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Screening subclinical coronary artery disease with noninvasive modalities in patients with diabetes

Zhao, Yanglu; Wong, Nathan D.

Cardiovascular Endocrinology & Metabolism: December 2015 - Volume 4 - Issue 4 - p 120–126
doi: 10.1097/XCE.0000000000000056
Review articles

Diabetes mellitus is a global epidemic crisis as well as a major risk factor for coronary artery disease. Although several well-known noninvasive screening modalities including cardiac computed tomography, echocardiography, and myocardial perfusion imaging have been examined, controversies exist on the prognostic efficacy of these tests. Little is known with regard to the cost–benefit ratios and potential harms of radiation, and no standard screening algorithms have been established. In this review, we discuss the need and criteria for good testing methods and then summarize some of the latest evidence from either randomized or nonrandomized studies to see whether they may possibly strengthen current recommendations and extend the application of these screening methods in related guidelines. We propose, in the future, the development of newer, more sensitive screening modalities to better detect both short-term and long-term cardiovascular risk among asymptomatic patients with diabetes.

Heart Disease Prevention Program, Division of Cardiology, University of California, Irvine, California, USA

All supplementary digital content is available directly from the corresponding author.

Correspondence to Nathan D. Wong, PhD, Heart Disease Prevention Program, C240 Medical Sciences, University of California, Irvine, CA 92697, USA Tel: +1 949 824 5433; fax: +1 949 439 5561; e-mail:

Received January 27, 2015

Accepted May 18, 2015

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Diabetes mellitus (DM) has increased in epidemic proportions: in 2014, 387 million (8.3%) people globally had diabetes 1. Although the prevalence of DM remains high in developed countries, developing countries are catching up at a rapid pace. The primary metabolic change in diabetic patients is hyperglycemia, which induces many other chronic conditions and can lead to an increased risk for cardiovascular disease (CVD). Patients with type 2 DM are at a two- to four-fold higher risk of having a cardiovascular event compared with nondiabetic patients 2. Among all the major cardiovascular complications, the most common and the most fatal one is coronary artery disease (CAD), which accounts for about three out of four deaths among diabetic patients 3. DM patients not only have a higher percentage of overall CAD 4, but CAD can be silent even when advanced and before the coronary event occurs 5, partially because of vascular endothelial dysfunction and an impaired autonomic nervous system 6. However, once CAD clinically manifests, the long-term and short-term outcomes among diabetic patients are often worse than in their nondiabetic counterparts, given their high exposure to other risk factors like hyperinflammation, hyperco-agulability, etc. Therefore, early detection of asymptomatic DM in patients seems intuitively appealing. However, the benefits of systematic screening remain controversial. Because of the lack of supporting evidence and some ambiguity in outcomes with regard to the benefit versus harm of such screening, the current American Diabetes Association does not recommend routine screening for CAD 7. Pros and cons for screening subclinical CAD have been summarized in Table 1. It is proposed in this paper that there is a need for subclinical CAD screening at least in selected patients with DM, if not among all asymptomatic patients with DM.

Table 1

Table 1

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Diabetes: a coronary risk equivalent or not?

Diabetes has been previously accepted as a CAD risk equivalent. It has been observed that diabetic patients have a risk for first-time myocardial infarction (MI) that is comparable to the risk for a recurrent MI among their nondiabetic peers with prior MI events 2, and the concept of a CAD risk equivalent was adopted by the 2003 European CVD prevention guidelines and the 2002 NECP guideline 8,98,9. However, a recent meta-analysis including 13 studies actually shows that those with diabetes have a 43% lower risk for future hard CAD events compared with those with a prior MI, indicating that diabetes is not a CAD equivalent 10. Furthermore, those with diabetes are extremely heterogeneous with regard to the risk for future CVD, especially contrasting male and female individuals. In addition, Wong et al.11 observed that among those with DM in the United States National Health and Nutrition Examination Survey, 32% of men and 48% of women were estimated as being at low to intermediate risk. However, diabetic women have an almost twice as high rate of cardiac death/MI compared with men, indicating the CVD susceptibility of women exposed to elevated glucose levels 12. Thus, it is of great necessity that we discriminate the high-risk subgroup from the low-risk to intermediate-risk ones among those with DM.

