Evidence on target blood glucose levels

English: Illustration of the changes in blood glucose over time following a high and low GI carbohydrate. Designed and made Public Domain by Scott Dickinson (user: Studio34), Sydney, Australia. (Photo credit: Wikipedia)

Diabetes - type 2 - Evidence
Evidence on target blood glucose levels

There is good evidence from epidemiological and intervention studies that decreasing the HbA_1c level can reduce both the macrovascular and the microvascular complications of type 2 diabetes. There appears to be no threshold below which the risk is no longer reduced, nor a level above which the risk is no longer increased.
Two recent randomized controlled trials (RCTs) comparing intensive blood glucose lowering treatment (targeting an HbA_1c level below 6.0%) with standard treatment (targeting an HbA_1c level between 7.0% and 7.9%) failed to identify a significant improvement in macrovascular vascular outcomes with intensive therapy; one study demonstrated a significant increase in all-cause mortality with intensive therapy, and both studies demonstrated a significant increase in hypoglycaemia with intensive therapy.
In one long-term follow up study, despite an early loss of difference in glycaemic control between a conventional treatment group and an intensive treatment group, a continued reduction in microvascular risk and emergent risk reductions for myocardial infarction and death from any cause were observed during 10 years of post-trial follow-up.
Epidemiological studies have demonstrated a relationship between HbA_1c and vascular complications in people with type 2 diabetes:

• The UK Prospective Diabetes Study 35 (n = 3867) suggested that the lower the HbA_1c level, the better the outcome [UK Prospective Diabetes Study Group et al, 2000]. For every percentage reduction in the HbA_1c level, there is a:
• 21% decrease in risk for any diabetes-related endpoint (95% CI 17 to 24, p < 0.0001).
• 21% decrease in risk for any diabetes-related death (95% CI 15 to 27, p < 0.0001).
• 14% decrease in risk for myocardial infarction (95% CI 8 to 21, p < 0.0001).
• 37% decrease in risk for microvascular complications (95% CI 33 to 41, p < 0.0001).
• There was no indication of a threshold for any complication below which risk no longer decreased, nor a level above which risk no longer increased.

Two recent RCTs investigated the effect of intensive glucose control on vascular outcomes [Action to Control Cardiovascular Risk in Diabetes Study Group, 2008; ADVANCE Collaborative Group, 2008]:

