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J Am Coll Cardiol, 2007; 49:378-402, doi:10.1016/j.jacc.2006.10.001
(Published online 12 January 2007). © 2007 by the American College of Cardiology Foundation |
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Table of contents |
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Introduction......380
Consensus Statement Method......380
Introduction to CAC Measurement......381
Role of Risk Assessment in Cardiovascular Medicine......381
Matching Intensity of Intervention With Severity of Risk......382
Current Approaches to Global Risk Assessment and to Assessment of Incremental Risk Using New Tests......382
Risk Assessment for Coronary Heart Disease in Asymptomatic Populations......383
Prognosis by Coronary Artery Calcium Measurements......383
Theoretical Relationship Between Coronary Calcification and CHD Events......383
Approaches to Technology Assessment in CHD Screening......383
Systematic Reviews and Meta-Analyses......383
Data Quality Issues......384
Inclusion Criteria and Endpoint Definitions for the Present Analysis......384
Prognostic Value of CAC Scores From Published Reports From 2003–2005......385
Independent Prognostic Value of CAC Scores Over Cardiac Risk Factors......386
Predictive Accuracy in Patients With an Intermediate FRS......387
Future Research Needs......387
Summary......387
Role of CAC Scoring in Assessment of Symptomatic Patients......388
Diagnosis of Coronary Stenosis in Patients With Possible CHD by CAC......388
Comparison With Other Tests for CHD Diagnosis......389
Exercise ECG Test......389
Myocardial Perfusion Imaging and Stress Echocardiography......390
Other Uses of CAC Measurement in Symptomatic Persons......390
Summary......391
Use of Coronary CT for Assessment of Progression or Regression of Coronary Atherosclerosis......391
Biologic Relevance of Coronary Atherosclerosis Progression......391
Accuracy of Serial Coronary Calcium Assessments......391
Prognostic Relevance of CAC Score Changes......391
Modification of CAC Progression......392
Summary and Implications......392
Cost-Effectiveness of Coronary Calcium Scoring for Risk Assessment of Cardiac Death or MI......392
Summary and Conclusion......393
Special Considerations......393
CAC Scores and Gender......393
Epidemiology......393
Risk Assessment......393
Summary......393
Ethnicity......393
Chronic Kidney Disease (CKD) and End-Stage Renal Disease (ESRD)......395
Diabetes......395
Incidental Findings in Patients Undergoing CAC Testing......395
Summary and Final Conclusions......396
References......397
Appendix 1......400
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Preamble |
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The Task Force on Clinical Expert Consensus Documents makes every effort to avoid any actual or potential conflicts of interest that might arise as a result of an outside relationship or personal interest of a member of the writing panel. Specifically, all members of the writing panel are asked to provide disclosure statements of all such relationships that might be perceived as real or potential conflicts of interest to inform the writing effort. These statements are reviewed by the parent task force, reported orally to all members of the writing panel at the first meeting, and updated as changes occur. The relationships with industry information for writing committee members and peer reviewers are published in the appendices of the document.
Robert A. Harrington, MD, FACC, Chair, ACCF Task Force on Clinical Expert Consensus Documents
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Introduction |
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Consensus Statement Method |
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At its first meeting, each member of this ACCF/AHA Writing Committee indicated any relationship with industry. Relevant conflicts of the Writing Committee and peer reviewers are reported in Appendixes 1 and 2, respectively. The next step in the development of this document was to obtain a complete literature review from the Griffith Resource Library at the ACC concerning CAC measurement by fast CT methods from 1998 through early 2005 (National Library of Medicine’s Elhill System). Additional relevant prior or subsequently published references have also been identified by personal contacts of the Writing Committee members, and substantial efforts were made to identify all relevant manuscripts that were currently in press. At the first meeting, members of the Writing Committee were given assignments to provide descriptions and analyses of CAC measurement for identifying and modifying coronary event risk in the asymptomatic patient, for modifying the clinical care and outcomes of symptomatic patients suspected of having coronary artery disease (CAD), and for understanding the role of CAC measurement in selected patient subgroups. Each individual contributor to these parts of the document had his or her initial full written presentation critiqued by all other members of this Writing Committee. Outside peer review was also undertaken before the document was finalized.