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The need for individualized risk assessment and the detection gap of traditional risk factors

With only limited resources for healthcare services, necessary individualized risk assessment based on patient characteristics is important and mandatory. Only after the absolute risk among the DM patients is assessed accurately can the following prevention strategies be efficient and cost-saving. The Framingham and European risk scores emphasize only the classic coronary heart disease risk factors and are only moderately accurate for the prediction of short-term and long-term risk of manifestation of a major coronary artery event 13. Other studies have shown that the effect of other traditional risk factors (dyslipidemia, hypertension, obesity, etc.) may be subsumed by the presence of diabetes, and the number of risk factors did not help identify asymptomatic patients with a higher prevalence of CAD 14. However, risk factors detected by the noninvasive means of screening, such as coronary artery calcium (CAC) levels and myocardial ischemia, could better distinguish patients at low-risk from those at high-risk for future events 15,1615,16.

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Criteria for good screening modalities

According to Pasternak et al.13, a good screening test should have following features: (i) accurately discriminate low-risk and high-risk patients, (ii) produce reliable results, (iii) provide incremental value to the risk predicted by office-based risk assessment, and (iv) detect individuals in whom early intervention is likely to have a beneficial impact. Miller et al.17 also suggested two additional criteria for good screening methods: (i) having a high enough prevalence of the disease in the population such that a meaningful number of affected individuals can be identified and (vi) exhibiting high cost-effectiveness. Although the currently used modalities may not satisfy all the criteria because of a lack of strong evidence, many of them do provide support for these criteria, warranting further investigation.

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Different modalities for detecting early coronary artery disease

Coronary artery calcium computed tomography scanning

The CAC level, which is assessed by multidetector or electron beam computed tomography (CT) technology, is an indicator of subclinical atherosclerosis. CAC CT scanning shows excellent sensitivity for detecting athero-sclerosis when compared with invasive angiography as the gold standard 18. Previous studies have demonstrated that a CAC score of zero has a negative predictive value of 100% in excluding significant CAD 19. CAC CT scanning can better discriminate high-risk and low-risk diabetic patients 15,2015,20. A CAC score of 0 among diabetic patients predicts a mortality profile equal to or less than that of many nondiabetics. DM patients have higher rates of CAD/CVD in each predefined CAC score stratum (CAC=0, CAC=1–100, CAC=101–400, CAC>400) 15. The EISNER Study recruited 2137 volunteers (although not specifically with DM) who were randomly assigned to either the CAC scanning group or the nonscanning group, and the groups were compared for 4-year changes in CVD risk; within the scanning group, an increase in the baseline CAC score was associated with an improvement in risk factors over 4 years including a greater reduction in blood pressure, low-density lipoprotein-cholesterol, and waist circumference in those with increased abdominal girth (P<0.05; although the Framingham risk score remained static in those randomized to CT scanning, it increased in those not undergoing scanning at baseline). Improvements in lifestyle behaviors and increased adherence to preventive medications likely contributed to this 21. Compared with myocardial perfusion imaging (MPI), CAC screening is superior to the use of established cardiovascular risk factors in predicting silent myocardial ischemia and short-term outcomes in patients with uncomplicated type 2 DM 22. In addition, CAC screening is also more cost-effective than MPI. It was estimated that CAC can prevent one event at a cost of $71 249, almost one-third the cost associated with MPI and half the cost associated with a ‘treatment-without-screening strategy’ 23. Preliminary data from a large Korean cohort including 774 patients with diabetes who underwent multidetector CT for CAC screening matched to 1548 controls showed that 5-year all-cause mortality was significantly lower in the multidetector CT group (4.5 vs. 6.8%), perhaps because of greater statin and other medical therapy use, and possibly as a result of revascularization coronary angiography, which was also more common in the screened group, indicating that coronary multidetector CT may play a beneficial role as a screening test to detect advanced macrovascular complications in asymptomatic diabetic patients and in increasing the survival rate 24.

In both the 2010 American Heart Association (AHA) risk assessment guidelines (level IIa) and the 2014 position statement of the Brazilian Diabetes Society (level A), CAC screening is recommended for those at intermediate risk or those with diabetes to reclassify patients into different risk categories 25,2625,26. The 2012 American Association of Clinical Endocrinology Lipid Management Guideline also states that CAC can be used in certain clinical situations to refine risk stratification and the need for aggressive preventive strategies, indicating its preference for a screening test before universal usage of aggressive therapy 27. Most recently, the American College of Cardiology/AHA guideline on the assessment of cardiovascular risk 28 reported that CAC may be used to help stratify risk for the purpose of initiating or intensifying statin or other therapy when the treatment decision based on global risk assessment is uncertain. This may include diabetic patients for whom additional evidence may be required for various reasons before starting or initiating such therapy.

