Final Evidence Summary
Diabetes Mellitus (Type 2) in Adults: Screening
June 15, 2008
Recommendations made by the USPSTF are independent of the U.S. government. They should not be construed as an official position of the Agency for Healthcare Research and Quality or the U.S. Department of Health and Human Services.
A Review of the Evidence for the U.S. Preventive Services Task Force
Prepared by: Susan L. Norris, M.D., M.P.H.; Devan Kansagara, M.D.; Christina Bougatsos, B.S.; and Rongwei Fu, Ph.D.
Corresponding Author: Susan L. Norris, M.D., MPH, Department of Medical Informatics and Clinical Epidemiology, Oregon Health & Science University, 3181 SW Sam Jackson Park Road, Mail Stop B1CC, Portland, OR 97239; E-mail: firstname.lastname@example.org.
This report was conducted by the Oregon Evidence-based Practice Center under contract to the Agency for Healthcare Research and Quality (contract no. 290-02-0024, Task order no. 2 for the U.S. Preventive Services Task Force. The investigators involved have declared no conflicts of interest with objectively conducting this research. The findings and conclusions in this document are those of the authors, who are responsible for its content, and do not necessarily represent the views of AHRQ. No statement in this report should be construed as an official position of AHRQ or of the U.S. Department of Health and Human Services.
The information in this report is intended to help clinicians, employers, policymakers, and others make informed decisions about the provision of health care services. This report is intended as a reference and not as a substitute for clinical judgment.
This report may be used, in whole or in part, as the basis for the development of clinical practice guidelines and other quality enhancement tools, or as a basis for reimbursement and coverage policies. AHRQ or U.S. Department of Health and Human Services endorsement of such derivative products may not be stated or implied.
This report was first published in the Annals of Internal Medicine on June 3, 2008 (Ann Intern Med 2008;148:855-68; http://www.annals.org).
Background: More than 19 million Americans are affected by type 2 diabetes mellitus, which is undiagnosed in one third of these persons. In addition, it is estimated that more than 54 million adults have prediabetes. Debate continues over the benefits and harms of screening and then treating adults who have asymptomatic diabetes or prediabetes.
Purpose: To update the 2003 U.S. Preventive Services Task Force review on the evidence for potential benefits and harms of screening adults for type 2 diabetes and prediabetes in primary care settings.
Data Sources: MEDLINE and the Cochrane Library for relevant studies and systematic reviews published in English between March 2001 and July 2007.
Study Selection: Trials and observational studies that directly addressed the effectiveness and adverse effects of screening interventions were included. Randomized, controlled trials were used to assess the effectiveness of diabetes and prediabetes treatments. For diabetes interventions, trials of patients with disease for 1 year or less were included, as well as trials comparing outcomes among diabetic and nondiabetic patients.
Data Extraction: Relevant data were abstracted in duplicate into a standardized template.
Data Synthesis: Data were synthesized in a qualitative manner, and a random-effects meta-analysis of the effects of interventions in prediabetes on the incidence of diabetes was performed.
Limitations: Most of the data on diabetes treatment were not from primary trial data but from subgroup analyses. Participants in intensive lifestyle interventions for prediabetes may not be representative of general prediabetic populations.
Conclusion: Direct evidence is lacking on the health benefits of detecting type 2 diabetes by either targeted or mass screening, and indirect evidence also fails to demonstrate health benefits for screening general populations. Persons with hypertension probably benefit from screening, because blood pressure targets for persons with diabetes are lower than those for persons without diabetes. Intensive lifestyle and pharmacotherapeutic interventions reduce the progression of prediabetes to diabetes, but few data examine the effect of these interventions on long-term health outcomes.
The 2002 National Health and Nutrition Examination Survey estimated that 19.3 million U.S. adults (9.3% of the total U.S. population) had diabetes mellitus, one third of whom had undiagnosed diabetes 1. In addition, 26.0% had impaired fasting glucose and impaired glucose tolerance was even more prevalent 2. The prevalence of diagnosed diabetes is increasing, particularly among obese individuals 3,5. The risk for death among persons with diabetes is about twice that of persons without diabetes, and cardiovascular events account for more than three fourths of these deaths 4.
Type 2 diabetes often goes undiagnosed for many years because hyperglycemia develops gradually and may not produce symptoms 3,5. Persons with diabetes are at increased risk for microvascular and macrovascular complications, and duration of diabetes and degree of hyperglycemia are associated with an increased risk for microvascular complications 6-9. The prevalence of macrovascular complications is elevated in persons with prediabetes (defined as impaired fasting glucose, impaired glucose tolerance, or both) and in persons with newly diagnosed diabetes 10-18. A substantial proportion of persons presenting with a new cardiovascular event have undiagnosed diabetes or prediabetes 10,19-23. Several recent observational studies and a meta-analysis suggest an association between chronic hyperglycemia and cardiovascular disease and stroke 24-27.
Diabetes has a long preclinical phase, estimated at 10 to 12 years on the basis of the progression of microvascular complications 28, and valid and reliable tests can detect type 2 diabetes during this asymptomatic period 29. The previous evidence review for the U.S. Preventive Services Task Force (USPSTF) 29,30 suggested that screening is justified if the ensuing treatments offer incremental net benefits compared with treatment at the time of clinical presentation. In 2003, the USPSTF concluded that the evidence was insufficient to recommend for or against routinely screening asymptomatic adults for type 2 diabetes or prediabetes, but it did recommend screening for adults with hypertension or hyperlipidemia 31.
This review summarizes evidence that has become available since the previous report to inform an update of the 2003 USPSTF recommendations on screening for type 2 diabetes and prediabetes.
The methods of the USPSTF evidence reviews are fully detailed elsewhere 32. The analytic framework (Appendix Figure 1) focuses on decreasing the risk for complications from type 2 diabetes as a result of screening for diabetes. We did not consider secondary prevention studies that exclusively enrolled persons with known cardiovascular disease, because we considered those persons to have a potential preexisting diabetes complication.
We searched MEDLINE and the Cochrane Library for relevant English-language systematic reviews and studies published between March 2001 (6 months before the end date of the previous search) and July 2007 related to 5 key questions. We also examined the reference lists of included studies and ClinicalTrials.gov for relevant trials. We evaluated all studies included in relevant systematic reviews for potential inclusion. We included randomized, controlled trials (RCTs) and observational studies that examined the effectiveness or adverse effects of screening and diagnosis of type 2 diabetes. We used RCTs to assess the effectiveness of diabetes and prediabetes treatments. For diabetes interventions, we included trials with patients who had disease for 1 year or less, as well as trials comparing outcomes among diabetic and nondiabetic populations. We used good-quality systematic reviews to assess the adverse effects of treatment. Search strategies are available in the full evidence report, which can be found at https://www.ncbi.nlm.nih.gov/books/NBK33981/.
An investigator screened titles and abstracts, and a random sample of 1500 titles and abstracts was dual reviewed. Two reviewers examined the full text of potentially relevant articles to achieve consensus on inclusion (Figure 1). Data were abstracted by one investigator and checked by another. We assessed internal validity of individual trials by examining factors that might introduce bias: adequate randomization, allocation concealment, baseline comparability of participants, blinding, and loss to followup. We rated studies as good, fair, or poor quality by using standard USPSTF criteria 32. We rated systematic reviews on the basis of established criteria, and we included only good-quality reviews 33,34. We assessed potential applicability of individual studies to primary care practice on the basis of the methods of participant recruitment and selection.
We identified studies that modeled screening interventions from our main search, as well as from a recent, good-quality systematic review of screening for type 2 diabetes by the National Health Service Research and Development Health Technology Assessment Programme35. We independently abstracted the relevant studies included in that report and relied on their extensive assessments of model quality.
We performed a qualitative synthesis of abstracted data that were generally too heterogeneous for quantitative pooling, except for estimates of the effect of pharmacotherapeutic or lifestyle interventions on diabetes incidence in prediabetic populations. We calculated these pooled estimates by using a hazard ratio and its SE from Cox regression; either a rate ratio or a risk ratio was calculated when a hazard ratio was not reported36-38. We tested for statistical heterogeneity with the standard chi-square test and obtained the overall estimates of relative risk by using a random-effects model 39.
Role of the Funding Source
This study was funded by the Agency for Healthcare Research and Quality (AHRQ) under a contract to support the work of the USPSTF. Agency staff and USPSTF members participated in the initial scope of this work and reviewed interim analyses and the final report. A draft version was distributed to content experts for review. Agency approval was required before this manuscript could be submitted for publication, but the authors are solely responsible for the content and the decision to submit it for publication.
Key Question 1
Is there direct evidence that systematic screening for type 2 diabetes, impaired fasting glucose, or impaired glucose tolerance among asymptomatic adults improves health outcomes?
We identified no RCTs examining the effectiveness of a screening program for type 2 diabetes. A small, good-quality, case-control study did not find benefit from screening when microvascular complications were considered 40. Limited data from 2 cross-sectional studies did not provide good-quality, direct evidence of the effectiveness of screening for type 2 diabetes in either targeted or general populations 41,42.