• The Action to Control Cardiovascular Risk in Diabetes (ACCORD) study investigated whether intensive therapy (target HbA_1c level below 6.0%) would reduce cardiovascular events compared with standard therapy (target HbA_1c level between 7.0% and 7.9%) in people with type 2 diabetes [Action to Control Cardiovascular Risk in Diabetes Study Group, 2008]:
• People with type 2 diabetes and either established cardiovascular (CV) disease or additional CV risk factors (n = 10,251) were randomized to receive either intensive therapy targeting an HbA_1c level of less than 6.0% or standard therapy targeting a level of 7.0–7.9%.
• The primary outcome was a composite of the first occurrence of nonfatal myocardial infarction (MI), nonfatal stroke, or death from CV causes.
• Stable median HbA_1c levels of 6.4% (interquartile range 6.1 to 7.0) in the intensive therapy group and 7.5% (interquartile range 7.0 to 8.2) in the standard therapy group were achieved at 1 year and were maintained throughout follow up.
• Intensive therapy was stopped after a mean of 3.5 years follow up because of a higher mortality rate in the intensive therapy group.
• The incidence of nonfatal myocardial infarction (MI), nonfatal stroke, or death from CV causes did not differ between the two groups:
• During follow up, the primary composite outcome occurred in 352 people (6.9%) in the intensive therapy group compared with 371 people (7.2%) in the standard therapy group (hazard ratio [HR] 0.90, 95% CI 0.78 to 1.04; p = 0.16).
• However, all-cause mortality and death from CV causes increased in the intensive therapy group compared with the standard therapy group:
• During follow up, death from any cause occurred in 257 people (5.0%) in the intensive therapy group compared with 203 people (4.0%) in the standard therapy group (HR 1.22, 95% CI 1.01 to 1.46; p = 0.04).
• During follow up, death from CV causes occurred in 135 people (2.6%) in the intensive therapy group compared with 94 people (1.8%) in the standard therapy group (HR 1.35, 95% CI 1.04 to 1.76; p = 0.02).
• Hypoglycaemia requiring assistance and weight gain of more than 10 kg were also more frequent in the intensive therapy group (p < 0.001).
• The ADVANCE study was also designed to investigate the effects of intensive glucose control (using modified-release gliclazide plus other antidiabetic drugs as required to achieve an HbA_1c level of 6.5% or less) on vascular outcomes [ADVANCE Collaborative Group, 2008]:
• People with type 2 diabetes and a history of major macrovascular or microvascular disease or at least one other risk factor for vascular disease (n = 11,140) were randomized to receive either intensive therapy (modified-release gliclazide with the addition of metformin, a glitazone, acarbose, or insulin as needed to attain an HbA_1c level of less than 6.0%) or standard therapy (HbA_1c targets defined on the basis of local guidelines).
• The primary outcomes were a composite of macrovascular events (death from CV causes, nonfatal MI, or nonfatal stroke) and a composite of microvascular events (new or worsening nephropathy or retinopathy), considered both jointly and separately.
• After a median of 5 years of follow up, the mean HbA_1c level was lower in the intensive glucose control group (6.5%) than in the standard glucose control group (7.3%).
• The incidence of combined major macrovascular and microvascular events was reduced with intensive control (18%) compared with standard control (20%): HR 0.90, 95% CI 0.82 to 0.98; p = 0.01.
• The incidence of major microvascular events was also reduced (9.4% compared to 10.9%, HR 0.86, 95% CI 0.77 to 0.97; p = 0.01), primarily because of a reduction in the incidence of nephropathy (4.1% compared to 5.2%, HR 0.79, 95% CI 0.66 to 0.93; p = 0.006), with no effect on retinopathy (p = 0.50).
• The type of glucose control had no effect on major macrovascular events, death from CV causes, or death from any cause.
• Severe hypoglycaemia, although uncommon, was more common in the intensive glucose control group (2.7%) than the standard glucose control group (1.5%): HR 1.8, 95% CI 1.42 to 2.40; p < 0.001.
• A 10-year follow up of UK Prospective Diabetes Study (UKPDS 33) investigated whether intensive glucose-lowering treatment during the early stage of type 2 diabetes had a long-term effect on macrovascular outcomes [Holman et al, 2008].
• In UKPDS 33, 4209 people with newly diagnosed type 2 diabetes were randomized to either conventional therapy (dietary restriction) or intensive therapy (either sulfonylurea or insulin or, in overweight patients, metformin). After the study, 3277 of the participants attended an annual review for 5 years, and completed a questionnaire for a further 5 years. No attempt was made to maintain their previously assigned study treatment.
• Between-group differences in HbA_1c levels were lost after the first year of post-trail follow-up.
• In the sulfonylurea–insulin group compared with the conventional treatment group, reductions in risk persisted at 10 years for any diabetes-related end point (risk ratio [RR] 0.91, 95% CI 0.93 to 0.99) and microvascular disease (RR 0.76, 95% CI 0.64 to 0.89). Reductions in risk for myocardial infarction (RR 0.85, 95% CI 0.74 to 0.97) and death from any cause (0.87, 95% CI 0.79 to 0.96) emerged over time, as more events occurred.
• In the metformin group, reductions in risk persisted for any diabetes-related end point (RR 0.79, 95% CI 0.66 to 0.95), myocardial infarction (RR 0.67, 95% CI 0.51 to 0.89), and death from any cause (RR 0.73, 95% CI 0.59 to 0.89

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Glucose Meter Recall

blood glucose monitor (Photo credit: Wikipedia)