Considerable discussion among the group focused on the best and most proper way to assess clinical appropriateness of tests such as CAC measurement since there have been no clinical trials to evaluate the impact of CAC testing on clinical outcomes in either symptomatic or asymptomatic patients. The Writing Committee agreed uniformly that the ideal assessment of cardiac tests would require clinical trials that utilize important patient outcomes such as improving the quality or quantity of a patient’s life. However, recognizing that this standard is not available for CAC measurement, the Committee considered other standards of evidence in reaching a consensus opinion. A minority of the Writing Committee felt that CAC testing could not be advised for any clinical indication until clinical trials were available to show benefit on actual patient outcomes. However, the majority of the Writing Committee felt that this standard of evidence is rarely applied in assessment of cardiac testing appropriateness. Therefore, the majority position presented here reflects the concept that prognostic testing such as CAC measurement can be considered reasonable where there is evidence that the test results can have a meaningful impact on medical decision-making.
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Introduction to CAC Measurement |
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Electron-beam computed tomography (EBCT) and multi-detector computed tomography (MDCT) are the primary fast CT methods for CAC measurement at this time. Both technologies employ thin slice CT imaging, using fast scan speeds to reduce motion artifact. Thirty to 40 adjacent axial scans usually are obtained. A calcium scoring system has been devised based on the X-ray attenuation coefficient, or CT number measured in Hounsfield units, and the area of calcium deposits (12). A fast CT study for coronary artery calcium measurement is completed within 10 to 15 min, requiring only a few seconds of scanning time.
Cardiac computed tomography has been used with increasing frequency in the United States and other countries during the past 15 years, initially with the goal of identifying patients at risk of having obstructive coronary artery disease based on the amount of coronary calcium present. However, in the past 5 to 10 years, fast CT methods have been used primarily for 2 purposes: 1) to assist in coronary heart disease (CHD) risk assessment in asymptomatic patients, and 2) to assess the likelihood of the presence of CHD in patients who present with atypical symptoms which could be consistent with myocardial ischemia.
Many technical aspects are relevant to the choice of EBCT versus MDCT, and these are beyond the scope of this document. A related document, recently prepared by the AHA, addresses these important technical issues (2). In contrast, this document focuses on clinical uses of fast CT for CAC measurement and addresses the appropriateness of CAC measurement in defined clinical circumstances.
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Role of Risk Assessment in Cardiovascular Medicine |
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Risk assessment is often regarded as a key first step in the clinical management of cardiovascular risk factors. Risk assessment algorithms, such as those from the Framingham Heart Study in the United States or from the Prospective Cardiovascular Münster (PROCAM) study in Germany, or the European risk prediction system called SCORE (Systemic Coronary Risk Evaluation), are among the most common and widely available for estimating multi-factorial absolute risk in clinical practice (13). Each of these risk assessment algorithms, as most often used, projects 10-year, absolute risk, which can be considered short-term or intermediate-term (not lifetime) risk. These risk projections are often regarded by policy makers and clinicians as useful when selecting the most appropriate candidates for drug therapies intended to reduce risk. Cholesterol and blood pressure guidelines in the United States and elsewhere have followed the principle that the intensity of treatment should be aligned with the severity of a patient’s risk (14,15). The rationale behind this balance between treatment intensity and patient risk is that proportional risk reduction and cost-effectiveness analyses indicate that there is greater benefit of drug exposure when the patient’s risk is high. It has been considered useful to divide patients into several categories depending on their 10-year risk estimates. Three commonly used categories are high risk, intermediate risk, and low risk. Beginning in 2004, the National Cholesterol Education Program (NCEP) further divided the intermediate-risk category into moderately high risk and moderate risk (16). Table 1 shows the most recent NCEP categories of 10-year absolute risk used to stratify patients for cholesterol-lowering therapy. This classification can be applied to other CHD risk reduction therapies as well, such as blood pressure lowering.
