosed with T2DM not receiving insulin who were SMBG users and a population of non-SMBG controls with similar demographic and clinical characteristics using propensity score matching. The main study outcomes compared between the two groups were time to achieve (1) HbA1c <7% for patients with baseline HbA1c ≥ 7% and (2) a ≥ 5% reduction in weight from baseline.

RESULTS

Of the 589 patients identified in each group, 113 in each group had a baseline HbA1c ≥ 7% (mean, 8.2%). The SMBG users were more likely to achieve an HbA1c <7% (12 months: 58.4% versus 38.9%, p = .0037; 36 months: 84.0% versus 70.0%, p = .0013) and to do so faster (median, 6.5 versus 20.5 months; log-rank p = .0016). Self-monitoring of blood glucose was associated with faster weight reduction (median time to achieve a ≥ 5% reduction, 23.5 versus 35.9 months for SMBG and non-SMBG, respectively; log-rank p = .0005).

CONCLUSIONS

In newly diagnosed T2DM insulin-naïve patients, SMBG users had an improved rate of achieving long-term glycemic control and weight loss in a real-world clinical setting.

Changes in A1C levels are significantly associated with changes in levels of the cardiovascular risk biomarker hs-CRP: results from the SteP study

OBJECTIVE

The effect of therapeutic strategies on cardiovascular (CV) disease can be evaluated by monitoring changes in CV risk biomarkers. This study investigated the effect of a structured self-monitoring of blood glucose (SMBG) protocol and the resulting improvements in glycemic control on changes in high-sensitivity C-reactive protein (hs-CRP) in insulin-naïve patients with type 2 diabetes.

RESEARCH DESIGN AND METHODS

The Structured Testing Program (STeP) study was a prospective, cluster-randomized, multicenter trial in which 483 poorly controlled, insulin-naïve patients with type 2 diabetes were randomized to active control (ACG) or structured testing (STG) that included quarterly structured SMBG. Changes in A1C, hs-CRP, and glycemic variability (STG subjects only) were measured at baseline and quarterly.

RESULTS

Reductions in geometric mean hs-CRP values were significantly greater in the STG group at months 3 (P = 0.005), 6 (P = 0.0003), and 12 (P = 0.04) than in the ACG group. STG patients at high CV risk (>3 mg/L) showed significantly greater reductions in hs-CRP levels than ACG patients at high CV risk: -3.64 mg/dL (95% CI -4.21 to -3.06) versus -2.18 mg/dL (-2.93 to -1.43), respectively (P = 0.002). There was a strong correlation between reductions in hs-CRP and A1C in both groups: standardized coefficient (β) was 0.25 for the entire cohort (P < 0.0001), 0.31 for STG (P < 0.0001), and 0.16 for ACG (P = 0.02).

CONCLUSIONS

Reductions in hs-CRP level are associated with reductions in A1C but not reductions in lipids or glycemic variability. Comprehensive structured SMBG-based interventions that lower A1C may translate into improvements in CV risk, as evidenced by levels of the biomarker hs-CRP.

Challenging evidence and assumptions: is there a role for self-monitoring of blood glucose in people with type 2 diabetes not using insulin?

BACKGROUND

There is debate in the literature about the effectiveness of self-monitoring of blood glucose (SMBG) for people with type 2 diabetes (T2DM) who do not use insulin. Several recent systematic reviews and meta-analyses conclude that SMBG does not have any clinical benefit for this group.

OBJECTIVE

We critically appraise the available evidence, and argue whether SMBG is warranted for people with non-insulin-treated T2DM.

RESULTS

Considerable heterogeneity exists amongst the literature, and aspects of the methodology of some of these studies confound interpretation of results. Recent evidence demonstrates that when SMBG is 'structured', incorporated as part of a complex intervention, and embedded within education and collaborative care, improvements in average blood glucose levels result. In contrast, studies that do not apply SMBG systematically, or that assess a low frequency SMBG regimen that precludes identification and interpretation of SMBG patterns, are not clinically effective. Psychosocial outcomes, such as self-efficacy and diabetes-related distress, and other clinical outcomes, such as hypoglycaemia detection, should also be considered as important clinical endpoints.