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Echocardiography can be used to detect left ventricular diastolic or systolic dysfunction or increased left ventricular mass or hypertrophy, which can add to risk in patients with diabetes. One investigation involving 234 asymptomatic patients with type 2 DM found that diastolic dysfunction was highly frequent (68%) and was independently related to subclinical CAD measured in terms of CAC scores 29. Dobutamine stress echocardiography has good sensitivity (84%) for the diagnosis of CAD in diabetic patients 30. Stress echocardiography also provides prognostic information. A 13-year follow-up study demonstrated that stress echocardiography was strongly predictive of long-term outcomes 31. Given the modest cost of echocardiography (both regular and stress) and comparable risk predictive efficacy to other stress tests, it should be first considered for evaluation of diabetic cardiomyopathy. In the 2008 appropriate-use criteria for stress echocardiography, it was rated as inappropriate in low-risk and moderate-risk populations (according to the Framingham risk score) and as uncertain in high-risk populations of asymptomatic patients. However, among asymptomatic patients with a high CAC score (≥400), stress echocardiography was rated as appropriate 32.

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Stress myocardial perforation imaging

Prior observational studies have shown high sensitivity (86%) of standard MPI among DM patients, and in high-risk groups, the sensitivity is even higher (94%) 33,3433,34. However, it was found in the Detection of Ischemia in Asymptomatic Diabetics (DIAD) clinical trial that screening DM patients does not improve clinical outcomes 35 even though the participants demonstrate resolution of ischemia upon repeat testing after 3 years 36. Participants in the DIAD trial had a much lower CAD prevalence (22%) compared with those in other population-based studies, and the nonsignificant findings could have been due to the low incidence of coronary events. A Japanese investigation also found that summed stress scores of 9 or higher, measured by gated MPI, were significantly related to future CVD events after adjustment based on 3-year follow-up data 37. In addition, Acampa et al.38 recently found that the net reclassification improvement on adding MPI results to a model including pretest CAD likelihood (calculated from traditional risk factors and stress ECG results) was 0.25 (95% confidence interval 0.06–0.44, P<0.01), concluding that gated MPI influences a patient’s risk with long-term follow-up. Hage et al.39 also found that stress MPI was more sensitive in detecting ischemia than ECG and therefore may be more useful since diabetic patients have a significantly higher prevalence of ischemia than their nondiabetic counterparts. Interestingly, they also found large discrepancy between ischemia detected by MPI and that detected by ECG among female participants.

Although some guidelines (i.e. the 2004 France Society of Cardiology and 2010 AHA risk assessment guidelines) recommended silent myocardial ischemia screening (first stress ECG, otherwise SPECT or echocardiography) for high-risk asymptomatic type 2 DM patients at 2-year intervals if negative results were found 25,3325,33, it is no longer recommended in other guidelines 7,267,26.

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Computed tomography angiography

CTA helps detect obstructive CAD and was found to strongly predict future coronary events in cohort studies 40–4340–4340–4340–43. Both per-patient maximal stenosis and the number of obstructive vessels have prognostic value 41, and CTA can predict short-term and long-term major acute coronary events 42,4342,43. One advantage is that CTA can detect noncalcified plaques, which are very prone to rupture, cause acute coronary syndrome, and are more prevalent among diabetic patients 44,4544,45. However, a recent finding of the FACTOR-64 Randomized Clinical Trial enrolling 900 asymptomatic patients with diabetes is that the use of CTA to screen for CAD does not reduce the risk for all-cause mortality, nonfatal MI, or unstable angina requiring hospitalization; thus, the trial fails to support CTA screening in this population. The negative trial outcome may be related to relatively low event rates caused by either short follow-up time or aggressive preventive measures 46. Another prospective observational study also showed that diabetes was independently related to the false-negative results of CTA 47. Given these potential disadvantages, the harm associated with radiation exposure, and the unknown cost-efficiency of the CTA test, it is not recommended either to the low–intermediate-risk populations or to the high-risk population in most current guidelines 48–5048–5048–50.

