Coronary Artery Calcium Scanning and Patient Adherence

While there are many traditional and novel risk factors for cardiovascular disease (CVD) that have been identified, lifestyle-related factors represent the foundation of most of the major risk factors for CVD.1 Significant advances in the treatment of CVD and the medical management of existing CVD risk factors have substantially reduced cardiovascular mortality over the last thirty years, but important behavioral risk factors, such as poor diet, overeating and physical inactivity have increased over the same time period. Improved management of the behavioral risk factors for CVD is now a national priority because of the role that these factors play in sustaining the high prevalence of CVD in our society, with its consequential effects on CVD mortality, disease morbidity, and the rising costs associated with the care of cardiovascular patients.

In 2010, the American Heart Association (AHA) addressed this need by outlining strategic impact goals designed to improve the cardiovascular health of Americans by 20% by the year 2020.2 In this initiative, the concept of ideal cardiovascular health was proposed, based on optimal levels for the following seven metrics: 1) absence of tobacco use; 2) body mass index <25 kg/m2; 3) regular physical activity (≥150 minutes/week of moderate-intensity physical activity); 4) ideal diet rich in fruits, vegetables, fiber, whole grains, and fish, and low in processed meat, added/refined sugars and sodium; 5) total cholesterol <200 mg/dL; 6) blood pressure <120/80 mm Hg; and 7) fasting blood glucose <100 mg/dL. In 2012, Shay et al. published prevalence estimates of ideal cardiovascular health using National Health and Nutrition Examination Survey (NHANES) data from 2003-2008.3 Overall, <1% of the studied population was classified as having ideal cardiovascular health, and dietary risk, which exceeds smoking as a contributor to death,1 was the most poorly followed lifestyle factor, with >90% having a poor- or intermediate-quality diet.

To date, it has proven to be quite challenging to modify behavioral risk factors in the context of clinical medical practice. As an example, according to a Cochrane Review, unassisted smoking cessation rates range from 2-3% in the general population;4 mere physician advice to quit smoking can increase the success rate another 1-3%. However, when patients sustain cardiovascular events, the chance for obtaining adherence to recommended behavioral changes can increase substantially. For instance, smoking cessation rates increase to 30-50% following an acute myocardial infarction.5 Similarly, while the prevalence of a healthy diet and adequate physical activity are low in the U.S., compliance rates with a heart-healthy diet and recommended levels of physical activity have been reported at 47% and 44%, respectively, following an acute coronary syndrome.6

There are theories that the demonstration of definite disease by virtue of coronary artery calcium (CAC) scanning could also impact patients and motivate them to change by converting "theoretical" future risk of disease (i.e., the discussion of CVD risk factors) to definite, concrete evidence of present disease. To date, a small number of observational studies have examined the influence of CAC scanning on medication use or health behaviors, with follow-up times that ranged from eight months to six years.7-12 In one small study, the presence of CAC was not associated with a greater rate of smoking cessation among 99 smokers followed for 3.5 years.8 However, among five other studies, investigators noted an increased use of statins or aspirin in association with elevated CAC scores,7,9-12 and in some of these studies, an elevated CAC score was associated with an increase in self-reported exercise or self-reported improvement in diet.7,9-11 Overall, however, the assessment of behavioral change has lacked vigor in these studies. For instance, these observational studies did not assess objective measures of behavioral change, such as change in weight, pedometer steps, or exercise fitness.

Randomized Imaging Trials

While prospective randomized trials to assess the impact of cardiac imaging procedures on medication use, health behaviors, and overall medical management are rare, two randomized trials assessed the impact of CAC scanning on such health outcomes. The first study was the Prospective Army Coronary Calcium (PACC) trial, which assessed the impact of CAC scanning on health behaviors among young military recruits with a mean age of 42 years.13 While this was a negative trial, the study was severely limited due to the low prevalence of CAC in this young very low-risk population, with only 15% having any CAC abnormality. The second trial was the Early Identification of Subclinical Atherosclerosis by Noninvasive Imaging Research (EISNER) trial.14 In this trial, 2,137 volunteer subjects with coronary artery disease risk factors were randomized to either a CAC scan at baseline or no CAC scan at baseline in a 2:1 ratio. All subjects received a one-time risk factor counseling session after risk assessment. The subjects were then followed for four years to assess whether the two groups differed in terms of subsequent risk factor profiles, Framingham Risk Score (FRS), downstream test utilization, and incurred medical costs. Overall, the scan group manifested a net favorable improvement in serum low-density lipoprotein, systolic blood pressure, and weight (for those who were overweight at baseline) and had a more favorable change in FRS at four years compared to the group that was randomized to risk factor counseling without CAC scanning. Notably, CAC scanning did not lead to increase in downstream testing compared to the no scan group. However, the EISNER trial does not make it clear whether such testing actually led to improvement in health behaviors. Rather, much of the benefit in the scan group apparently came from a favorable "dose-response" increase in medications with increasing CAC abnormality. This increase could have been principally driven by more aggressive physician management and follow-up rather than increase in patient motivation, per se.