LIMITATIONS

This is not a systematic literature review. The literature is limited by a lack of studies evaluating a 'structured' approach to SMBG.

CONCLUSIONS

It is the quality, not quantity, of SMBG that makes a difference to outcomes for people with non-insulin-treated T2DM. The benefits of 'structured' SMBG should be considered as part of a complex intervention when making decisions about policy and practice, and assumptions about the benefits of SMBG for people with non-insulin-treated T2DM should be challenged.

Self-monitoring of blood glucose in noninsulin-using type 2 diabetic patients: right answer, but wrong question: self-monitoring of blood glucose can be clinically valuable for noninsulin users

Given the importance of glycemic control in the development of diabetes complications, the plethora of tools now available to monitor the day-to-day trends in glycemia is remarkable. In this regard, self-monitoring of blood glucose (SMBG) has been considered a key component of patient management. Arguably, there remains almost universal agreement that SMBG should be available to all diabetic patients regardless of current treatment strategy. However, recently there have been reports that have challenged the current paradigm that all patients should use SMBG and concluded that SMBG for type 2 diabetic patients not on insulin may not be beneficial on glycemic control and must be weighed against the expense and inconvenience. In the counterpoint narrative following the contribution by Malanda et al., Drs. Polonsky and Fisher provide a compelling argument suggesting that while it is evident that implementing SMBG in unstructured ways without training patients and clinicians is likely to be a waste of resources, there are effective and powerful ways to use structured SMBG in insulin-naïve type 2 diabetic patients. -William T. Cefalu, MD Editor in Chief, Diabetes Care.

The association of self-monitoring of blood glucose use with medication adherence and glycemic control in patients with type 2 diabetes initiating non-insulin treatment

BACKGROUND

The value of self-monitoring of blood glucose (SMBG) for persons with type 2 diabetes who do not use insulin remains controversial. This observational study compares the likelihood of medication adherence and change in glycated hemoglobin (A1C) for non-insulin-using patients using SMBG versus those not using SMBG. The study also assessed the association between diabetes medication adherence and SMBG use.

PATIENTS AND METHODS

Data were extracted on 5,172 patients who began non-insulin diabetes medication between October 1, 2006, and March 31, 2009. The study assessed change in A1C associated with SMBG use and testing frequency at different categorical levels of baseline A1C. The likelihood of medication adherence for SMBG users was compared with that for non-SMBG users at different categorical levels of baseline A1C. The study further explored the interactions between SMBG use and medication adherence on change in A1C.

RESULTS

SMBG users had greater reductions in A1C compared with nonusers when the baseline A1C was ≥ 7%. Increasing SMBG frequency was associated with greater reductions in A1C. The study also examined the associations among SMBG use, medication adherence, and change in A1C. SMBG users had greater decreases in A1C for both medication-adherent and -nonadherent patients. As expected, medication adherence was associated with greater reductions in A1C for both SMBG nonusers and users. It is interesting that medication-nonadherent SMBG users had similar reductions in A1C compared with medication-adherent non-SMBG users.

CONCLUSIONS

Both SMBG use and medication adherence were associated with similar degrees of A1C reduction after controlling for baseline A1C, suggesting that both factors may be important for attaining glycemic control.

What do we need beyond hemoglobin A1c to get the complete picture of glycemia in people with diabetes?