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Current Approaches to Global Risk Assessment and to Assessment of Incremental Risk Using New Tests. In current clinical practice, in accordance with a number of guidelines (14,15), it is common that the first step in clinical risk assessment is to identify any high-risk conditions that obviate the need for further risk assessment; these mainly include established atherosclerotic cardiovascular disease (ASCVD) and diabetes (see Table 1, High risk). If none of these high-risk conditions is present, the second step is to identify the presence of major risk factors (also listed in Table 1). If 2 or more major risk factors are present, one should then estimate the 10-year likelihood for development of major coronary events or total cardiovascular events. In the United States, the most-commonly used and most extensively validated quantitative assessment is provided by the multivariable scoring system of the Framingham Heart Study. The Framingham algorithm for "hard CHD" events including myocardial infarction and cardiac death is available through the National Cholesterol Education Program website (http://hin.nhlbi.nih.gov/atpiii/calculator.asp). Framingham scoring includes the following major risk factors: gender, total cholesterol, high-density lipoprotein (HDL) cholesterol, systolic blood pressure (or on treatment for hypertension), cigarette smoking, and age. PROCAM scoring employs a somewhat different set of risk factors: gender, age, low-density lipoprotein (LDL) cholesterol, HDL cholesterol, triglycerides, systolic blood pressure, cigarette smoking, family history, and presence or absence of diabetes (http://www.chd-taskforce.com/). The European SCORE algorithm uses risk factors similar to the Framingham Score.
For each of these risk assessment tools, the most powerful risk factors are age and gender. The other risk factors can be examined for their additive predictive power by determining increments in the area under the curve of the receiver-operating characteristic (ROC). The area under the ROC curve is also known as the C-statistic. An ROC analysis plots sensitivity (fraction of true positives) versus 1-specificity (fraction of false positives) of a risk factor for predicting events. ROC curves are used to evaluate the discrimination of a prediction, and often, the predictive power of a set of risk factors. If a given set of risk factors predicted the development of cardiovascular events perfectly, the curve would reach 100% in the upper left corner (100% sensitivity and 100% specificity), that is, all true positives and no false positives. The area under the curve would be 100% (C-statistic = 1.0). A random and useless predictor would give a straight line at 45 degrees (C-statistic = 0.5) since this would define a test where true positive rate and false positive rate are equal to one another at every possible cutoff value. In the evaluation of additional tests, added to the basic set of Framingham risk factors, the area under the curve would increase when the test provides incremental discrimination. The Framingham algorithm applied to the Framingham population generally gives a C-statistic of approximately 0.8, meaning that the probability is 80% that patients who experience CHD events will have a higher risk score than patients who did not experience an event. An important but unresolved issue is whether discovery and addition of new biochemical risk factors or imaging markers to Framingham or PROCAM algorithms will increase the C-statistic. In considering the role of CAC measurement for risk assessment, a key issue is whether discriminative ability is improved, often as judged by an increase in the C-statistic compared to that derived from risk factors alone.
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Risk Assessment for Coronary Heart Disease in Asymptomatic Populations |
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In the past several years, however, a number of publications have reported on the incremental prognostic value of CAC in large series of patients including asymptomatic self-referred and population cohorts (18–22). A major rationale for the current document is the need for an update including recent publications regarding CAC as it relates to the estimation of CHD death or nonfatal myocardial infarction (MI). Although earlier evidence included the use of "soft" endpoints including coronary revascularization as a primary outcome, more recent data are available on the estimation of CHD death or MI (18–22). Models predicting "hard" cardiac events (i.e., CHD death or MI) are less subjective and less likely to overestimate the predictive accuracy of CAC scoring (23).
Theoretical Relationship Between Coronary Calcification and CHD Events. Atherosclerotic plaque proceeds through progressive stages where instability and rupture can be followed by calcification, perhaps to provide stability to an unstable lesion (8). As the occurrence of calcification reflects an advanced stage of plaque development, some researchers have proposed that the correlation between coronary calcification and acute coronary events may be suboptimal based largely on angiographic series (11). In order to understand this apparent conflict between the stability of a calcified lesion and CHD event rates, one must recognize the association between atherosclerotic plaque extent and more frequent calcified and non-calcified plaque (24). That is, patients who have calcified plaque are also more likely to have non-calcified or "soft" plaque that is prone to rupture and acute coronary thrombosis (24). It is the co-occurrence of calcified and non-calcified plaque that provides the means for estimating acute coronary events. Furthermore, although CAC detection cannot localize a stenotic lesion or one that is prone to rupture, CAC scoring may be able to globally define a patient’s CHD event risk by virtue of its strong association with total coronary atherosclerotic disease burden, as shown by correlation with pathologic specimens (1,24).