Of modeling studies identified 35,43-48, 2 recent high-quality studies suggested that targeted screening for type 2 diabetes among persons with hypertension may be relatively cost-effective when macrovascular benefits of optimal blood pressure control are considered 35,47, older persons benefitted more than younger persons 35,47, and screening obese persons was more cost-effective than mass screening 35.
The ADDITION (Anglo-Danish-Dutch Study of Intensive Treatment in People with Screen Detected Diabetes in Primary Care) study 49, currently in progress, may shed light on differences in baseline characteristics and long-term health outcomes between persons with screening-detected diabetes and those who present with symptoms.
Key Question 2
Does beginning treatment of type 2 diabetes early as a result of screening provide an incremental benefit in health outcomes compared with initiating treatment after clinical diagnosis?
We identified no studies that directly explored this question by comparing treatment effects between persons with screening-detected versus clinically detected diabetes, nor did we identify new studies reporting treatment effects in an exclusively screening-detected or recently diagnosed diabetes cohort. Because of the lack of direct evidence, we examined intervention studies comparing treatment effects in diabetic versus nondiabetic populations 50-61 to address the question: "Would early knowledge of a diabetes diagnosis prompt a change in clinical management?"
Tight Glycemic Control
No new, completed studies have examined the effect of glycemic control strategies in persons with newly diagnosed type 2 diabetes since the previous USPSTF review 29. The UKPDS (United Kingdom Prospective Diabetes Study) 62 remains the largest and most influential trial of intensive glycemic control in persons with newly diagnosed, mainly clinically detected, type 2 diabetes. In the UKPDS, persons assigned to intensive glycemic control had a 25% reduction (95% CI, 7% to 40%) in microvascular complications, mostly due to a reduced need for retinal photocoagulation, as well as a nonsignificant 16% relative risk reduction (CI, 71% to 100%) of myocardial infarction 62. The UKPDS investigators estimated that 19.6 persons (CI, 10 to 500 persons) would need to be intensively treated for 10 years to prevent 1 person from developing any single clinical end point 62. A recent meta-analysis combined results from the UKPDS and other older trials examined in the last USPSTF review, and it concluded that tight glycemic control resulted in a modest reduction of macrovascular events, particularly peripheral vascular and cerebrovascular events, in persons with type 2 diabetes (combined incidence rate ratio for any macrovascular event, 0.81 [CI, 0.73 to 0.91]) 27. Examination of the individual trials, however, showed largely nonsignificant results, and it was unclear how overlapping populations from the UKPDS were accounted for in the meta-analysis.
It is unlikely that good-quality trial evidence of the final health benefits of early glycemic control in a screening-detected population will ever be available because withholding treatment from persons with known diabetes is unethical and the length of follow-up required might be prohibitive. The ADDITION study 49 should provide valuable information, although it will be assessing the incremental benefit of very aggressive glycemic control over current standards for glycemic control in a screened population.
Specific Antihypertensive Treatment
There is no clear evidence that persons with diabetes detected by screening would respond differently to specific antihypertensive regimens compared with persons without diabetes. We found no new studies involving antihypertensive agents in screening-detected individuals; however, we identified 2 new trials comparing the effect of different antihypertensive regimens in persons with and those without diabetes (Appendix Table 1) 51,52. The ALLHAT (Antihypertensive and Lipid-Lowering Treatment to Prevent Heart Attack Trial) 51 was an effectiveness trial showing no demonstrable advantage of either a calcium-channel blocker or an angiotensin-converting enzyme inhibitor over a thiazide diuretic in reducing deaths or cardiovascular events in both the diabetes and nondiabetes subgroups. A second study compared verapamil with either a ß-blocker or a thiazide diuretic and found no evidence of a differential effect on cardiovascular outcomes between those with and those without diabetes 52. However, neither trial was originally powered to detect differences between the diabetes and nondiabetes subgroups. A third trial (included in the previous USPSTF review 29 examined persons with hypertension and left ventricular hypertrophy. It showed that persons with diabetes had lower cardiovascular mortality with losartan compared with atenolol, and those without diabetes experienced a reduction in stroke with losartan 53,54.
We identified 1 meta-analysis of antihypertensive trials that compared outcomes between persons with and those without diabetes 63. Angiotensin-receptor blockers provided significantly greater protection against congestive heart failure for those with diabetes than for those without diabetes. All of the studies of angiotensin-converting enzyme inhibitors compared with placebo were secondary prevention trials, except for the HOPE (Heart Outcomes Prevention Evaluation) trial, which was a combination of primary and secondary prevention 64,65 and was included in the previous USPSTF review 29. The HOPE trial showed that persons with type 2 diabetes and at least moderate cardiovascular risk (age > 55 years and 1 additional cardiovascular risk factor) experienced a 25% relative risk reduction (CI, 12% to 36%) in cardiovascular events, cardiovascular deaths, and stroke with ramipril treatment—a similar benefit to that achieved in persons with a history of ischemic heart disease and no diabetes 64,65.
Intensity of Antihypertensive Treatment
As discussed in the previous USPSTF review 29, 1 trial (the HOT [Hypertension Optimal Treatment] trial 66) provided evidence that aggressive blood pressure control in persons with diabetes reduces cardiovascular morbidity. In that trial, the diabetes subgroup experienced a 51% relative risk reduction in cardiovascular events from more aggressive blood pressure control, a greater benefit than that observed in nondiabetic patients 29,66. We did not identify new trials comparing intensive and less intensive blood pressure treatment targets in persons with and without diabetes. A recent meta-analysis presented limited evidence that higher-intensity antihypertensive treatment reduces the risk for major cardiovascular events in persons with diabetes (relative risk, 0.64 [CI, 0.46 to 0.89]) but not in those without diabetes 63; the differential effect on cardiovascular mortality was less clear. The ACCORD (Action to Control Cardiovascular Risk in Diabetes) trial, currently in progress, will examine the relative benefits of very intensive blood pressure control compared with more moderate standards (target systolic blood pressure <120 mm Hg vs. <140 mm Hg) 67.
Initiation of Lipid-Lowering Treatment
Studies of intensive lipid-lowering treatment suggest that persons with diabetes benefit to a similar extent as those without diabetes. For this update, we identified 4 trials (Appendix Table 2) 50,55,57,58 and 1 meta-analysis 68 examining the effects of 3-hydroxy-3-methylglutaryl coenzyme A (HMG-CoA) reductase inhibitors on primary prevention of cardiovascular events and deaths in persons with and without diabetes. In 1 trial, neither the diabetes group nor the nondiabetes subgroup benefited from statin treatment in reducing mortality or cardiovascular event rates, but the rate of nonstudy statin use was high in the control group and the differential reduction in low-density lipoprotein cholesterol between study groups was relatively small 50. In 2 fair-quality trials, statin therapy did not significantly reduce the primary end point (coronary events in 1 trial and coronary and/or stroke events in the other) in the diabetes subgroup, but it did benefit the nondiabetes subgroup 55,58. Comparisons between persons with and those without diabetes were hampered by a relatively low absolute number of events in the diabetes subgroup.
The Heart Protection Study 57 was a large, good-quality RCT examining the efficacy of an HMG-CoA reductase inhibitor in primary and secondary prevention of cardiovascular events and death. Persons with diabetes had a similar reduction in cardiovascular events (relative risk reduction, 27% [CI, 7% to 40%]) as did persons without diabetes who had known vascular disease, and the benefit was independent of initial low-density lipoprotein cholesterol levels. Many in the diabetes subgroup had additional cardiovascular risk factors, including smoking, hypertension, dyslipidemia (high triglyceride and low high-density lipoprotein cholesterol levels), or a combination of these. Although persons with shorter diabetes duration seemed to benefit to a similar extent as those with much longer-duration diabetes, power was insufficient to determine whether participants with newly diagnosed diabetes (that is, ≤1 year) benefited to a significant extent.
A recent meta-analysis of 6 primary prevention trials—the 4 just discussed, an older trial using a fibric acid derivative, and an older statin trial-reported that lipid-lowering drug treatment seemed to be equally efficacious in persons with and those without diabetes 68.
Aspirin for Primary Prevention
The previous USPSTF review 29 included several trials of aspirin for primary prevention of cardiovascular disease. The Antithrombotic Trialists' Collaborative meta-analysis showed a nonsignificant 7% relative risk reduction in the incidence of vascular events in the high-risk diabetic population 69, a result mainly driven by the results of the ETDRS (Early Treatment Diabetic Retinopathy Study), in which the incidence of fatal and nonfatal coronary events decreased in the treatment group (relative risk, 0.83 [CI, 0.66 to 1.04]) 70. In the Physicians' Health Study 71, aspirin was associated with significant cardiovascular risk reduction in persons with diabetes, and the benefit seemed greater in those with diabetes than in those without.