Hemoglobin A1c (HbA1c) is currently the most commonly used marker for the determination of the glycemic status in people with diabetes and it is frequently used to guide therapy and especially medical treatment of people with diabetes. The measurement of HbA1c has reached a high level of analytical quality and, therefore, this biomarker is currently also suggested to be used for the diagnosis of diabetes. Nevertheless, it is crucial for people with diabetes and their treating physicians to be aware of possible interferences during its measurement as well as physiological or pathological factors that contribute to the HbA1c concentration without being related to glycemia, which are discussed in this review. We performed a comprehensive review of the literature based on PubMed searches on HbA1c in the treatment and diagnosis of diabetes including its most relevant limitations, glycemic variability and self-monitoring of blood glucose (SMBG). Although the high analytical quality of the HbA1c test is widely acknowledged, the clinical relevance of this marker regarding risk reduction of cardiovascular morbidity and mortality is still under debate. In this respect, we argue that glycemic variability as a further risk factor should deserve more attention in the treatment of diabetes.

A survey of blood glucose monitoring in patients with type 2 diabetes: are recommendations from health care professionals being followed?

OBJECTIVE

To survey the self-reported use of self-monitoring of blood glucose (SMBG) among patients with type 2 diabetes (T2DM), both insulin users (IUs) and non-insulin users (NIUs), in the United States and to examine: how often patients test; what SMBG instructions patients report receiving from their health care providers (HCPs); how the frequency of testing conforms with reported HCP recommendations for testing; and what is done with the results of testing. Differences between IUs and NIUs were also investigated.

METHODS

A convenience sample of 886 T2DM participants at a series of one-day conferences across the United States completed a survey on current and recommended SMBG frequency, how SMBG results were used, and how HCPs reportedly talked about SMBG issues with the patient. IUs (65% of the sample) and NIUs (35%) were examined separately.

RESULTS

IUs and NIUs reported testing significantly less frequently than was recommended (in both cases, p < 0.001), with wide variations within both groups. Many IUs (42%) and NIUs (50%) did not bring SMBG data regularly to medical visits, and 54% of IUs and 56% of NIUs did not respond regularly to out-of-range SMBG readings. HCPs were generally supportive and responsive to SMBG data. More frequent SMBG was associated with more regular HCP attention to SMBG records, for IUs (p = 0.02) and NIUs (p = 0.004).

CONCLUSIONS

Self-reported SMBG use is common in T2DM, though frequency is lower than HCP recommendations. Wide variations in actual and recommended SMBG were observed. HCP support for SMBG is reportedly common, and is associated with greater SMBG frequency. While SMBG data can be valuable, recommendations are often not followed and data often goes unused by both HCPs and patients.

Cost effectiveness of self-monitoring of blood glucose (SMBG) for patients with type 2 diabetes and not on insulin: impact of modelling assumptions on recent Canadian findings

BACKGROUND

Canadian patients, healthcare providers and payers share interest in assessing the value of self-monitoring of blood glucose (SMBG) for individuals with type 2 diabetes but not on insulin. Using the UKPDS (UK Prospective Diabetes Study) model, the Canadian Optimal Prescribing and Utilization Service (COMPUS) conducted an SMBG cost-effectiveness analysis. Based on the results, COMPUS does not recommend routine strip use for most adults with type 2 diabetes who are not on insulin. Cost-effectiveness studies require many assumptions regarding cohort, clinical effect, complication costs, etc. The COMPUS evaluation included several conservative assumptions that negatively impacted SMBG cost effectiveness.

OBJECTIVES

Current objectives were to (i) review key, impactful COMPUS assumptions; (ii) illustrate how alternative inputs can lead to more favourable results for SMBG cost effectiveness; and (iii) provide recommendations for assessing its long-term value.

METHODS

A summary of COMPUS methods and results was followed by a review of assumptions (for trial-based glycosylated haemoglobin [HbA(1c)] effect, patient characteristics, costs, simulation pathway) and their potential impact. The UKPDS model was used for a 40-year cost-effectiveness analysis of SMBG (1.29 strips per day) versus no SMBG in the Canadian payer setting. COMPUS assumptions for patient characteristics (e.g. HbA(1c) 8.4%), SMBG HbA(1c) advantage (-0.25%) and costs were retained. As with the COMPUS analysis, UKPDS HbA(1c) decay curves were incorporated into SMBG and no-SMBG pathways. An important difference was that SMBG HbA(1c) benefits in the current study could extend beyond the initial simulation period. Sensitivity analyses examined SMBG HbA(1c) advantage, adherence, complication history and cost inputs. Outcomes (discounted at 5%) included QALYs, complication rates, total costs (year 2008 values) and incremental cost-effectiveness ratios (ICERs).

