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Electron-Beam Computed Tomography in the Diagnosis of Coronary Artery Disease
A Meta-analysis
Brahmajee K. Nallamothu, MD, MPH;
Sanjay Saint, MD, MPH;
Lawrence F. Bielak, DDS, MPH;
Seema S. Sonnad, PhD;
Patricia A. Peyser, PhD;
Melvyn Rubenfire, MD;
A. Mark Fendrick, MD
Arch Intern Med. 2001;161:833-838.
ABSTRACT
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Background Electron-beam computed tomography (EBCT) is a new, noninvasive method
of detecting coronary artery calcification that is being increasingly advocated
as a diagnostic test for coronary artery disease (CAD). Before its clinical
use is justified, however, the overall accuracy of EBCT must be better defined.
Objective To estimate the accuracy of EBCT in diagnosing obstructive CAD.
Data Sources English-language studies from January 1, 1979, through Feburary 29,
2000, were retrieved using MEDLINE and Current Contents databases, bibliographies,
and expert consultation.
Study Selection We included a study if it (1) used EBCT as a diagnostic test; (2) reported
cases in absolute numbers of true-positive, false-positive, true-negative,
and false-negative results; and (3) used coronary angiography as the reference
standard for diagnosing obstructive CAD (defined as  50% diameter stenosis).
Data Extraction Data were extracted from the included articles by 2 independent reviewers.
Data Synthesis Weighted pooled analysis and summary receiver operating characteristic
(ROC) curve analysis were used to determine sensitivity and specificity rates.
Results from 9 studies with 1662 subjects were included. Pooled sensitivity
for EBCT was 92.3% (95% confidence interval [CI], 90.7%-94.0%) and pooled
specificity was 51.2% (95% CI, 47.5%-54.9%). Maximum joint sensitivity and
specificity for EBCT from its summary ROC curve was 75%. As the threshold
for defining an abnormal test varied, sensitivity and specificity changed.
For a threshold that resulted in a sensitivity of 90%, specificity was 54%;
when sensitivity was 80%, specificity rose to 71%.
Conclusion The performance of EBCT as a diagnostic test for obstructive CAD is
reasonable based on sensitivity and specificity rates from its summary ROC
curve.
INTRODUCTION
ELECTRON-BEAM computed tomography (EBCT) is a new, noninvasive method
of obtaining cross-sectional images of the heart in subsecond scanning times.1 Through the use of an electron x-ray source and 4
stationary tungsten targets, EBCT reduces the distorting effects of cardiac
motion and yields high-resolution CT images with limitation of artifact.1 Thus, EBCT can accurately detect and quantify even
small areas of coronary artery calcification, an established marker for atherosclerosis
and coronary artery disease (CAD).1-4
As a noninvasive test for CAD, EBCT has great appeal because it is fast (<15
minutes for an entire scan), simple to use (no physiological or pharmacological
intervention required), and predominantly operator independent.5-6
During the next few years, the number of EBCT scanners in clinical use
is anticipated to rise dramatically.5 Many
of these scanners will be used to evaluate suspected obstructive CAD (defined
as 50% diameter stenosis in any coronary vessel), one of the best-studied
clinical indications for EBCT.1, 4
Support for its use in this setting has come from several sources. In a 1996
consensus statement, the American Heart Association declared EBCT to be "sufficiently
accurate for predicting the presence of angiographic stenosis."4
Furthermore, evidence suggests that EBCT may be more cost-effective for diagnosing
obstructive CAD than traditional noninvasive testing.7
Before clinical use of EBCT can be justified, however, its overall diagnostic
accuracy, which has varied widely in published reports, must be more clearly
defined.
We therefore performed a meta-analysis to answer the question "What
is the overall discriminatory power of EBCT in diagnosing obstructive CAD
in pa tients undergoing coronary angiography?" Although the reported sensitivity
of EBCT ranges from 68% to 100% and specificity from 21% to 83%, some of the
variability across different studies, as with all diagnostic tests, is likely
due to differences in the test threshold used for defining an abnormal result.4 Until recently, no statistical framework existed to
account for the contribution of these different "positivity" thresholds on
the reported sensitivity and specificity of a test, which limited attempts
to combine results quantitatively from different evaluations. However, with
the development of summary receiver operating characteristic (ROC) curve analysis,
threshold differences across studies can be adjusted for, thereby allowing
for an objective review of available data.8-9
MATERIALS AND METHODS
We sought to summarize the discriminatory power for EBCT in diagnosing
obstructive CAD and to determine if the performance of EBCT in diagnosing
obstructive CAD was affected by selected study characteristics.
LITERATURE REVIEW
A computerized search was performed to identify relevant English-language
articles published from January 1, 1979, through February 29, 2000, in MEDLINE
and Current Contents databases. In MEDLINE, we combined medical subject headings tomography, x-ray computed or tomography
scanners, x-ray computed with the exploded term coronary disease. We performed a similar Current Contents search crossing
key words computed tomography or electron-beam computed tomography with coronary disease. We also scanned references in retrieved articles and contacted original
authors and experts to identify other published or unpublished reports.
STUDY ELIGIBILITY
We included a study if it (1) used EBCT as a diagnostic test for obstructive
CAD; (2) reported cases in absolute numbers of true-positive (TP), false-positive
(FP), true-negative (TN), and false-negative (FN) results or presented sufficient
data for deriving these numbers; and (3) used coronary angiography as the
reference standard for diagnosing obstructive CAD. Studies were excluded if
(1) performed exclusively in patients after coronary artery bypass graft surgery
or percutaneous transluminal coronary angioplasty; (2) findings other than
coronary artery calcification (eg, wall motion abnormalities and ventricular
size) were used as criteria for a positive result; or (3) incomparable EBCT
methods such as EBCT angiography or EBCT stress imaging were used. When several
studies were published by a similar group of authors, the corresponding author
from each report was contacted to determine whether significant overlap existed
across the different study groups; if groups overlapped by more than 50%,
we excluded results from the smaller study.