By Robert Lowes
Medscape Medical News

The LifeScan unit of Johnson & Johnson is voluntarily recalling almost 2 million of its OneTouch Verio blood glucose meters because they malfunction at extremely high blood glucose levels.
The recall includes 1.2 million meters sold worldwide under the brand name OneTouch Verio IQ, says LifeScan spokesperson David Detmers. Of those, 90,000 are in the United States. Also recalled are 670,000 OneTouch Verio Pro meters in Europe, and 4,900 OneTouch Verio Pro + meters used in hospitals and clinics in various markets outside the United States.
Each of the One Touch Verio models malfunction a bit differently at blood glucose levels of 1024 mg/dL and higher.
LifeScan is advising US patients using the OneTouch Verio IQ meter to call 1-800-717-0276 to receive a free replacement. They can continue using their current meter as long as they understand the defect, according to LifeScan. However, an unexpected shutoff during testing could indicate extreme high blood sugar,  which warrants contacting a healthcare professional.
The likelihood of anyone experiencing a blood glucose level of 1024 mg/dL is remote, but possible, LifeScan said in a press release. "Because [the OneTouch Verio IQ meters] do not provide an appropriate warning…diagnosis and treatment of extreme hyperglycemia may be delayed or incorrect treatment may be given resulting in potentially serious health risk or fatality."
More information about the recall is available on the Johnson & Johnson web site. 
 To see a version of this story for physicians, visit Medscape, the leading site for physicians and health care professionals.

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Statins, Diabetes, and Attacking a Meta-Analysis

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Source: Evidence Based Medicine

I'm a little late reading the June 19th 2010 Lancet, but was intrigued to find letters in response to the meta-analysis by Sattar et al. looking at whether statin therapy increases the risk of diabetes.

I had previously written about this well-performed meta-analysis, and also written about some unfair ways that people use to try to attack randomized trials, and these letters provide an interesting (at least to me) intersection between these posts.
Letters in academic scientific journals are sociologically revealing. There's typically a polite veneer on even the most vicious attacks. Letters written to European medical journals have a somewhat different feel from those to American medical journals, and letters to the Lancet often seem to have a sneering tone that would be unusual to find in the NEJM or JAMA.
One letter about the meta-analysis objects that the results cease to be statistically significant when diabetes diagnosed only by physician report are excluded, and secondly that the results involved a post-hoc analysis of the data, with the warning that we might fall victim to the logical fallacy, "Post hoc ergo propter hoc".
Are these fair objections?
Diagnosing diabetes by physician report rather than blood glucose measurement is likely to lead to misclassification: some patients will be classified as having diabetes who don't, and some who have diabetes will be missed. In an RCT, though, misclassification like this will almost certainly be random as well, leading to random misclassification bias. Bias of this sort is toward the null hypothesis (no difference between the groups), as you can convince yourself of if you imagine that the classification is perfectly random such that there is no relation between the classification and diabetes. Under such perfect misclassification, the two groups would have equal numbers of patients classified as having diabetes and there would be no difference between treatment and control. In a meta-analysis that found higher rates of diabetes in patients receiving statins, misclassification bias can be expected to have somewhat reduced the true effect, not to have created an effect out of thin air.
The second objection might be called the "post-hoc-ergo-propter-hoc-fallacy fallacy". The actual fallacy is, of course, a way of saying that just because B follows A, you should not conclude that A caused B. This question of causality is central to epidemiologic research and one of the primary reasons for performing randomized trials, which have particular strengths when arguing for causality. The fallacy has nothing to do with performing post hoc analyses of trials. (To be fair, it's possible the letter writer understood this and was being humorous when writing of this fallacy.) The main problem with a post hoc analysis of a randomized trial is that it often involves multiple comparisons/data dredging, where statistical blips are likely to confuse the issue of what is a true effect. As discussed in my earlier post, a prime issue preceding this meta-analysis was whether JUPITER had found just such a random blip or detected a real problem. The meta-analysis' reason for being performed was primarily to answer this question, and in such a setting there is nothing at all concerning about going back to previously conducted RCTs and performing post hoc analyses looking for diabetes effects. No data dredging was involved, and the analysis should not be looked at askance simply for being post hoc. Revealingly, the meta-analysis found an increased risk of diabetes even when data from JUPITER were excluded.
A second letter complained that the analysis would have been better had it been carried out using hazard ratios rather than odds ratios. While this would likely be true, such an analysis was not possible given the information available to the authors, and it is hard to imagine why an OR analysis would have shown statins to be causing diabetes if it were not true. The same letter also re-raised the possibility that statins appeared to be causing people to have more diabetes by keeping them alive longer to develop diabetes. However, the authors had already addressed this in their meta-analysis and reiterated in their response to the letters that differences in survival were much too small to produce such an effect.
A third letter mis-states the definition of a type I error on its way to arguing that the meta-analysis should have used 99% confidence intervals (p-value cutoff of 0.01) for some reason that was not made terribly clear, but seemed related to concerns that a very large meta-analysis would be more likely to detect a spurious result. It is true that given the enormous N in the analysis, it was possible to find a statistically significant difference in diabetes rates that is likely of little clinical significance, but this has nothing to do with the truth or falsehood of the result itself. The letter also argues that the result is biologically implausible, though it does not seem implausible that a medication could increase diabetes rates during the time of a randomized trial, if only by raising blood sugars in patients near the margin between insulin resistance and diabetes.
A fourth letter suggests that the "diabetes" found in the study might be different in terms of patient-important outcomes than the clinical condition we think of as diabetes. That is, statins might be raising blood sugars in a way that is harmless. While this is possible, it's interesting that when a drug class raises blood sugar people are willing to argue it might be harmless, but when a drug class lowers  blood sugar there's a tendency (at least for the manufacturer) to argue that blood sugar control is an excellent surrogate for clinical outcomes. The author of the letter suggests an analysis that might have been done to sort out this issue, which the authors of the meta-analysis correctly point out would not have answered the question.
There were a few other replies to the article, which I have not detailed. Overall, though, this is a fairly typical picture of what happens when someone publishes a trial that conflicts with conventional beliefs, such as "statins are good". This occurs even when the conflict is quite minor -- the meta-analysis merely shows a small increase in diabetes that would be heavily outweighed by cardiovascular benefit in anyone who would be appropriately treated with a statin.
There is no guarantee that the meta-analysis by Sattar et al. is correct about statins and diabetes, but none of the letters published by Lancet raise a sensible reason to think that the post-analysis state of knowledge should change: it is now far more likely than not that statins cause a small increase in diabetes risk. Our response to a meta-analysis like this should be to congratulate the authors on a job well done, while recognizing the possibilities for errors and chance to disrupt the conclusions. It should not be to search high and low for far-fetched flaws that would allow us to discard the inconvenient likelihood that a new statin side-effect has been detected.