RESULTS

The base-case ICER was $Can63 664 per QALY gained; approximately 56% of the COMPUS base-case ICER. SMBG was associated with modest risk reductions (0.10-0.70%) for six of seven complications. Assuming an SMBG advantage of -0.30% decreased the current base-case ICER by over $Can10 000 per QALY gained. With adherence of 66% and 87%, ICERs were (respectively) $Can39 231 and $Can54 349 per QALY gained. Incorporating a more representative complication history and 15% complication cost increase resulted in an ICER of $Can49 743 per QALY gained.

CONCLUSIONS

These results underscore the importance of modelling assumptions regarding the duration of HbA(1c) effect. The current study shares several COMPUS limitations relating to the UKPDS model being designed for newly diagnosed patients, and to randomized controlled trial monitoring rates. Neither study explicitly examined the impact of varying the duration of initial HbA(1c) effects, or of medication or other treatment changes. Because the COMPUS research will potentially influence clinical practice and reimbursement policy in Canada, understanding the impact of assumptions on cost-effectiveness results seems especially important. Demonstrating that COMPUS ICERs were greatly reduced through variations in a small number of inputs may encourage additional clinical research designed to measure SMBG effects within the context of optimal disease management. It may also encourage additional economic evaluations that incorporate lessons learned and best practices for assessing the overall value of SMBG for type 2 diabetes in insulin-naive patients.

The impact of blood glucose monitoring on depression and distress in insulin-naïve patients with type 2 diabetes

OBJECTIVE

To test whether a structured self-monitoring of blood glucose (SMBG) protocol reduces depressive symptoms and diabetes distress.

RESEARCH DESIGN AND METHODS

A 12-month, cluster-randomised, clinical trial compared patients who received a collaborative, structured SMBG, physician/patient intervention with an active control. Studied were 483 insulin naïve type 2 diabetes patients (experimental = 256, control = 227) (≥ 7.5% HbA1c) from 34 primary care practices (experimental = 21, control = 13). Experimental patients used a paper tool to record a 7-point SMBG profile on each of three consecutive days prior to their quarterly physician visit. Patients and physicians interpreted SMBG results to make medication and lifestyle changes.

CLINICAL TRIAL REGISTRATION

NIH Trial Registry Number: NCT00674986.

MAIN OUTCOME MEASURES

Depressive symptoms (Patient Health Questionnaire: PHQ-8), diabetes-related distress (Diabetes Distress Scale: DDS). HbA1c and SMBG frequency were assessed quarterly; data were analysed using Linear Mixed Models (LMM) for intent-to-treat (ITT) and per protocol (PP) analyses.

RESULTS

ITT analyses showed significant improvement in depression and disease-related distress among experimental and control patients from baseline to 12 months (p < 0.01 in both cases) with no between-group differences. Experimental patients displayed significantly greater reductions in distress related to regimen adherence than controls. Also, experimental patients with elevated diabetes distress or depressive symptoms at baseline showed significantly greater reductions in distress and depressive symptoms than control patients at 12 months. The greater improvement in mood in the experimental than control group was independent of improvements in glycaemic control and changes in SMBG frequency.

CONCLUSIONS

Using well standardised measures, collaborative, structured SMBG leads to reductions, not increases, in depressive symptoms and diabetes distress over time, for the large number of moderately depressed or distressed type 2 patients in poor glycaemic control. Changes in affective status are independent of improvements in glycaemic control and changes in SMBG frequency for these patients.