We identified 2 new studies of low-dose aspirin for primary prevention of cardiovascular events in persons with and without diabetes 59,60. In the Primary Prevention Project 59, the subgroup with diabetes did not experience any benefit, whereas the subgroup without diabetes experienced a reduction in the incidence of major cardiovascular and cerebrovascular events (relative risk, 0.59 [CI, 0.37 to 0.94]). This fair-quality study was stopped early, with a resultant low event rate in both groups. Given the small size of the group with diabetes, the trial was probably underpowered to detect a difference in this subgroup. The Women's Health Study 60, a large, good-quality trial, showed that aspirin reduced the incidence of ischemic stroke (relative risk, 0.42 [CI, 0.22 to 0.82]), but not cardiovascular events, in women with diabetes. There was no evidence that the effect of aspirin was significantly more pronounced in women with diabetes than in those without. The difference in results between the Primary Prevention Project 59 and the Women's Health Study 60 may be due to differences in the populations considered or to the differential risks for stroke versus those for myocardial infarction (the rate of stroke was higher than that of myocardial infarction in the Women's Health Study).
Key Question 3
Does beginning treatment of impaired fasting glucose or impaired glucose tolerance early as a result of screening provide an incremental benefit in final health outcomes compared with initiating treatment after clinical diagnosis of type 2 diabetes?
Three studies reported cardiovascular outcomes with intensive lifestyle interventions in persons with prediabetes 36,72,73. In the DPP (Diabetes Prevention Program) 36, neither the cumulative incidence of cardiovascular disease nor the event rate differed among treatment groups; however, the study was not adequately powered to examine these outcomes 74. The STOP-NIDDM (Study to Prevent Non-Insulin-Dependent Diabetes Mellitus) trial 72, in which patients with impaired glucose tolerance were randomly assigned to placebo or acarbose, showed a reduction in cardiovascular events of any type (hazard ratio, 0.51 [CI, 0.28 to 0.95]; absolute risk reduction, 2.5%). However, this study was limited by an attrition rate of 24% overall, with a much higher rate in the treatment group. In the DREAM (Diabetes Reduction Assessment with Ramipril and Rosiglitazone Medication) trial73,75, the incidence rate of the primary composite outcome of cardiovascular events did not significantly differ between the rosiglitazone and placebo groups (hazard ratio, 1.37 [CI, 0.97 to 1.94]) 72 (Appendix Table 3).
Many studies have examined the effect of lifestyle interventions on the incidence of type 2 diabetes among persons with prediabetes 36,38,76-81, several of which36,76,80,81 were included in the previous review 29. In the DPP36, the incidence of diabetes was reduced at 3-year follow-up with an intensive lifestyle intervention (reduction in incidence, 58% [CI, 48% to 66%]) and with treatment with metformin (reduction in incidence, 31% [CI, 17% to 43%]), both compared with placebo. The Finnish Diabetes Prevention study 76 examined a lifestyle intervention, and the incidence rate of diabetes was significantly reduced at mean follow-up of 3.2 years (hazard ratio, 0.4 [CI, 0.3 to 0.7]). This was maintained 3 years after completion of the intervention (hazard ratio, 0.57 [CI, 0.43 to 0.76]) 82. A Chinese study also reported a significant decrease in the incidence of type 2 diabetes at 6-year follow-up with an intensive lifestyle intervention 80. Two smaller, more recent trials examined the effect of lifestyle interventions on incidence rates of diabetes among persons with prediabetes and found a significant decrease in incidence compared with usual care 38,77.
Several recent studies examined the effect of pharmacotherapeutic interventions on diabetes incidence. In the DREAM trial 73,75, rosiglitazone reduced the incidence of diabetes among persons with prediabetes when it was administered for a median of 3.0 years (hazard ratio, 0.38 [CI, 0.33 to 0.44]) 75, whereas ramipril was not effective in reducing the incidence of diabetes 73. In the STOPNIDDM trial 72, the incidence rate of type 2 diabetes was reduced significantly in the acarbose treatment group over the 3.3-year intervention (hazard ratio, 0.75 [CI, 0.63 to 0.90]).
In the XENDOS (XENical in the Prevention of Diabetes in Obese Subjects) study 83, which was rated fair-to-poor quality because of high attrition, orlistat reduced the incidence of type 2 diabetes over 4 years in patients with impaired glucose tolerance (hazard ratio, 0.55 [CI not reported]) 83. A meta-analysis of 3 other studies of orlistat produced similar results 37. Acarbose 84 and metformin 77 also decreased diabetes incidence at up to 3-year follow-up. Two studies of interventions in persons with prediabetes are in progress, and published results are not yet available 85,86.
Results from our meta-analyses showed that the incidence of type 2 diabetes was decreased with lifestyle interventions (pooled hazard ratio, 0.48 [CI, 0.40 to 0.58]) (Appendix Figure 2 and Appendix Figure 3). Pharmacotherapeutic interventions also reduced diabetes incidence (pooled hazard ratio, 0.65 [CI, 0.51 to 0.83]), although the data were statistically heterogeneous largely due to the effect of the rosiglitazone group of the DREAM trial 73.
We did not identify any data to address the question of whether there should be different treatment targets for lipid levels and blood pressure for persons with prediabetes compared with normoglycemic persons.
We identified only 1 study examining the comparative effectiveness of different medications for treating hyperlipidemia, hypertension, and cardiovascular disease among persons with prediabetes versus those with normoglycemia. The ALLHAT 51 examined various antihypertensive therapies among persons with diabetes, impaired fasting glucose, and normoglycemia and failed to demonstrate superiority for an angiotensin-converting enzyme inhibitor or a calcium-channel blocker compared with a thiazide-type diuretic across the 3 glycemic strata for the composite outcome of coronary heart disease death and nonfatal myocardial infarction.
Modeling studies have been used to examine the treatment of prediabetes 35,87-94. The health technology assessment by Waugh and colleagues 35recommended screening for glucose intolerance because strategies for reducing cholesterol and blood pressure are effective and because type 2 diabetes can be prevented. Waugh and colleagues seem to assume that the effects of treating persons with screening-detected diabetes are the same as those of treating persons with clinically detected diabetes and that there are proven linkages between treating dysglycemia and final health outcomes. They also systematically reviewed published economic models and noted that, despite the variable quality, structure, and assumptions of the models, all predicted that delaying the onset of diabetes would substantially reduce the incidence of vascular complications, improve quality of life, and avoid future medical costs. They concluded that if a screening program was implemented to target persons at risk for diabetes, subsequent treatment for persons with impaired glucose tolerance with lifestyle or pharmacologic interventions was a good use of resources.
Herman and associates 90 examined the lifetime utility and cost-effectiveness of the DPP lifestyle intervention 36 and found the intervention to be relatively cost-effective (cost per quality-adjusted life-year, $8800 [from a societal perspective]), with a 0.5-year gain in life expectancy and 20% decrease in diabetes incidence. Results were somewhat less marked with metformin, which was still relatively cost-effective.
Eddy and colleagues 87,88 examined the DPP interventions and also predicted large absolute reductions in the proportion of persons developing type 2 diabetes and a delay of 7 to 8 years in onset of diabetes, as well as that the DPP lifestyle intervention will lead to fewer complications and improved quality-adjusted life-years 95. They, however, estimated much higher marginal cost-effectiveness ratios than did Herman and associates 96.
Several other models recently evaluated primary prevention of type 2 diabetes among persons with impaired glucose tolerance 91,92,94,97, and all demonstrated relative cost-effectiveness of lifestyle interventions. Two models examined metformin and found it to be cost-saving under many conditions 92,97.
Key Question 4
What adverse effects result from screening a person for type 2 diabetes, impaired fasting glucose, or impaired glucose tolerance?
Data are sparse on the psychological effects of screening for type 2 diabetes, and none of the data that we identified suggested significant adverse effects at up to 1-year follow-up 98-110. In the ADDITION study 103, stepwise screening had limited effects on anxiety levels at up to 1-year follow-up. In a cross-sectional study, Skinner and colleagues 109 did not find that screening high-risk patients for type 2 diabetes with an oral glucose tolerance test was associated with significant anxiety. Other included studies also did not report any serious psychological effects of a new diagnosis of type 2 diabetes 98-104,107,108,110.
Several studies compared persons with screening-detected diabetes with persons without diabetes. Using Hoorn observational data, Adriaanse and colleagues 100 found no significant differences in well-being and health-related quality of life between patients with newly diagnosed diabetes and those at high risk but without diabetes at 2-week and 1-year follow-ups. Poorer quality-of-life scores at 6-month follow-up in the group with diabetes may suggest a temporary effect. Similar results were found in several other studies 98,104,107. In the ADDITION study 102,103,110, persons with screening-detected diabetes generally reported low emotional distress, with some differences in distress and self-efficacy noted between groups treated intensively compared with usual care.
We identified no studies that addressed the effects of a false-positive result from any of the tests used to screen for dysglycemia. We identified no studies that directly addressed labeling of persons with screening-detected diabetes and no studies that examined the effect of a diagnosis of prediabetes.
Key Question 5
What adverse effects result from treating a person with type 2 diabetes, impaired fasting glucose, or impaired glucose tolerance detected by screening?