Approaches to Technology Assessment in CHD Screening. A major criterion utilized in many technology assessments has been that a screening test must have a high level of evidence on the effect of screening on actual health outcomes, such as fewer events, extended life, or better quality of life. This type of analysis requires research detailing an improvement in either quantity or quality-of-life years as a result of the screening procedure. An example of a high level of such evidence was recently published on screening for abdominal aortic aneurysm (AAA) (25). Using this example, a meta-analysis reported reduced mortality in randomized trials of AAA screening. These results allowed for favorable support of AAA screening by the USPSTF resulting in a class B recommendation (i.e., evidence includes consistent results from well-designed, well-conducted studies in representative populations that directly assess effects on health outcomes) (26). Lack of similar controlled clinical trial evidence played a central role in the conclusion by the USPSTF not to support CHD screening using CAC measurement (see http://www.ahrq.gov/downloads/pub/prevent/pdfser/chdser.pdf).
Although no studies have shown a net effect on health outcomes of CAC scoring (27), at least one randomized trial is nearing completion (Early Identification of Subclinical Atherosclerosis using NoninvasivE Imaging Research [EISNER]). However, the concept of matching treatment intensity to the degree of cardiovascular risk suggests that efforts to identify the most accurate approach to risk stratification is an initial and critical step that should aid in the best selection of treatment options for patients at risk for cardiovascular disease.
Systematic Reviews and Meta-Analyses. In the sections that follow, we review recent evidence on the prognostic value of CAC and include data from one recent systematic review. A comprehensive data synthesis on this subject was published by Pletcher et al. (23) evaluating the prognostic value of CAC from 4 studies published through 2002 meeting quality-based inclusion criteria. Articles were considered for that meta-analysis if they evaluated the prognostic value of CAC in asymptomatic individuals and also presented data on CHD events. Based on a random-effects model, the summary relative risk ratios were 2.1 (for CAC score of 1 to 100) and as high as 10 (for CAC greater than 400) as compared to patients with a score of 0 (p less than 0.0001). This meta-analysis (23) offers support for the concept that there is a linear relationship between CAC and CHD events, but the analysis did not address whether CAC measurement is incremental to Framingham Risk Score (FRS) for CHD risk prediction.
Data Quality Issues. A lack of rigor in study methodology was a focus of the 2000 ACC document (1). A detailed review of the quality of the published data on the prognostic value of CAC was also published by Pletcher et al. (23) noting significant heterogeneity in study quality with often a lack of blinded outcome adjudication, greater use of categorical or historical risk factors, and variable tomographic slice thickness (3 vs. 6 mm) contributing to an overestimation of the relative risk of events by CAC measurements. For example, the relative risk ratio was significantly higher for CAC of 101 to 400 (p = 0.01) and greater than 400 (p = 0.004) when self-reported or historical risk factors were employed in a predictive model as compared with measured risk factor data. The clinical implication of this distinction is that physicians interpreting these results may overvalue CAC scores as substantially more predictive than traditional risk factors.
Evaluation of more recent publications indicates that some of the important methodological limitations of earlier reports have been addressed. Notably, more recent publications report the independent prognostic value of CAC in multivariable models including measured risk factor data (18,19,22). Larger sample sizes have also resulted in improved precision in risk prediction models. However, issues of selection or referral bias when using patient cohorts remain pertinent and are likely to have resulted in an overestimation of risk when based on clinical cohorts as compared with population samples (20,22). It is important to recognize that relative risk ratios from patient cohorts have generally been higher than from studies conducted in population samples even when the overall direction of the prognostic findings has been concordant.
Inclusion Criteria and Endpoint Definitions for the Present Analysis. The current document focuses on the ability of CAC scoring to estimate CHD death or MI. This approach allows for a comparison of the expected annual event rates based on the FRS. The FRS estimates that annual rates of CHD death or MI are less than 1.0% for low risk, 1.0% to 2.0% for intermediate risk (Table 1), and greater than 2.0% for high risk. When multiple publications have been reported from the same cohort study (1,4,5,33–36), we employ here only the most recent report in the current analysis (19,20).
The inclusion criteria for this analysis are: 1) data not previously reported in the 2000 document (1); 2) published series on the prognostic value of CAC in asymptomatic cohorts reported since 2002; 3) endpoint data must be reported on the outcome of CHD death or MI over a specified follow-up time period (usually within 3 to 5 years); and 4) data extraction must allow for the calculation of univariable relative risk ratios and must also include risk-adjustment for traditional cardiac risk factors (e.g., age, gender, cholesterol, hypertension, etc.) or the FRS.