Actionable self-monitoring of blood glucose: redefining the role for patients using multiple daily injection therapy

Self-monitoring of blood glucose (SMBG) values is an accepted requirement for patients with diabetes using multiple daily injections of insulin. Nevertheless, for many patients, the full value of SMBG has yet to be realized due to a number of factors that contribute to patients not taking appropriate action based on the achieved result. The reasons for this are complex but are related to the burden imposed by performing the tests, the need for complex numerical calculations, and the demand for undertaking this activity multiple times each day. In the near future, SMBG devices are likely to include technological innovations that are aimed at overcoming these barriers, offering "actionable" SMBG for patients using insulin. These innovations should include technologies that will allow customization and individualization based upon specific therapy regimens.

A structured self-monitoring of blood glucose approach in type 2 diabetes encourages more frequent, intensive, and effective physician interventions: results from the STeP study

BACKGROUND

We evaluated how a structured patient/physician self-monitoring of blood glucose (SMBG) intervention influenced the timing, frequency, and effectiveness of primary care physicians' treatment changes with type 2 diabetes mellitus (T2DM) patients over 12 months.

METHODS

The Structured Testing Program (STeP) study was a cluster-randomized, multicenter trial with 483 poorly controlled, insulin-naive T2DM subjects. Primary care practices were randomized to the Active Control Group (ACG) or the Structured Testing Group (STG), the latter of which included quarterly review of structured SMBG results. STG patients used a paper tool that graphs seven-point glucose profiles over 3 consecutive days; physicians received a treatment algorithm based on SMBG patterns. Impact of structured SMBG on physician treatment modification recommendations (TMRs) and glycemic outcomes was examined.

RESULTS

More STG than ACG patients received a TMR at each study visit (P < 0.0001). Of patients who received at least one TMR, STG patients demonstrated a greater reduction in glycated hemoglobin A1c (HbA1c) than ACG patients (-1.2% vs. -0.8%, P < 0.03). Patients with a baseline HbA1c ≥8.5% who received a TMR at the Month 1 visit experienced greater reductions in HbA1c (P = 0.002) than patients without an initial TMR. More STG than ACG patients were started on incretins (P < 0.01) and on thiazolidinediones (P = 0.004). The number of visits with a TMR was unrelated to HbA1c change over time.

CONCLUSIONS

Patient-provided SMBG data contribute to glycemic improvement when blood glucose patterns are easy to detect, and well-trained physicians take timely action. Collaborative use of structured SMBG data leads to earlier, more frequent, and more effective TMRs for poorly controlled, non-insulin-treated T2DM subjects.

Effects of a structured self-monitoring of blood glucose method on patient self-management behavior and metabolic outcomes in type 2 diabetes mellitus

BACKGROUND

The purpose of this study was to evaluate the effect of structured self-monitoring of blood glucose (SMBG) on patient self-management behavior and metabolic outcomes in patients with type 2 diabetes mellitus (T2DM).

METHODS

From January to June 2009, 30 patients with basic diabetes education were followed for a period of 90 days. To provide assessment of glycemic control and frequency of dysglycemia, patients, underwent 3 consecutive days of seven-point SMBG during each month for 3 consecutive months, using the ACCU-CHEK 360° View tool. Glucose profiles of the first and third month were used for comparison.

RESULTS

Hemoglobin A1c (HbA1c) improved significantly during the 90-day period in all patients [confidence interval (CI) 95%, 0.32-1.64%, p < .05] and those with poor metabolic control (group B; CI 95%, 0.86-2.64%, p < .05). Mean blood glucose (MBG) values decreased significantly in group B (CI 95%, 0.56-24.78 mg/dl, p < .05) and all cases (CI 95%, 1.61-19.73 mg/dl, p < .05). Meanwhile, there was an average decrease of 15.7 mg/dl in fasting blood sugar (FBS) levels in the whole subjects. Mean postprandial blood glucose levels (MPP) decreased by 19.3 and 11.3 mg/dl in group B and in all cases, respectively. However, there were no significant changes in HbA1c, MBG, FBS, and MPP in people with good metabolic control.