Recent systematic reviews of the adverse effects of drugs used in treating type 2 diabetes and prediabetes 111-136 reveal some important new data related to the safety to thiazolidinediones. An association between rosiglitazone and increased risk for myocardial infarction 134,137 and heart failure 134 was noted recently. For other drugs examined in the studies included in this review, we identified no new data on severe adverse effects compared with data available at the time of the previous USPSTF review 29. Intensive glucose control in the UKPDS was not associated with high rates of hypoglycemia (0.55% annual incidence of major hypoglycemia) 138. Relatively common side effects, such as cough with angiotensin-converting enzyme inhibitors and gastrointestinal effects with acarbose, should be considered when prescribing these drugs, but they are not associated with increased deaths or adverse cardiovascular outcomes.
No direct evidence clearly determines whether screening asymptomatic individuals for diabetes or prediabetes alters health outcomes (Table 1). Evidence shows that persons with diabetes benefit from control of blood pressure and lipid levels, but studies have not included persons with screening-detected diabetes. Persons with hypertension and type 2 diabetes benefit from lower blood pressure targets than persons with hypertension but without diabetes 66. Persons with newly diagnosed, largely clinically detected, diabetes benefit from intensive glycemic control, largely because of a reduction in microvascular events 62. Evidence shows that intensive lifestyle modification in persons with prediabetes—an implicitly screening-detected population—delays the progression to clinical diabetes, but whether treatment alters final health outcomes is unknown because studies were not powered for those outcomes or were not of sufficient duration.
Table 2 and Table 3 show the numbers needed to screen to prevent an outcome of interest in different theoretical populations. These outcomes have not changed from the estimates of the previous USPSTF review 29 because we identified no new data on the effectiveness of these interventions. As noted elsewhere 29, interventions that target cardiovascular events produce greater effects than those that target microvascular complications occurring later in the disease process.
On the basis of the DPP 36 and the Finnish Diabetes Prevention Study 76, screening 1000 persons with prediabetes will delay 44 cases of type 2 diabetes over 3.0 years. Pharmacotherapy with metformin (on the basis of DPP data 36) produced a somewhat less favorable number needed to screen. Many important assumptions underlying number-needed-to-screen estimates remain, including length of the asymptomatic period, prevalence of undiagnosed diabetes or prediabetes, incidence rates of diabetes complications, and treatment effect.
Screening targeted to populations at risk for diabetes would probably increase the yield and economic efficiency of screening, and risk scores have been developed to identify those at high risk for diabetes 139-144. In the DPP, older age and higher body mass index increased the yield of screening across ethnic groups 145. On the other hand, the prevalence of diagnosed diabetes in certain high-risk groups, such as non-Hispanic black persons and Mexican-American persons, has increased, whereas the proportion of persons with undiagnosed disease in those groups has decreased, suggesting that opportunistic screening targeted to populations at high risk may already be occurring. This trend reduces the prevalence of undiagnosed diabetes and increases the number needed to screen to prevent adverse events in the remaining unscreened group 1.
A diabetes population of significant interest to a screening program would be individuals who would benefit from aggressive interventions to reduce macrovascular complications in persons who would not have been otherwise identified through recommended hypertension and hyperlipidemia screening 31. Many persons with diabetes are hypertensive or have additional cardiovascular disease risk factors, and those with the highest cardiovascular risk profiles are likely to benefit most from treatment 57,62,146-148. As shown in the Heart Protection Study 63, elevated low-density lipoprotein cholesterol levels alone may not identify many persons with diabetes and dyslipidemia who might benefit from lipid-lowering treatment, but this population had higher-than-average cardiovascular risk profiles. The benefit of identifying and treating asymptomatic diabetes in normotensive, nondyslipidemic persons at average cardiovascular risk is unclear.
The potential yield of diabetes and prediabetes screening must be weighed carefully against the potential harms of screening and diagnosis. We did not identify evidence suggesting serious adverse effects of screening for type 2 diabetes. The literature does, however, have important limitations. Included studies examined persons at high risk for diabetes, and thus the results may not be applicable to mass screening programs that are not targeted 98-100. Theoretical concerns include the effects of labeling 149 on anxiety and insurability, but available evidence is insufficient to support or refute these concerns.
Several limitations deserve mention. First, we restricted our review of diabetes treatment to studies with mean diabetes duration of 1 year or less, because we felt that these patient populations would most closely resemble screening-detected populations. Individuals with longstanding type 2 diabetes will likely show greater benefits from treatment, so focusing on treatment of early disease, in the absence of trials with extended follow-up, may underestimate the effectiveness of treatment and therefore screening interventions. For studies comparing a given treatment among persons with and persons without type 2 diabetes, we included studies of any duration of disease, and the applicability of these data to populations with screening-detected disease is uncertain. Second, attempts to divide patients with diagnosed diabetes into those with a "clinical diagnosis" based on symptoms and those deemed to be "screened" because of alleged asymptomatic status does not truly compare "not screened" with "screened" patients. Third, participants with prediabetes in studies of intensive lifestyle interventions may not be representative of general prediabetic populations. For example, the level of physical inactivity in the DPP cohort was less than that reported in the Third National Health and Nutrition Examination Survey 150. Fourth, most of the data on diabetes treatment were from prespecified subgroup analyses of large trials that included both diabetic and nondiabetic populations. The diabetes and nondiabetes subgroups had important differences, and subgroup analyses were often underpowered to demonstrate significant changes in primary outcomes. Prevention trials among persons with prediabetes were powered to examine the primary outcome of new cases of diabetes and not to examine long-term health outcomes, such as cardiovascular events.
Models rely on data from trials and observational studies and are only as good as the data and assumptions underlying them. All 7 models that we identified that examined the effect of screening interventions 35,43-48 lack transparency to some degree, and all have had 1 or more of their important underlying assumptions criticized 35.
Further research is needed to define the benefits and harms of screening average-risk individuals for type 2 diabetes. We must learn whether early, aggressive glycemic control in persons with diabetes produces improvements in clinical outcomes after many years of follow-up 151. An extension of the largest study of an initial strategy of sustained tight glycemic control in type 1 diabetes 152 suggested that participants originally randomly assigned to tight glycemic control had a significant reduction in cardiovascular events at long-term follow-up despite similar glycemic control in the control group during the postrandomization period 153. To date, similar data are unavailable for type 2 diabetes. We also need studies to define the duration of the prediabetes phase and identify measurable risk factors for progression to diabetes and its complications, particularly cardiovascular disease.
The cost-effectiveness of diabetes screening programs is considered to be mainly determined by the long-term health benefits rather than the cost of detection and treatment of diabetes 154. Thus, intervention research needs to continue focusing on long-term, sustainable interventions that affect health outcomes in real-world settings. Further work is also needed to examine the effect of screening and diagnosis on patient self-efficacy, motivation for lifestyle change, and the potential psychological effects of labeling.
Direct evidence is lacking on the health benefits of detecting type 2 diabetes by either targeted or mass screening, and indirect evidence also fails to demonstrate health benefits for screening general populations or persons at high risk for diabetes complications without hypertension. Persons with hypertension do benefit from knowing their diagnosis of diabetes, because blood pressure targets are lower than for nondiabetic persons. Although intensive lifestyle interventions delay or prevent diabetes onset in persons with prediabetes, positive effects of this delay on long-term health outcomes have not been adequately demonstrated.
Acknowledgment: The following people provided valuable guidance and insights: Mark Helfand, MD, MPH, Evelyn Whitlock, MD, MPH, and Peggy Nygren, MA, of the Oregon Evidence-based Practice Center; Tracy Wolff, MD, MPH, and Mary Barton, MD, MPP, at the Agency for Healthcare Research and Quality; and the U.S. Preventive Services Task Force members Ned Calonge, MD, Russ Harris, MD, MPH, George Isham, MD, MS, and Virginia Moyer, MD, MPH. The authors thank Andrew Hamilton, MLS, MS, for assistance in developing and running search strategies; Peggy Nygren, MA, and Tracy Dana, MLS, for assistance with data abstraction; and Sarah Baird, MS, for technical assistance.
Grant Support: This report was conducted by the Oregon Evidence-based Practice Center under contract to the Agency for Healthcare Research and Quality (contract no. 290-02-0024, Task order no. 2 for the U.S. Preventive Services Task Force.
Potential Financial Conflicts of Interest: None disclosed.
Requests for Single Reprints: Reprints are available from the Agency for Healthcare Research and Quality Web site (https://www.uspreventiveservicestaskforce.org/).