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Algorithm of screening

Neither a ‘no-screening’ nor an ‘all-screening’ approach is appropriate for asymptomatic diabetic patients. Rather than a single test, only an appropriate combination of several screening tests can help achieve the goal of accurate detection of CAD (high sensitivity) without overdiagnosis (high specificity). However, different tests need specific indications before being conducted on selected patients, otherwise the related costs may overweigh the potential benefits of cost reduction. Although MPI failed to show outcome differences in the DIAD study, it was useful in classifying patients as high risk (moderate-to-severe abnormalities and ischemia on stress ECG) and low risk (small defects or normal perfusion). Hence, it would still be preferable to test for ischemia more selectively among higher risk diabetic patients rather than among all diabetic patients. Given these needs, an algorithm for screening subclinical DM patients is necessary.

Appropriate use of multimodalities depends on multiple factors: (i) patients with DM, depending on their clinical history and other risk factors, should be preassessed and selected for different modalities; (ii) If one method is not enough to detect the future risk, is the incremental value of a second and third screening method significant enough to address the residual risk?; (iii) What is the right order to conduct various tests? Some data showed that CAC scores accurately reflect the possibility of abnormal MPI findings, suggesting a role for CAC scoring as a gatekeeper for patients who may benefit from further risk stratification with stress MPI. For example, Wong et al.51 showed the prevalence of abnormal MPI to be very low in individuals with metabolic syndrome or diabetes, until the CAC score was 100 or higher, suggesting this to be a reasonable cutoff point for CAC burden at which further evaluation with MPI might provide an adequate yield of positive tests. In addition, CAC screening and MPI provided complementary evidence of risk assessment by nature, as CAC is usually an indicator of anatomic CAD, whereas MPI reflects pathophysiological change of CAD. Several studies have demonstrated that patients with apparently anatomically significant CAD do not always present consistently severe stress-inducible ischemia 52–5452–5452–54. Several algorithms have been proposed: Bax et al.55 first developed an algorithm for MPI and suggested performing MPI in all moderate-risk and high-risk DM populations (Fig. 1a). Scholte et al.56, Yerramasu et al.57, and Peix 58 separately proposed more detailed algorithms recommending CAC scanning before MPI, and MPI only in those with CAC scores greater than 100 or with risk factors (Fig. 1b–d). The three proposed algorithms have the following consensus: first, the prevention strategy corresponding to risk stratification is consistent; second, screening methods are used as part of the risk evaluation loop to help in the reclassification of patients; third, MPI screening usually requires repeat testing after 2 years. The 2010 AHA guidelines stated that stress MPI may be considered for advanced cardiovascular risk assessment in asymptomatic adults with diabetes or with otherwise high risk, for example, with a CAC score of 400 or higher (class IIb–C) 25.

Fig. 1

Fig. 1

Figure 2

Figure 2

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Future of screening methods

Individuals with diabetes have high mortality because of CVD, yet many of them are still suboptimally treated for CVD risk factors 59. Besides, the heterogeneity in CVD risk among individuals with DM calls for individualized risk assessment before further tailored management is implemented. Although current screening methods have been demonstrated to be effective in predicting future coronary events, the following points need to be addressed: (i) only a few studies have been conducted on the cost-effectiveness of various scanning modalities. Acampa et al.60 calculated the cost per net reclassification index change of MPI scanning to be $880.80, but they did not specify whether this number was cost-saving or not. A promising outcome may promote the utility of screening in a wider variety of patient groups if covered by insurance. (ii) Large randomized clinical trials should be designed to directly look into the impact of screening tests on clinical outcomes, as well as the impact on downstream clinical decisions, risk factor changes, and total savings. (iii) Seldom have screening methods been directly compared for predictive efficacy using the hazard ratio from Cox regression, the C-statistic, numbers need-ed to treat, or the net reclassification index in models; this evidence will be the most powerful for demonstrating screening preference in DM patients. In the future, many more novel screening methods will be investigated and may provide better solutions to the problem of CVD risk assessment in patients with diabetes.

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Conflicts of interest

Dr Wong is a consultant for Re-Engineering Healthcare. Dr. Zhao has no conflict of interest.

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asymptomatic diabetes; coronary artery disease; noninvasive imaging

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