Two committee members (AJT, LJS) evaluated the quality of each included report with the results of this analysis being included in Table 2. The quality assessment criteria included: 1) documentation of prospective data collection; 2) inclusion of self-referred patient series or from a population sample; 3) reporting of CHD events; 4) reporting of outcome data by gender and ethnicity; 5) sample size greater than 1000 individuals; 6) avoiding potential for limited challenge (i.e., an inclusion of very low to very high-risk patients resulting in a wide spread in the outcome results) by not reporting data within strata of clinical risk; 7) reporting measured versus historical or self-reported risk factor data; and 8) reporting univariable and multivariable prognostic models (i.e., ascertaining the incremental value of CAC scores). A review of the highlighted reports reveals that all studies identified for inclusion were of at least moderate-high quality.
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Using a random-effects model, an analytical approach frequently applied to observational data such as that reported in the CAC series, Figure 1 reports on the univariable and summary (weighted average) relative risk ratios from 6 recently published reports in 27 622 patients (n = 395 CHD death or MI). This figure reports the summary relative risk ratio of 4.3 (95% confidence interval [CI] = 3.5 to 5.2) for any measurable calcium as compared with a low-risk CAC (generally using a score of 0) (p less than 0.0001). These data imply that the 3 to 5 year risk of any detectable calcium elevates a patient’s CHD risk of events by nearly 4-fold (p less than 0.0001). Importantly, patients without detectable calcium (or a CAC score = 0) have a very low rate of CHD death or MI (0.4%) over 3 to 5 years of observation (n = 49 events/11 815 individuals).
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The summary relative risk ratios in Figure 2 reveal an incremental relationship where higher CAC scores are associated with higher event rates and higher relative risk ratios. In this figure, a mild risk CAC score (with scores ranging from 1 to 112) was associated with an elevation in CHD death or MI risk with a summary relative risk ratio of 1.9 (95% CI = 1.3 to 2.8, p = 0.001). This mild risk grouping was more often reported in younger populations undergoing preventive health screenings (18,28).
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Independent Prognostic Value of CAC Scores Over Cardiac Risk Factors. A necessary criterion for establishing a high degree of predictive accuracy for CAC measurements is the establishment of the independent contribution of CAC above and beyond risk factor data alone (29). Recent reports have included univariable and multivariable models that have evaluated the independent contribution of CAC in models evaluating risk factors or the FRS (Table 3). From the St. Francis Heart Study, measured risk factor data were available in 1293 of the total enrolled cohort of 4903 asymptomatic individuals. In univariable (p less than 0.0001) and multivariable (p = 0.01) models estimating CHD events at 4.3 years of follow-up, CAC scores were independently predictive of CHD outcome above and beyond both historical and measured risk factors (19). The CAC scores were also predictive of outcome in a multivariable model containing high-sensitivity C-reactive protein (18), similar to a previous report by Park et al. (30). Several reports have also evaluated the independent prognostic contribution of CAC in multivariable models that controlled for other cardiovascular risk markers, including risk factors not in the FRS, such as a family history of premature CHD (18,22) or body mass index (22) (Table 4).
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In addition, the recent data provide support for the concept that use of CAC testing is most useful in terms of incremental prognostic value for populations with an intermediate FRS (29). In a secondary analysis of patients with an intermediate FRS from 4 reports (19,20,22,28), annual CHD death or MI rates were 0.4%, 1.3%, and 2.4% for each tertile of CAC score where scores ranged from less than 100, 100 to 399, and greater than or equal to 400, respectively (19,20) (Fig. 3). From this analysis, intermediate-risk FRS patients with a CAC score greater than or equal to 400 (Fig. 3) would be expected to have event rates that place them in the CHD risk equivalent status (event rate greater than or equal to 20% over 10 years (31).
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Summary. Since 2000, when the last ACC CECD report on CAC measurement was published, there has been growing evidence on the use of CAC in better-studied cohorts of patients and asymptomatic individuals. CAC scoring has an increasingly high level of quality evidence on its role in risk stratification of asymptomatic patients. Recent evidence is supportive that measurement of CAC is predictive of CHD death or MI at 3 to 5 years. Current evidence also suggests that the use of CAC is independently predictive of outcome over and above traditional cardiac risk factors. Published reports have largely been derived from patient cohorts where referral bias is operational resulting in an overestimation of CHD death or MI risk estimates. Upcoming data from the MESA study may be helpful to devise population screening strategies for women and in non-whites. The MESA data will also be useful in validating predictive capability by ethnicity and across a broad age range of asymptomatic people. Data employing direct comparisons of CAC measurement versus other imaging modalities or biomarkers are generally not available.