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- Strippoli GF, Bonifati C, Craig M, Navaneethan SD, Craig JC. Angiotensin converting enzyme inhibitors and angiotensin II receptor antagonists for preventing the progression of diabetic kidney disease. Cochrane Database Syst Rev 2006:CD006257. [PMID: 17054288]
- Strippoli GF, Craig M, Deeks JJ, Schena FP, Craig JC. Effects of angiotensin converting enzyme inhibitors and angiotensin II receptor antagonists on mortality and renal outcomes in diabetic nephropathy: systematic review. BMJ 2004;329:828. [PMID: 15459003]
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- Verdecchia P, Angeli F, Gattobigio R, Reboldi GP. Do angiotensin II receptor blockers increase the risk of myocardial infarction? Eur Heart J 2005;26:2381-6. [PMID: 16081468]
- McQuaid KR, Laine L. Systematic review and meta-analysis of adverse events of low-dose aspirin and clopidogrel in randomized controlled trials. Am J Med 2006;119:624-38. [PMID: 16887404]
- Berger JS, Roncaglioni MC, Avanzini F, Pangrazzi I, Tognoni G, Brown DL. Aspirin for the primary prevention of cardiovascular events in women and men: a sex-specific meta-analysis of randomized controlled trials. JAMA 2006;295:306-13. [PMID: 16418466]
- Wiysonge CS, Bradley H, Mayosi BM, Maroney R, Mbewu A, Opie LH, et al. Beta-blockers for hypertension. Cochrane Database Syst Rev 2007:CD002003. [PMID: 17253471]
- Bolen S, Feldman L, Vassy J, Wilson L, Yeh HC, Marinopoulos S, et al. Systematic review: comparative effectiveness and safety of oral medications for type 2 diabetes mellitus. Ann Intern Med 2007;147:386-99. [PMID: 17638715]
- Gangji AS, Cukierman T, Gerstein HC, Goldsmith CH, Clase CM. A systematic review and meta-analysis of hypoglycemia and cardiovascular events: a comparison of glyburide with other secretagogues and with insulin. Diabetes Care 2007;30:389-94. [PMID: 17259518]
- Saenz A, Fernandez-Esteban I, Mataix A, Ausejo M, Roque M, Moher D. Metformin monotherapy for type 2 diabetes mellitus. Cochrane Database Syst Rev 2005:CD002966. [PMID: 16034881]
- Salpeter S, Greyber E, Pasternak G, Salpeter E. Risk of fatal and nonfatal lactic acidosis with metformin use in type 2 diabetes mellitus. Cochrane Database Syst Rev 2006:CD002967. [PMID: 16437448]
- Salpeter SR, Greyber E, Pasternak GA, Salpeter EE. Risk of fatal and nonfatal lactic acidosis with metformin use in type 2 diabetes mellitus: systematic review and meta-analysis. Arch Intern Med 2003;163:2594-602. [PMID: 14638559]
- Setter SM, Iltz JL, Thams J, Campbell RK. Metformin hydrochloride in the treatment of type 2 diabetes mellitus: a clinical review with a focus on dual therapy. Clin Ther 2003;25:2991-3026. [PMID: 14749143]
- Bonovas S, Sitaras NM. Does pravastatin promote cancer in elderly patients? A meta-analysis. CMAJ 2007;176:649-54. [PMID: 17325332]
- McClure DL, Valuck RJ, Glanz M, Hokanson JE. Systematic review and meta-analysis of clinically relevant adverse events from HMG CoA reductase inhibitor trials worldwide from 1982 to present. Pharmacoepidemiol Drug Saf 2007;16:132-43. [PMID: 17072896]
- Law M, Rudnicka AR. Statin safety: a systematic review. Am J Cardiol 2006;97:52C-60C. [PMID: 16581329]
- Silva MA, Swanson AC, Gandhi PJ, Tataronis GR. Statin-related adverse events: a meta-analysis. Clin Ther 2006;28:26-35. [PMID: 16490577]
- Norris SL, Carson S, Roberts C. Drug Class Review on Thiazolidinediones. Portland, OR: Oregon Health & Science University; May 2006. Assessed on 8 April 2008 at http://ohsu.edu/drugeffectiveness/reports/final.cfm.
- Richter B, Bandeira-Echtler E, Bergerhoff K, Clar C, Ebrahim SH. Rosiglitazone for type 2 diabetes mellitus. Cochrane Database Syst Rev 2007:CD006063. [PMID: 17636824]
- Richter B, Bandeira-Echtler E, Bergerhoff K, Clar C, Ebrahim SH. Pioglitazone for type 2 diabetes mellitus. Cochrane Database Syst Rev 2006: CD006060. [PMID: 17054272]
- Singh S, Loke YK, Furberg CD. Long-term risk of cardiovascular events with rosiglitazone: a meta-analysis. JAMA 2007;298:1189-95. [PMID: 17848653]
- Norris SL, Zhang X, Avenell A, Gregg E, Schmid CH, Lau J. Pharmacotherapy for weight loss in adults with type 2 diabetes mellitus. Cochrane Database Syst Rev 2005:CD004096. [PMID: 15674929]
- Li Z, Maglione M, Tu W, Mojica W, Arterburn D, Shugarman LR, et al. Meta-analysis: pharmacologic treatment of obesity. Ann Intern Med 2005;142:532-46. [PMID: 15809465]
- Nissen SE, Wolski K. Effect of rosiglitazone on the risk of myocardial infarction and death from cardiovascular causes. N Engl J Med 2007;356:2457-71. [PMID: 17517853]
- Wright AD, Cull CA, Macleod KM, Holman RR; for the UKPDS Group. Hypoglycemia in type 2 diabetic patients randomized to and maintained on monotherapy with diet, sulfonylurea, metformin, or insulin for 6 years from diagnosis: UKPDS73. J Diabetes Complications 2006;20:395-401. [PMID: 17070446]
- Stern MP, Williams K, Haffner SM. Identification of persons at high risk for type 2 diabetes mellitus: do we need the oral glucose tolerance test? Ann Intern Med 2002;136:575-81. [PMID: 11955025]
- Lorenzo C, Okoloise M, Williams K, Stern MP, Haffner SM. San Antonio Heart Study. The metabolic syndrome as predictor of type 2 diabetes: the San Antonio heart study. Diabetes Care 2003;26:3153-9. [PMID: 14578254]
- Lindstrom J, Louheranta A, Mannelin M, Rastas M, Salminen V, Eriksson J, et al. The Finnish Diabetes Prevention Study (DPS): lifestyle intervention and 3-year results on diet and physical activity. Diabetes Care 2003;26:3230-6. [PMID: 14633807]
- Wilson PW, Meigs JB, Sullivan L, Fox CS, Nathan DM, D'Agostino RB Sr. Prediction of incident diabetes mellitus in middle-aged adults: the Framingham Offspring Study. Arch Intern Med 2007;167:1068-74. [PMID: 17533210]
- Greaves CJ, Stead JW, Hattersley AT, Ewings P, Brown P, Evans PH. A simple pragmatic system for detecting new cases of type 2 diabetes and impaired fasting glycaemia in primary care. Fam Pract 2004;21:57-62. [PMID: 14760046]
- Schmidt MI, Duncan BB, Bang H, Pankow JS, Ballantyne CM, Golden SH, et al. Identifying individuals at high risk for diabetes: the Atherosclerosis Risk in Communities study. Diabetes Care 2005;28:2013-8. [PMID: 16043747]
- Diabetes Prevention Program Research Group. Strategies to identify adults at high risk for type 2 diabetes: the Diabetes Prevention Program. Diabetes Care 2005;28:138-44. [PMID: 15616247]
- UK Prospective Diabetes Study (UKPDS) Group. Effect of intensive blood-glucose control with metformin on complications in overweight patients with type 2 diabetes (UKPDS 34). Lancet 1998;352:854-65. [PMID: 9742977]
- Colhoun HM, Betteridge DJ, Durrington PN, Hitman GA, Neil HA, Livingstone SJ, et al. Primary prevention of cardiovascular disease with atorvastatin in type 2 diabetes in the Collaborative Atorvastatin Diabetes Study (CARDS): multicentre randomised placebo-controlled trial. Lancet 2004;364:685-96. [PMID: 15325833]
- Stamler J, Vaccaro O, Neaton JD, Wentworth D. Diabetes, other risk factors, and 12-yr cardiovascular mortality for men screened in the Multiple Risk Factor Intervention Trial. Diabetes Care 1993;16:434-44. [PMID: 8432214]
- Grimes DA, Schulz KF. Uses and abuses of screening tests. Lancet 2002;359:881-4. [PMID: 11897304]
- Kriska AM, Edelstein SL, Hamman RF, Otto A, Bray GA, Mayer-Davis EJ, et al. Physical activity in individuals at risk for diabetes: Diabetes Prevention Program. Med Sci Sports Exerc 2006;38:826-32. [PMID: 16672833]
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- Nathan DM, Cleary PA, Backlund JY, Genuth SM, Lachin JM, Orchard TJ, et al. Intensive diabetes treatment and cardiovascular disease in patients with type 1 diabetes. N Engl J Med 2005;353:2643-53. [PMID: 16371630]
- Zhang P, Engelgau MM, Valdez R, Benjamin SM, Cadwell B, Narayan KM. Costs of screening for pre-diabetes among US adults: a comparison of different screening strategies. Diabetes Care 2003;26:2536-42. [PMID: 12941715]
- Barzilay JI, Jones CL, Davis BR, Basile JN, Goff DC Jr, Ciocon JO, et al. Baseline characteristics of the diabetic participants in the Antihypertensive and Lipid-Lowering Treatment to Prevent Heart Attack Trial (ALLHAT). Diabetes Care 2001;24:654-8. [PMID: 11315826]
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- Gerstein HC, Yusuf S, Holman R, Bosch J, Pogue J. The DREAM Trial Investigators. Rationale, design and recruitment characteristics of a large, simple international trial of diabetes prevention: the DREAM trial. Diabetologia 2004;47:1519-27. [PMID: 15322749]
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This is a flow diagram which shows the steps that two reviewers used to examine the full text of potentially relevant articles to achieve consensus on inclusion. It shows a text boxes in sequential steps.