CONCLUSION

A structured SMBG program improves HbA1c, FBS, MPP, and MBG in people with poorly controlled diabetes. This improvement shows the importance of patient self-management behavior on metabolic outcomes in T2DM.

Structured self-monitoring of blood glucose significantly reduces A1C levels in poorly controlled, noninsulin-treated type 2 diabetes: results from the Structured Testing Program study

OBJECTIVE

To assess the effectiveness of structured blood glucose testing in poorly controlled, noninsulin-treated type 2 diabetes.

RESEARCH DESIGN AND METHODS

This 12-month, prospective, cluster-randomized, multicenter study recruited 483 poorly controlled (A1C ≥ 7.5%), insulin-naïve type 2 diabetic subjects from 34 primary care practices in the U.S. Practices were randomized to an active control group (ACG) with enhanced usual care or a structured testing group (STG) with enhanced usual care and at least quarterly use of structured self-monitoring of blood glucose (SMBG). STG patients and physicians were trained to use a paper tool to collect/interpret 7-point glucose profiles over 3 consecutive days. The primary end point was A1C level measured at 12 months.

RESULTS

The 12-month intent-to-treat analysis (ACG, n = 227; STG, n = 256) showed significantly greater reductions in mean (SE) A1C in the STG compared with the ACG: -1.2% (0.09) vs. -0.9% (0.10); Δ = -0.3%; P = 0.04. Per protocol analysis (ACG, n = 161; STG, n = 130) showed even greater mean (SE) A1C reductions in the STG compared with the ACG: -1.3% (0.11) vs. -0.8% (0.11); Δ = -0.5%; P < 0.003. Significantly more STG patients received a treatment change recommendation at the month 1 visit compared with ACG patients, regardless of the patient's initial baseline A1C level: 179 (75.5%) vs. 61 (28.0%); <0.0001. Both STG and ACG patients displayed significant (P < 0.0001) improvements in general well-being (GWB).

CONCLUSIONS

Appropriate use of structured SMBG significantly improves glycemic control and facilitates more timely/aggressive treatment changes in noninsulin-treated type 2 diabetes without decreasing GWB.

Effects of lifestyle education program for type 2 diabetes patients in clinics: study design of a cluster randomized trial

Background

The number of patients with type 2 diabetes is drastically increasing worldwide. It is a serious health problem in Japan as well. Lifestyle interventions can reduce progression from impaired glucose tolerance to type 2 diabetes, and glycemic control has been shown to improve postprandial plasma glucose levels. Moreover, several studies have suggested that continuous interventions (combined diet and exercise) can improve the plasma glucose level and reduce dosage of hypoglycemic agents.

Although many interventional studies of lifestyle education for persons with diabetes in hospitals have been reported, only a few have been clinic-based studies employing an evidence-based lifestyle education program. This article describes the design of a cluster randomized controlled trial of the effectiveness of lifestyle education for patients with type 2 diabetes in clinics by registered dietitians.

Methods/Design

In Japan, general practitioners generally have their own medical clinics to provide medical care for outpatients in the community, including those with type 2 diabetes. With the collaboration of such general practitioners, the study patients were enrolled in the present study. Twenty general practitioners were randomly allocated to each provide patients for entry into either an intervention group (10) or a control group (10). In total, 200 participants will be included in the study. The intervention group will receive intensive education on lifestyle improvement related to type 2 diabetes by registered dietitians in clinics. Lifestyle education will be conducted several times during the study period. The control group will receive information on dietary intake and standard advice on glycemic control by registered dietitians. The primary endpoint is the change from the baseline value of HbA1c at 6 months. Data on health behavior and related issues will be gathered continuously over a 6-month period.

Discussion

This is the first study to evaluate lifestyle education in clinics by a cluster randomization trial in Japan. The proposed study will provide practical information about the usefulness of the intensive lifestyle improvement education program in primary care settings. The study was started in September 2007 and entry of subjects was completed in December 2010. Data on the effect evaluation will be available in 2011.

Trial Registration

UMIN000004049