The consensus of the Committee was that the body of evidence is supportive of recommendations from the USPSTF that unselected screening is of limited clinical value in patients who are at low risk for CHD events, typically estimated using a low FRS less than 1.0% per year (see http://www.ahrq.gov/downloads/pub/prevent/pdfser/chdser.pdf).
A subset analysis of the predictive accuracy of CAC in patients with an intermediate FRS reveals that for a score greater than or equal to 400, the patient’s 10-year CHD risk would achieve risk equivalent status similar to that noted with diabetes or peripheral arterial disease (31). Thus, clinical decision-making could potentially be altered by CAC measurement in patients initially judged to be at intermediate risk (10% to 20% in 10 years).
The accumulating evidence suggests that asymptomatic individuals with an intermediate FRS may be reasonable candidates for CHD testing using CAC as a potential means of modifying risk prediction and altering therapy. On the other hand, there is little to be gained by testing with CAC in patients with a low FRS. Furthermore, patients with a high FRS should be treated aggressively consistent with secondary prevention goals based upon the current NCEP III guidelines and thus should not require additional testing, including CAC scoring, to establish this risk evaluation (31). Additionally, the current CAC literature does not provide support for the concept that high-risk asymptomatic individuals can be safely excluded from medical therapy for CHD even if CAC score is 0.
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Role of CAC Scoring in Assessment of Symptomatic Patients |
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In the symptomatic patient, CAC has been evaluated as a noninvasive diagnostic technique for detecting obstructive CAD. To define its test characteristics and to compare it with other noninvasive tests, a meta-analysis was performed and published in the previous ACC/AHA consensus statement (1). In the previous meta-analysis, a total of 3683 patients were considered among 16 studies evaluating the diagnostic accuracy of CAC measurement (1). Inclusion criteria were: diagnostic catheterization for patients without prior history of coronary disease or prior cardiac transplantation. Patients were symptomatic and referred to the cardiac catheterization laboratory for diagnosis of obstructive CAD. On average, significant coronary disease (greater than 50% or greater than 70% stenosis by coronary angiography) was reported in 57.2% of the patients. Presence of CAC was reported on average in 65.8% of patients (defined as a score greater than 0 in all but one report). The weighted-average or summary odds were elevated 20-fold with a positive CAC (score greater than 0) (95% CI 4.6 to 87.8). Additional summary odds ratios were also calculated with various anatomic and calcium score cut points. For detection of minimal, greater than 50%, and greater than 70% stenosis at cardiac catheterization, the summary odds increased from 6.8-fold (95% CI 3.0 to 15.6) to 16.4-fold (95% CI 5.1 to 53.1) to 50-fold (95% CI 24.1 to 103.0); that is, the odds of significant coronary disease increased when greater angiographic lesion thresholds were used for significant disease (although the confidence bounds widened). Higher coronary calcium scores increased the likelihood of detecting significant coronary disease (greater than 50% or greater than 70% luminal stenosis). A threshold of detectable calcium or a score greater than 5 was associated with an odds of significant disease of 25.6-fold (95% CI 9.6 to 68.4).
Schmermund et al. (36) examined 291 patients with suspected CHD who underwent risk factor determination as defined by the NCEP, CAC measurement, and clinically indicated coronary angiography. A simple noninvasive index (NI) was constructed as the following: log(e)(LAD score) + log(e)(LCx score) + 2[if diabetic] + 3[if male]. Receiver-operating characteristic curve analysis for this NI yielded an area under the curve of 0.88 ± 0.03 (p less than 0.0001) for separating patients with, versus without, angiographic 3-vessel and/or left main CAD. Various NI cutpoints demonstrated sensitivities from 87% to 97% and specificities from 46% to 74%. Guerci et al. (37) studied 290 men and women undergoing coronary arteriography for clinical indications. A coronary calcium score greater than 80 (Agatston method) was associated with an increased likelihood of any coronary disease regardless of the number of risk factors, and a coronary calcium score greater than or equal to 170 was associated with an increased likelihood of obstructive coronary disease regardless of the number of risk factors (p less than 0.001). Kennedy et al. (35) studied 368 symptomatic patients undergoing cardiac catheterization. By multivariate analysis, only male sex and coronary calcification were significantly related to extent of angiographic disease. Receiver-operating characteristic curve analysis showed that the amount of coronary calcium was a significantly better discriminator of disease than were the standard risk factors. In all three studies, CAC scoring improved diagnostic discrimination over conventional risk factors in the identification of persons with angiographic coronary disease.