This box arrows down to another box, and in the middle of the vertical arrow, there is a horizontal arrow pointing to another text box on the right.
Box 2: Articles excluded during abstract review (n=7409)
Box 3: Full-text articles reviewed for more detailed evaluation (n = 1184)
Box 3 arrows down to another box, and in the middle of the vertical arrow, there is a horizontal arrow pointing to another text box on the right.
Box 4 is a text box with a list:
Excluded articles (n = 848):
Diabetes treatment study with diabetes duration >1 y: 143
Diabetes treatment study with unknown diabetes duration: 5
Wrong patient population: 92
Wrong treatment/intervention: 55
Wrong outcome: 128
Wrong study design or publication type or no data: 422
Non-English-language study: 3
Excluded background articles (n = 246)
Included studies (in 90 articles) (n = 69)
Box 5 arrows down to a row of 5 text boxes, one for each Key Question. The row of boxes will be described from left to right starting with the box for Key Question (KQ) 1.
Included studies for KQ1 (screening and outcomes):
Research studies (n = 3)
Modeling studies (n = 7)
Included studies for KQ2 (diabetes interventions):
Research studies (in 11 articles) (n = 8)
Systematic reviews (n = 2)
Included studies for KQ3 (prediabetes interventions):
Research studies (in 25 articles) (n = 11)
Modeling studies (in 8 articles) (n = 6)
Included studies for KQ4 (adverse effects of screening):
Research studies (n = 8)
Included studies for KQ5 (adverse effects of treatment):
Systematic reviews (in 26 articles) (n = 24)
KQ = key question.
*Cochrane databases were the Cochrane Central Register of Controlled Trials, Cochrane Database of Systematic Reviews, and Database of Abstracts of Reviews of Effects.
†Other sources were reference lists and expert referrals.
- Is there direct evidence that systematic screening for type 2 diabetes, impaired fasting glucose, or impaired glucose tolerance among asymptomatic adults improves health outcomes?
- Does beginning treatment of type 2 diabetes early as a result of screening provide an incremental benefit in health outcomes compared with initiating treatment after clinical diagnosis?
- Does beginning treatment of impaired fasting glucose or impaired glucose tolerance early as a result of screening provide an incremental benefit in final health outcomes compared with initiating treatment after clinical diagnosis of type 2 diabetes?
- What adverse effects result from screening a person for type 2 diabetes, impaired fasting glucose, or impaired glucose tolerance?
- What adverse effects result from treating a person with type 2 diabetes, impaired fasting glucose, or impaired glucose tolerance detected by screening?
At the top of the chart is a horizontal line with a circle on it labeled “KQ1” for “key question #1” right in the middle of the line. This line connects the word “Screening” on the far top left of the chart to a rectangle at the far right, labeled “Final outcomes.”
The screening types are listed as follows:
- Hemoglobin A1c
- Fasting blood glucose
- Oral glucose tolerance test
The final outcomes are listed as follows:
- Quality of life
- Cardiovascular mortality
- Lower-extremity amputations
- Nonhealing ulcers
- Severe visual impairment
- Stage IV and V chronic kidney disease
- Symptomatic neuropathy
Beneath the line for KQ1 is another line running parallel with a circle labeled KQ2 and another circle to the right on the same line labeled KQ3. At the left of the line is a list entitled "Treatment interventions in screening-detected persons or persons with diabetes duration ≤ 1 y". Below that heading is a list as follows:
- Glycemic control
- Blood pressure control
- Lipid treatment
- Counseling for lifestyle change
- Foot care
The horizontal line continues to the right of the KQ3 circle and joins up with the vertical arrow to the "Final outcomes" list, connecting the list of treatment interventions to the line leading to the Final Outcomes list..
Below the list entitled "Screening" a second major section of the flowchart starts. It begins with the phrase "Asymptomatic adults" and there is a curved line with two circles below it to the right of the phrase. The first circle is labeled "KQ4" and it points to another circle with the phrase "Harms of screening". To the right of the line from "KQ4" is a lozenge-shaped rectangle with the following text in it:
- Impaired fasting glucose
- Impaired glucose tolerance
The horizontal line continues to the right of the rounded square box to another curved line with two circles below it. The first circle is labeled "KQ5" and it has a curved arrow pointing to the circle labeled "Harms of treatment".
To the right of those circles the horizontal line ends with an arrow pointing to a lozenge-shaped rectangle with the label "Intermediate outcome" directly above it. Inside the text box are the words "Incidence of type 2 diabetes". A broken horizontal line line continues to the right of the text box and ends in an arrow pointing to the "Final outcomes box".
Below the flow chart is a note indicating that KQ = key question.
Figure 2 shows a table with the relative risk of diabetes incidence in lifestyle trials using data from various studies. The relative risk range is also shown graphically in a bar chart to the right of the table.
|Study, Year (Reference)||Follow-up, y||Participants, n||Relative Risk
|Control Group||Intervention Group|
|Pan et al., 199780||6||133||397||0.60 (0.43-0.83)|
|Tuomilehto et al., 200176||3.2||257||265||0.40 (0.26-0.61)|
|DPP*, 200236||2.8||1082||1079||0.44 (0.38-0.50)|
|Kosaka et al., 200538||4||356||102||0.32 (0.11-0.96)|
|Ramachandran et al., 200677||3||136||133||0.62 (0.42-0.92)|
|All studies combined||0.48 (0.40-0.58)|
Test for heterogeneity: Q = 6.104; P = 0.192
The bar chart shows that those studies with a relative risk under 1.00 favors intervention.
Figure 3 shows a table with the relative risk of diabetes incidence in drug trials using data from various studies. The relative risk range is also shown graphically in a bar chart to the right of the table.
|Study, Year (Reference)||Drug||Follow-up, y||Participants, n||Relative Risk
|Control Group||Intervention Group|
|Heymsfield et al., 200037||Orlistat||2||53||67||0.40 (0.08-2.08)|
|Chiasson et al., 200272||Acarbose||3.3||715||714||0.75 (0.63-0.90)|
|DPP*, 200236||Metformin||2.8||1082||1073||0.71 (0.62-0.81)|
|Torgerson et al., 200483||Orlistat||4||1637||1640||0.63 (0.46-0.86)|
|DREAM*, 200675||Rosiglitazone||3||2635||2634||0.38 (0.31-0.47)|
|DREAM*, 200673||Ramipril||3||2646||2623||0.91 (0.77-1.08)|
|Ramachandran et al., 200677||Metformin||3||136||133||0.65 (0.44-0.96)|
|All studies combined||0.65 (0.51-0.83)|
Test for heterogeneity: Q = 23.466; P = 0.001
The bar chart shows that those studies with a relative risk under 1.00 favors intervention.
|Variable||Design||Limitations||Consistency||Primary Care Applicability||Overall
|KQ1: overall effect of screening on final outcomes||3 studies.||Case-control and cross-sectional studies.40-42||Data were limited; studies considered microvascular complications only.||Studies were consistent.||Case-control study was representative of a primary care population, but results did not represent population-level results from a screening program. Fair-quality cross-sectional study was a non-U.S. population in an area of high screening rates and national registries; however, an unknown percentage was clinically detected.||Poor||Both fair-quality studies demonstrated no benefit for screening:
Case-control study: Patients with ≥1 glucose screening event in 10 years had a 13% reduction in risk for severe microvascular T2DM complications.
Cross-sectional study: No significant differences between T2DM population and general Swedish population (where there is a high level of screening for T2DM) in most measures of visual acuity.