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Performance of A1C for the classification and prediction of diabetes.

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Selvin E, Steffes MW, Gregg E, et al. Performance of A1C for the classification and prediction of diabetes. Diabetes Care. 2011 Jan;34(1):84-9. Epub 2010 Sep 20. (Original) PMID: 20855549

Abstract

OBJECTIVE: Although A1C is now recommended to diagnose diabetes, its test performance for diagnosis and prognosis is uncertain. Our objective was to assess the test performance of A1C against single and repeat glucose measurements for diagnosis of prevalent diabetes and for prediction of incident diabetes. RESEARCH DESIGN AND METHODS: We conducted population-based analyses of 12,485 participants in the Atherosclerosis Risk in Communities (ARIC) study and a subpopulation of 691 participants in the Third National Health and Nutrition Examination Survey (NHANES III) with repeat test results. RESULTS: Against a single fasting glucose >/=126 mg/dl, the sensitivity and specificity of A1C >/=6.5% for detection of prevalent diabetes were 47 and 98%, respectively (area under the curve 0.892). Against repeated fasting glucose (3 years apart) >/=126 mg/dl, sensitivity improved to 67% and specificity remained high (97%) (AUC 0.936). Similar results were obtained in NHANES III against repeated fasting glucose 2 weeks apart. The accuracy of A1C was consistent across age, BMI, and race groups. For individuals with fasting glucose >/=126 mg/dl and A1C >/=6.5% at baseline, the 10-year risk of diagnosed diabetes was 88% compared with 55% among those individuals with fasting glucose >/=126 mg/dl and A1C 5.7-<6.5%. CONCLUSIONS: A1C performs well as a diagnostic tool when diabetes definitions that most closely resemble those used in clinical practice are used as the ``gold standard.`` The high risk of diabetes among individuals with both elevated fasting glucose and A1

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