More recently, large multi-center studies have been reported using fast CT for diagnosis of obstructive CAD in symptomatic persons (n = 1851), who underwent coronary angiography for clinical indications. Study prediction models were designed to be continuous, adjusted for age and sex, corrected for verification bias, and independently validated in terms of their incremental diagnostic accuracy. The overall sensitivity was 95%, and specificity was 66% for coronary calcium score to predict obstructive disease on invasive angiography. The logistic regression model exhibited excellent discrimination (receiver operating characteristic curve area of 0.84 ± 0.02) and calibration (chi-square goodness of fit of 8.95, p = 0.44) (38). Increasing the cut-point for calcification markedly improved the specificity, but decreased the sensitivity. In the same study, increasing the CAC cutpoint to greater than 80 decreased the sensitivity to 79% while increasing the specificity to 72%. In another large study (n = 1764) comparing CAC to angiographic coronary obstructive disease, use of a CAC score greater than 100 resulted in a sensitivity of 95% and a specificity of 79% for the detection of significant obstructive disease by angiography (39). Summing these 2 large studies (n = 3615) leads to an estimated sensitivity of 85%, with a specificity of 75%. There is some concern, due to study design, that these studies (similar to validation of many non-invasive cardiovascular tests) are subject to verification bias, which could raise the sensitivity and lower the specificity. A large study, evaluating consecutive symptomatic persons undergoing cardiac catheterization, addresses this concern. 2115 consecutive symptomatic patients (n = 1404 men; mean age = 62, SD ± 19 years old) with no prior diagnosis of CAD were included in this study. These patients were being referred to the cardiac catheterization laboratory for diagnosis of possible obstructive coronary artery disease, without knowledge of the CAC scan results. The scan result did not influence the decision to perform angiography. Overall sensitivity was 99%, and specificity was 28% for the presence of any coronary calcium being predictive of obstructive angiographic disease. With volume calcium score greater than 100, the sensitivity to predict significant stenoses on angiography decreased to 87% and the specificity increased to 79% (40).
Comparison With Other Tests for CHD Diagnosis
It is appropriate to compare CAC scoring by fast CT with the older more mature diagnostic modalities. The equipment and personnel for performing stress electrocardiography, myocardial perfusion imaging, and echocardiography are readily available. The electrocardiographic (ECG) exercise test, like the echocardiogram, can be performed in the doctor’s office and does not require exposure to radiation.
Exercise ECG Test
Gianrossi et al. (41) investigated the reported diagnostic accuracy of the exercise ECG for CAD obstructive disease in a meta-analysis. One hundred forty-seven consecutively published reports involving 24 074 patients who underwent both coronary angiography and exercise testing were summarized. Wide variability in sensitivity and specificity was found (mean sensitivity was 68%, with a range of 23% to 100% and a standard deviation of 16%; mean specificity was 77%, with a range of 17% to 100% and a standard deviation of 17%).
Myocardial Perfusion Imaging and Stress Echocardiography
Fleischmann et al. (42) reviewed the contemporary literature to compare the diagnostic performance of exercise echocardiography and exercise nuclear perfusion scanning in the diagnosis of CAD. Forty-four articles (not unique patient data sets) met inclusion criteria: 24 reported exercise echocardiography results in 2637 patients with a weighted mean age of 59 years, of whom 69% were men, 66% had angiographic coronary disease, and 20% had prior myocardial infarction; and 27 reported exercise SPECT in 3237 patients, of whom 70% were men, 78% had angiographic coronary disease, and 33% had prior myocardial infarction. In pooled data weighted by the sample size of each study, exercise echocardiography had a sensitivity of 85% (95% CI 83% to 87%) with a specificity of 77% (95% CI 74% to 80%). Exercise perfusion yielded a similar sensitivity of 87% (95% CI 86% to 88%) but a lower specificity of 64% (95% CI 60% to 68%) (42).