One poor-quality study showed NSD.
|KQ2: diabetes treatment||8 studies.||RCTs with diabetes vs. nondiabetes (subgroup analyses); RCTs with duration of T2DM ≤1 y. 50-52,55,57-61||Several studies were probably underpowered for the diabetes subgroup. Baseline characteristics differed between the diabetes and nondiabetes subgroups.||Studies generally showed no evidence of a significant differential effect between diabetes and nondiabetes subgroups.||Studies were representative of a primary care population, but results did not represent population-level results from a screening program.||Fair||Persons with T2DM without known CVD seem to benefit from aggressive lipid-lowering treatment as much as persons without T2DM with known CVD. There is little strong evidence that specific antihypertensive drugs benefit persons with T2DM more than those without. Persons with T2DM seem to benefit from a lower BP target than persons without. Fair evidence suggests a marginal benefit of aspirin for primary prevention of CVD, although no clear evidence suggests that those with diabetes benefit more than other subgroups at high risk for CVD.|
|KQ3: prediabetes treatment||11 studies.||RCTs 36-38,72,75-79,83,84||Mean follow-up, approximately 3 years; longest follow-up, 7 years; only 3 studies examined long-term health outcomes.||Lifestyle and drug interventions consistently produced a decrease in incidence of T2DM.||Trials consisted of highly selected participants.||Fair||Intensive lifestyle and pharmacotherapeutic interventions reduce the progression of prediabetes to T2DM at follow-up up to 7 years. Few data exist on the effect of these interventions on cardiovascular events, death, or other long-term health outcomes.|
|KQ4: adverse effects of screening||8 studies||Cohort and cross-sectional studies. 98-100,103-105,107,109||All observational studies; predominantly white; study samples composed of volunteers; short follow-up.||It is difficult to compare results across studies because of heterogeneous outcome measures and comparison groups; however, no serious adverse effects were noted.||Studies included persons at high risk for T2DM, so results may not be applicable to primary care populations.||Fair to poor.||Data were sparse on the psychological effects of screening for T2DM, and no available data suggested significant adverse effects at up to 1-year follow-up. No study reported serious, long-term, adverse effects of a new diagnosis of T2DM.|
|KQ5: adverse effects of treatment||24 studies.||Systematic reviews. 111-113,115-124,126-136||Reviews were almost entirely based on trials of short to moderate duration; long-term data were lacking.||Not applicable; different drugs were examined in each review.||Included studies were largely trials of selected populations with limited applicability to real-world, primary care populations.||Fair||Acarbose: NSD in death from placebo; gastrointestinal side effects common.
Metformin: NSD in death, hypoglycemia, lactic acidosis vs. placebo or diet.
ACE-I: significant increase in cough vs. placebo.
β-Blockers: increase in withdrawals secondary to adverse events vs. placebo; NSD in total deaths.
Rosiglitazone: new data on potential for increased risk for cardiac events and heart failure.
a ACE-I = angiotensin-converting enzyme inhibitor; BP = blood pressure; CVD = cardiovascular disease; NSD = no significant difference; RCT = randomized, controlled trial; T2DM = type 2 diabetes mellitus.
|Prevalence of Undiagnosed Disease||Patient Population||Tight Glycemic Control to Prevent 1 Case of Blindness in 1 Eye (Screening 1000 People with Given Prevalence)||Tight Blood Pressure Control to Prevent 1 CVD Event (Screening 1000 Hypertensive People with Given Prevalence)|
|Increase in Persons with Tight Glycemic Control, %||Cases of Blindness Averted, nb||NNS||Increase in Persons with Tight Blood Pressure Control, %||CVD Events Averted, nc||NNS|
|2.8%||Standardized prevalence in U.S.c||50||0.06||16,420||50||0.53||1,905|
|3.6%||Standardized prevalence in U.S. non-Hispanic black personsc||50||0.08||12,771||50||0.68||1,481|
|6.0%||Prevalence estimated for previous review||50||0.13||7,663||50||1.13||889|
a CVD = cardiovascular disease; NNS = number needed to screen.
b Relative risk reduction, 0.29 over 5 years; rate of blindness in no-treatment group, 1.5% over 5 years. Data on incidence of retinal photocoagulation in 1 eye from the United Kingdom Prospective Diabetes Study.62
c Relative risk reduction of 0.50 over 5 years; 5-year incidence in usual treatment group, 7.5%. Data from the Hypertension Optimal Treatment trial.66
|Prevalence of IGT or IFG||Patient Population||Lifestyle Intervention to Prevent 1 Case of Diabetes (Screening 1000 People with Given Prevalence)b||Metformin to Prevent 1 Case of Diabetes (Screening 1000 People with Given Prevalence)c|
|Increase in Persons Adhering to Intervention, %||Cases of Diabetes Delayed, n||NNS||Increase in Persons Adhering to Intervention, %||Cases of Diabetes Delayed, n||NNS|
|15.0%||IGT only, total U.S. populationd||50||4.79||209||50||2.56||391|
|26.0%||IFG only, total U.S. populatione||50||8.29||121||50||4.43||226|
|40.0%||Estimate IFG and/or IGTf||50||12.76||78||50||6.82||147|
a IFG = impaired fasting glucose; IGT = impaired glucose tolerance; NNS = number needed to screen.
b Relative risk reduction, 58%; 38% achieved weight loss goal of 7% at end of 3-year follow-up (intention-to-treat analysis); control rate, 11%. Data from the Diabetes Prevention Program.36
c Relative risk reduction, 31% with adherence rates (≥ 80% of medications taken); 77% in control group; 72% in intervention group. Data from the Diabetes Prevention Program.36
d Based on National Health and Nutrition Examination Survey, 1994 data.2
e Prevalence data from National Health and Nutrition Examination Survey, 2002 (1): IFG, 5.5-6.93 mmol/L (100-126 mg/dL).
f From National Institute of Diabetes and Digestive and Kidney Diseases, 1994 data (http://diabetes.niddk.nih.gov/dm/pubs/statistics).
|Study, Year (Reference)||Intervention||Sample Size (Diabetes Subgroup/Total), n/n||Baseline Cardiovascular Risk Factors b||Achieved Blood Pressure,mm Hg||Outcome: Relative Risk (95% CI)||Quality Rating||Comment|
|ALLHAT, 200250, 200551, 2001155||Chlorthalidone vs. lisinopril vs. amlodipinec||13,101/31,512||HTN: 100/100
History of CVD: 36%/62%
|Mean SBP (SD) in DM subgroup:
Chlorthalidone: 135.0 (15.6)
Amlodipine: 136.3 (15.9)d
Lisinopril: 137.9 (19.0)d.
Mean SBP (SD) in normoglycemia subgroup:
Chlorthalidone: 133.4 (14.9)
Amlodipine: 133.5 (14.1)
Lisinopril: 134.8 (17.3).
|Fatal CVD or nonfatal MI in the DM subgroup:
Amlodipine-chlorthalidone: 0.97 (0.86-1.10); P = 0.64
Lisinopril-chlorthalidone: 0.97 (0.85-1.10); P = 0.59.
Fatal CVD or nonfatal MI in the normoglycemia subgroup:
Amlodipine-chlorthalidone: 0.94 (0.82-1.07); P = 0.36
Lisinopril-chlorthalidone: 1.02 (0.89-1.16); P = 0.79.
Difference between DM and normoglycemia subgroups: P = NRe
|Fair||Significantly higher rate of attrition in the lisinopril group.|
|CONVINCE, 200352||Verapamil vs. atenolol or HCTZ||3,239/16,476||HTN: 100%
Previous MI: 7.6%
Established vascular disease: 16.7%
|Mean SBP/DBP in total study sample (DM subgroup NR):
Atenolol or HCTZ: 136.6/79.5
|Fatal CVD, stroke, or MI:
DM subgroup: 0.86 (0.66-1.12); P= NR
Normoglycemia subgroup: 1.10 (0.92-1.31); P = NR
Difference between DM and normoglycemia subgroups: P = 0.16e
a ALLHAT = Antihypertensive and Lipid-Lowering Treatment to Prevent Heart Attack Trial; CONVINCE = Controlled Onset Verapamil Investigation of Cardiovascular End Points; CVD = cardiovascular disease; DBP = diastolic blood pressure; DM = diabetes mellitus; HCTZ = hydrochlorothiazide; HTN = hypertension; MI = myocardial infarction; NR = not reported; SBP = systolic blood pressure.
b Data reported as percentages for the DM/non-DM groups in ALLHAT and for the total study sample for the CONVINCE study (data for the DM subgroup alone NR).
c Doxazosin treatment was prematurely discontinued because of an excess of heart failure events.
d P < 0.5 compared with chlorthalidone.
e P value for interaction between DM and normoglycemia subgroups for primary outcome.
|Study, Year (Reference)||Intervention||Sample Size (Diabetes Subgroup/Total), n/n||Baseline Cardiovascular Risk Factorsb||Mean Achieved LDL-C Level (SD), mg/dL||Outcome: Relative Risk (95% CI)||Quality Rating||Comment|
|ALLHAT, 200250||Pravastatin titrated to achieve 25% reduction in LDL-C vs. usual care.||3,635/10,355b||Total group (DM subgroup information NR):
History of CVD: 14.2%
Mean LDL-C: 145.6 mg/dL (SD, 21.4)
|Pravastatin: 104.0 (29.1)
Usual care: 121.2 (34.6)
|All-cause mortality, pravastatin vs. usual carec:
DM subgroup: 1.03 (0.86-1.22); P = NR
Non-DM subgroup: 0.96 (0.84-1.1); P = NR.
CHD death or nonfatal MI:
DM subgroup: 0.89 (0.71-1.10); P = NR
Non-DM: 0.92 (0.76-1.10); P = NR.