Table 1: Observational Studies Concerning Change in Medication Use and Behaviors With Coronary Calcium Scanning

Author

Population

N

Mean Age

% Male

Heath Behavior

CAC Score > 0 (%)

Outcome

Wong et al. 199612

Self-Referred

703

54

80

Med Adherence; Health Behaviors

56

CAC >0
associated with 1.8-fold increase in ASA; 3.5-fold increase in cholesterol meds; 1.5-fold improvement in dietary habits

O'Malley et al. 20028

Self-Referred Smokers

99

50

68

Smoking

42

No difference in smoking
cessation

Kalia et al. 20069

MD-Referred

505

61

82

Med Adherence; Health Behaviors

NR

9-fold increase in statin adherence in highest vs. lowest CAC quartile

Orakzai et al.  200810

MD-Referred

980

60

78

Health Behaviors

76

2-3-fold increase in ASA use, diet change and exercise in highest vs. lowest CAC quartile

Taylor et al. 200811

U.S. Army Recruits

1,640

43

100

Med Adherence

22

CAC >0 associated with 3-fold increase in statin and ASA use

Schwartz et al.  201113

MD- and Self-Referred

510

64

62

Health Behaviors

58

CAC >0 associated with a 1.5-fold likelihood increasing exercise and changing diet

CAC= coronary artery calcium; Med = medication;
ASA = aspirin; NR= not reported

Future Directions

To date, a preponderance of data suggests that CAC scanning leads to greater medication adherence. This effect may be due both to the impact of CAC scores on physician management and/or upon patient motivation following the determination of increased risk. However, the impact of CAC scanning upon health behaviors requires more vigorous study. Importantly, meta-analytical study has indicated that motivational approaches only account for ~30% of the variance in human behaviors.15 The rest is linked to factors that inhibit patients' ability to maintain goals over time.16 Accordingly, future study is needed to assess the combined impact of CAC scanning that is coupled with techniques designed to enhance the execution and maintenance of health behaviors. Such studies should rely on objective methods to assess change in patients' health behaviors following CAC scanning.

References

  1. US Burden of Disease Collaborators; Murray CJL, Abraham J, Ali MK, et al. The state of US health, 1990-2010: burden of diseases, injuries, and risk factors. JAMA 2013;310:591-608.
  2. Lloyd-Jones DM, Hong Y, Labarthe D, et al. Defining and setting national goals for cardiovascular health promotion and disease reduction: the American Heart Association's strategic impact goal through 2020 and beyond. Circulation 2010;121:586-613.
  3. Shay CM, Ning H, Allen NB, et al. Status of cardiovascular health in US adults: prevalence estimates from the National Health and Nutrition Examination Surveys (NHANES) 2003-2008. Circulation 2012;125:45-56.
  4. Stead LF Bergson G, Lancaster T. Physician advice for smoking cessation. Cochrane Database of Syst Rev 2008 Apr 16;(2):CD000165
  5. Burling TA, Singleton EG, Bigelow GE, Baile WF, Gottlieb SH. Smoking following myocardial infarction: a critical review of the literature. Health Psychol 1984;3:83-96.
  6. Chow CK, Jolly S, Rao-Melacini P, Fox KAA, Anand SS, Yusuf S. Association of diet, exercise, and smoking modification with risk of early cardiovascular events after acute coronary syndromes. Circulation 2010;121:750-758.
  7. Wong ND, Detrano RC, Diamond G, et al. Does coronary artery screening by electron beam computed tomography motivate potentially beneficial lifestyle behaviors? Am J Cardiol 1996;78:1220-3.
  8. O'Malley PG, Rupard EJ, Jones DL, Feuerstein I, Brazaitis M, Taylor AJ. Does the diagnosis of coronary calcification with electron beam computed tomography motivate behavior change in smokers? Mil Med 2002;167:211-4.
  9. Kalia NK, Miller LG, Nasir K, Blumenthal RS, Agarwal N, Budoff M. Visualizing coronary calcium is associated with improvements in adherence to statin therapy. Atherosclerosis 2006;185:394-9.
  10. Orakzai RH, Nasir K, Orakzai SH, et al. Effect of patient visualization of coronary calcium by electron beam computed tomography on changes in beneficial lifestyle behaviors. Am J Cardiol 2008;101:999-1002.
  11. Taylor AJ, Bindeman J, Feuerstein I, et al. Community-based provision of statin and aspirin after the detection of coronary artery calcium within a community-based screening cohort. J Am Coll Cardiol 2008;51:1337-41.
  12. Schwartz J, Allison M, Wright CM. Health behavior modification after electron beam computed tomography and physician consultation. J Behav Med 2011;34:148-55.
  13. O'Malley PG, Feurstein IM, Taylor AJ. Impact of electron beam tomography with and without case management on motivation, behavioral change, and cardiovascular risk profile: a randomized controlled trial. JAMA 2003;289:215-23.
  14. Rozanski A, Gransar H, Shaw LJ, et al. Impact of coronary artery calcium scanning on coronary risk factors and downstream testing: the EISNER (Early Identification of Subclinical Atherosclerosis by Noninvasive Imaging Research) prospective randomized trial. J Am Coll Cardiol 2011;57:1622-32.
  15. Sheeran P. Intention-behavior relations: a conceptual and empirical review. Eur Rev Soc Psychol 2002;12:1-30.
  16. Rozanski A, Gransar H, Hayes SW, et al. Temporal trends in the frequency of inducible myocardial ischemia during cardiac stress testing: 1991-2009. J Am Coll Cardiol 2013;61:1054-65.

Clinical Topics: Acute Coronary Syndromes, Dyslipidemia, Noninvasive Imaging, Prevention, Lipid Metabolism, Nonstatins, Diet, Smoking

Keywords: Actigraphy, Acute Coronary Syndrome, Aspirin, Atherosclerosis, Blood Glucose, Blood Pressure, Body Mass Index, Calcium, Cereals, Cholesterol, Coronary Artery Disease, Counseling, Fasting, Follow-Up Studies, Fruit, Goals, Humans, Hyperphagia, Life Style, Lipoproteins, LDL, Meat, Medication Adherence, Military Personnel, Motivation, Motor Activity, Myocardial Infarction, Nutrition Surveys, Overweight, Prevalence, Prospective Studies, Research Personnel, Risk Assessment, Risk Factors, Self Report, Smoking, Smoking Cessation, Sodium, Vegetables, Virtues, Volunteers, Diagnostic Imaging


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