There are more recent direct comparison studies available in patients who underwent both CAC measurements, as well as either exercise electrocardiography and/or nuclear imaging, with results compared to cardiac catheterization. Shavelle et al. (43) reported 97 patients who underwent technetium stress testing (technetium-stress), treadmill-ECG, and fast CT coronary scanning within 3 months of invasive coronary angiography for the evaluation of chest pain. The relative risk of obstructive angiographic CAD for an abnormal test was higher for fast CT CAC scores (4.53) than either treadmill-ECG (1.72) or technetium-stress (1.96). The accuracy of fast CT was significantly higher (80%) than either treadmill testing (71%) or technetium-stress (74%) in the diagnosis of obstructive CAD. The combination of a positive CAC (calcium score greater than 0) and abnormal treadmill-ECG raised the specificity to 83% for obstructive disease).
Kajinami et al. (44) evaluated 251 symptomatic patients who underwent coronary angiography, fast CT, ECG, and thallium exercise testing. The ECG and thallium exercise tests had overall sensitivity of 74% and 83%, respectively, and specificity of 73% and 60%, respectively. The sensitivity and specificity of CAC scoring were 77% and 86%, respectively. In a related study (45), 150 patients underwent thallium stress testing, fast CT, and coronary angiography. The relative risk of an abnormal thallium stress test was 3.5, compared to 14.9 for an elevated CAC score as detected by fast CT. Yao et al. (46) compared technetium-99m single-photon emission tomography and fast CT in 51 patients with suspected CAD. Although differences were found between the 2 testing methods in patients with single-vessel CAD, the sensitivity, specificity, and accuracy were comparable in patients with multivessel CAD.
Schmermund et al. (47) also compared fast CT CAC measurement to nuclear stress test results in a cohort of 308 symptomatic patients. The association of CAC score with angiographically detected obstructive coronary disease remained highly significant after excluding the influence of all interrelated risk factors and SPECT variables (p less than 0.0001).
Data also support a complementary role for coronary calcium and myocardial perfusion scanning (MPS) measurements. He et al. (48) noted a threshold phenomenon with almost no observable myocardial hypoperfusion among patients with a CAC score less than 100 and with a marked increase in the frequency of an abnormal MPS in patients with high CAC values (greater than 100) (48). A recent study of 1195 patients who underwent CAC measurement and MPS assessment demonstrated that CAC was the most powerful predictor of an ischemic nuclear test, and that less than 2% of all patients with CAC less than 100 had positive MPS studies (49). CAC score, due to its high sensitivity for flow-limiting CAD, may be useful as a filter prior to invasive coronary angiography or stress nuclear imaging.
Other Uses of CAC Measurement in Symptomatic Persons
Another potential use of CAC is to determine the etiology of cardiomyopathy. The clinical manifestations of patients with ischemic cardiomyopathy are often indistinguishable from those patients with primary dilated cardiomyopathy. One large study in 120 patients with heart failure of unknown etiology demonstrated the presence of CAC was associated with 99% sensitivity for ischemic cardiomyopathy (50). Another study also demonstrated similarly high sensitivity using fast CT to differentiate ischemic from non-ischemic cardiomyopathy (51). This methodology has been demonstrated to be more accurate than echocardiography and MPS techniques in direct-comparison studies in this population (52,53). Additional comparative prognostic and diagnostic evidence is required to evaluate the role of CT as compared with conventional stress imaging techniques, as well as an assessment developing marginal cost effectiveness models.
Another potential application of CAC scoring relates to the triage of chest pain patients. Three studies have documented that CAC is a rapid and efficient screening tool for patients admitted to the emergency department with chest pain and nonspecific electrocardiograms (54–56). These relatively small-scale studies (with sample sizes ranging from 105 to 192) showed sensitivities of 98% to 100% for identifying patients with acute MI and very low subsequent event rates for persons with negative tests. The high sensitivity and high negative predictive value may allow early discharge of those patients with non-diagnostic ECG and negative CAC scans (scores = 0). Long term follow-up of one patient cohort demonstrated a very low risk of events in patients without demonstrated CAC at the time of emergency room visit (54). However, unlike the case with evaluations of asymptomatic patients (20), prognostic studies of CAC in symptomatic patients have generally been limited by biased samples (e.g., patients referred for invasive coronary angiography) and small numbers of hard outcome events. Future studies should include larger numbers of patients and should allow for adequate length of follow-up and assessment of larger numbers of hard endpoint events, especially all-cause mortality and myocardial infarction (57).
Summary
For the symptomatic patient, exclusion of measurable coronary calcium may be an effective filter before undertaking invasive diagnostic procedures or hospital admission. Scores less than 100 are
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