Difference between DM and normoglycemia subgroups: P = NRd
|Fair||Relatively small difference in LDL-C between intervention and usual care groups because of withdrawals in intervention group and off-protocol statin use in usual care group.|
|ASCOT, 200355, 200556||Atorvastatin, 10 mg, vs. placebo||2,532/10,305||DM/total group:
Mean LDL-C: 28.7 mg/dL (SD, 27.3)/124.8 mg/dL (SD, 27.3)
Cerebrovascular disease: 7.5%/9.7%
Peripheral vascular disease: 5.3%/5.0%
Mean number of CVD risk factors: 4.1/3.7
|Atorvastatin: 83.9 (26.5)
Placebo: 117.8 (30.4)
|Nonfatal MI or fatal CHDc:
DM subgroup: 0.84 (0.55-1.29); P = NR
Non-DM subgroup: 0.56 (0.41-0.77); P = NR.
Total CVD events and procedures:
DM subgroup: 0.77 (0.61-0.98); P = NR
Non-DM subgroup: 0.80 (0.68-0.94); P = NR.
Difference between DM and normoglycemia subgroups: P = 0.82d
|Fair||Study stopped early; relatively low number of total events in DM subgroup.|
|Heart Protection Study, 200357||Simvastatin, 40 mg, vs. placebo||5,963/20,536||DM/non-DM:
Previous MI: 19%/51%
Other history of CVD: 14%/28%
Blood pressure: 148/82 mm Hg/143/81 mm Hg
Mean LDL-C: 124.8 mg/dL(SD, 32.0)/132.6 mg/dL(SD, 32.0)
|Nonfatal MI or fatal CVDc:
DM subgroup: 0.73 (0.62-0.85); P < 0.001
Non-DM subgroup: 0.73 (0.66-0.81); P < 0.001.
DM subgroup: 0.76 (0.61-0.94); P = 0.01
Non-DM subgroup: 0.74 (0.64-0.86); P < 0.001.
Difference between DM and normoglycemia subgroups: P = 0.10d
|Good (for overall trial)||Baseline characteristics differed significantly between DM and normoglycemic subgroups.|
|PROSPER, 200258||Pravastatin, 40 mg, vs. placebo||623/5,804||Total group (DM subgroup information NR):
Previous angina: 26.9%
Previous MI: 13.4%
Cerebrovascular disease: 11.2%
Vascular disease: 44.2%
Mean LDL-C: 148.2 mg/dL (SD, 31.2)
|Mean LDL at 3 months: pravastatin, 96.7; placebo, 146.6||Nonfatal MI, fatal CVD, nonfatal and fatal strokec:
DM subgroup: 1.27 (0.90-1.80); P = NR
Non-DM subgroup: 0.79 (0.69-0.91); P = NR. Difference between DM and normoglycemia subgroups: P = 0.015d
|Fair||Little diabetes-specific information and relatively few persons with diabetes limit conclusions.|
a To convert LDL-C units to mmol/L, multiply value by 0.0259. ALLHAT = Antihypertensive and Lipid-Lowering Treatment to Prevent Heart Attack Trial; ASCOT = Anglo-Scandinavian Cardiac Outcomes Trial; CHD = coronary heart disease; CVD = cardiovascular disease; DM = diabetes; HTN = hypertension; LDL-C = low-density lipoprotein cholesterol; MI = myocardial infarction; NR = not reported; PROSPER = Prospective Study of Pravastatin in the Elderly at Risk.
b Including persons in the doxazosin group.
c Primary outcome.
d P value for interaction between DM and normoglycemia subgroups for primary outcome.
|Study, Year (Reference)||Country||Quality Rating||Total Sample Size, n||Mean Length of Follow-up||Sample Characteristicsb||Intervention||Outcomes|
|DPP, 2000156,157, 200236, 200574,145||United States||Good||3,234||2.8 y; 3.2 y for CVD outcomes||Age, 51 y (10.7); 32.3% men||Intensive lifestyle vs. metformin vs. placebo||Cumulative incidence of T2DM: metformin, 58% lower (95% CI, 48%-66%); lifestyle, 31% lower (CI, 17%-43%) than placebo.
Cumulative incidence of CVD and CVD event rate: NSD among groups, but underpowered for this outcome.
|DREAM trial, 2004158, 200673,75||International; multicenter||Good||5,269||Median, 3.0 y||Age, 5.7 y (10.9); 40.8% men;
BMI, 30.9 kg/m2 (5.6)
|Rosiglitazone vs. placebo;
ramipril vs. placebo
Death: HR, 0.91 (CI, 0.55-1.49); P = 0.7
T2DM incidence: HR, 0.38 (CI, 0.33- 0.44); P < 0.001
Composite CVD outcome: HR, 0.40 (CI, 0.35-0.46); P = 0.08. Ramipril:
Death: HR, 0.98 (CI, 0.60-1.60)
T2DM incidence: HR, 0.91 (CI, 0.80- 1.03)
Composite CVD outcome: HR, 0.91 (CI, 0.81-1.03); P = 0.68.
|Finnish Diabetes Prevention Study, 1999161, 200176, 2003141, 2003159, 2005160, 200682||Finland||Fair||522||3.2 y for postintervention outcomes; median total follow-up, 7 y||Age, 55 y (7); 32.9% men||Lifestyle vs. usual care||Cumulative incidence of T2DM:
At 3.2 y: HR, 0.4 (CI, 0.3-0.7); P < 0.001
At 7 y: HR, 0.57 (CI, 0.43-0.76); P < 0.001.
|Indian Diabetes Prevention Programme, 200677||India||Fair||531||Median, 2.5 y||Age, 54.9 y (5.7); 79.0% men||Lifestyle and metformin vs. lifestyle vs. metformin vs. placebo||Relative risk reduction in incidence of T2DM at year 3:
Lifestyle: 28.5% (CI, 20.5%-37.3%)
Metformin: 26.4% (CI, 19.1%-35.1%)
Lifestyle and metformin: 28.2% (CI, 20.3%-37.0%).
|Watanabe et al., 200378||Japan||Fair||173||1.0 y||Age, 55.1 y (7.1); 100% men||Dietary counseling vs. usual care||T2DM incidence: NSD between groups (data not provided).|
|Pan et al., 200384||China||Fair||261||16 wk||Age, 54.5 y (8.5); 40.0% men||Acarbose vs. placebo||T2DM incidence: acarbose, 5.6%; placebo, 9.5%; P = 0.245.|
|Kosaka et al., 200538||Japan||Fair||458||4.0 y||Age, NR; 100% men||Lifestyle vs. usual care||Cumulative incidence T2DM over 4 y: lifestyle, 3%; control, 9.3%; P = 0.043 between groups.|
|Heymsfield et al., 200037||International; multicenter||Fair to poor||675||2.0 y||Age, 43.9 y; 17.5% men||Orlistat vs. placebo; both received lifestyle intervention||IGT at baseline and at follow-up:
Normoglycemia: orlistat, 71.6%; placebo, 49.1%
IGT: orlistat, 25.4%; placebo, 43.4%
T2DM: orlistat, 3.0%; placebo, 7.6%
P = 0.04 between groups.
|STOP-NIDDM trial, 1998163, 200272, 2003162||International; multicenter||Fair||1,429||3.3 y||Age, 54.5 y (7.9); 49% men||Acarbose vs. placebo; both received lifestyle intervention||Cumulative incidence of:
T2DM: HR, 0.75 (CI, 0.63-0.90); P = 0.0015
Any CVD event: HR, 0.51 (CI, 0.28-0.95); P = 0.02
MI: HR, 0.09 (CI, 0.01-0.72); P = 0.02.
|Swinburn et al., 200179||New Zealand||Fair to poor||136||5.0 y||Age, 52.2 y (6.5); 50.7% men||Reduced-fat diet vs. usual diet||Intervention was associated with a lower proportion of persons with T2DM or IGT at 1 y (P < 0.05); NSD at 2, 3, or 5 y.
Included population all had IGT at recruitment, but only 31% had prediabetes with repeated testing at randomization; results are for all included patients.
|XENDOS study, 2001 (164), 200483||Sweden||Fair to poor||3305 total (694 with IGT)||4.0 y||Age, 43.8 y (8.0); 44.8% men; BMI, 37.3 kg/m2 (4.3)||Orlistat vs. placebo; both received lifestyle intervention||Cumulative incidence of T2DM in IGT subgroup after 4 y: HR, 0.551; P = 0.0024.|
a BMI = body mass index; CVD = cardiovascular disease; DPP = Diabetes Prevention Program; DREAM = Diabetes Reduction Assessment with Ramipril and Rosiglitazone Medication; HR = hazard ratio; IGT = impaired glucose tolerance; MI = myocardial infarction; NSD = no significant difference; OGTT = oral glucose tolerance test; STOP-NIDDM = Study to Prevent Non-Insulin-Dependent Diabetes Mellitus; T2DM = type 2 diabetes mellitus; XENDOS = Xenical in the Prevention of Diabetes in Obese Subjects.
b Data are reported as means (SDs), unless otherwise noted.