DATA EXTRACTION
Two of us (B.K.N. and L.F.B.) independently extracted data from each
article using a standardized form. Abstracted information included descriptive
data (authors, title, journal citation, and year of publication), study group
characteristics (sample size, mean age, proportion of men, and prevalence
of obstructive CAD), study design characteristics (for EBCT this related to
the threshold used to define a positive result and protocol information, whereas
for the reference coronary angiogram this referred to the angiographic definition
used for obstructive CAD), extent of blinding between readers of EBCT studies
and the reference standard, and evidence of verification bias. For each study,
results of the accuracy of EBCT were organized into a 2 x 2 table that
classified outcomes as TP, FP, TN, and FN. When an article reported more than
1 set of results (using different positivity thresholds), the single set most
emphasized by the authors was identified and tabulated for further analysis.
Any inconsistencies or controversies encountered in abstracted data were resolved
through discussion and consensus.
DATA ANALYSES
Pooled sensitivity and specificity estimates for EBCT were calculated
using a fixed-effects model that weighted each report by its sample size.8 We constructed corresponding 95% confidence intervals
(CIs) for sensitivity and specificity estimates.
We used a previously described method of variance-weighted least squares
regression to estimate the summary ROC curve for EBCT.9-12
Using data from the 2 x 2 table of each report, logit transformations
of the TP rate (sensitivity) and FP rate (1 - specificity) were performed.
The differences of the logit transformations (measures of the observed discriminatory
power of EBCT) were then regressed on the sums of the logit transformations
(measures of the positivity threshold used for determining a positive EBCT
result). A summary ROC curve for EBCT was constructed by means of back transforming
the fitted line from the regression model. We weighted each study in the regression
model by its variance and restricted the final summary ROC curve to the range
of observed TP and FP rates.
We characterized the summary ROC curve for EBCT by a point referred
to as the "maximum joint sensitivity and specificity," or the upper-left-most
point of the summary ROC curve.11 This point
is the maximum attainable common value of sensitivity and specificity and
is an overall measure of the discriminatory power of a test (eg, a perfect
test would have a maximum joint sensitivity and specificity of 100%). More
important, this point does not indicate the only or even the best combination
of sensitivity and specificity for a particular clinical setting. Rather,
the summary ROC curve demonstrates the inherent trade-off that exists between
sensitivity and specificity in any test as its positivity threshold is varied.
The addition of other covariates to the regression model allowed us
to evaluate the impact of selected study characteristics on the overall discriminatory
power of EBCT.9-12
The ß coefficients for covariates added to the model give an adjusted
measure of test performance for selected characteristics, with positive coefficients
indicating improved discriminatory ability and negative coefficients indicating
less discriminatory ability. Selected characteristics that we examined as
potentially related to test accuracy included sample size, mean age, proportion
of men in the study group, percentage of study group with obstructive CAD,
presence of blinding, and year of publication. The overall suitability of
the pooled and summary ROC curve analyses was evaluated using the Spearman
correlation coefficient.8 Heterogeneity was
assessed in a standardized manner by determining whether the predicted discriminatory
power for each study fell within the 95% CIs of the observed discriminatory
power for each study.9-12
All analyses were performed using commercially available software (Stata,
version 5; Stata Corporation, College Station, Tex).
RESULTS
SUMMARY OF LITERATURE REVIEW
We retrieved 455 citations from the computerized search (431 citations
were from MEDLINE; 38 were from Current Contents, and 14 were common to both
databases). Reasons for exclusion are delineated in Table 1. Five studies were excluded because of a substantial degree
of study group overlap.13-17
Nine studies satisfied all inclusion criteria and were included in the meta-analysis.18-26
One article, the multicenter study by Budoff and colleagues,18
reported results from 6 different sites (State University of New York–Buffalo;
Harbor–University of California–Los Angeles Medical Center, Torrance;
University of Illinois, Chicago; University of Iowa, Iowa City; Mount Sinai
Hospital, Miami, Fla; and Washington State University, Spokane) as a single,
pooled set of sensitivity and specificity rates.18
Because each center used different criteria in selecting a study population
and interpreting EBCT results, the pooled set of results may have incorrectly
estimated the overall accuracy of EBCT. We therefore obtained original data
from the corresponding author (Matthew Budoff, MD) to calculate 6 separate
center-specific TP and FP rates. A total of 14 reports from the 9 studies
were included in our analysis.
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Table 1. Reasons for Exclusion of Reports*
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Details from the included articles are summarized in Table 2. The mean number of subjects per report was 119, with study
groups varying in size from 50 (Washington State University)18
to 251.20 Reported sensitivity ranged from
81%19 to 99%26
and specificity ranged from 14% (Washington State University)18
to 83%.26 Most subjects were men (overall,
71%), with the proportion of men in each report ranging from 48%21
to 94%.19 Study groups in all instances consisted
of individuals undergoing coronary angiography for evaluation of obstructive
CAD. Five reports listed specific reasons for the referral.19, 22-25
Chest pain was the most common indication for coronary angiography in these
studies, with the percentage of patients undergoing evaluation for this symptom
ranging from 45%19 to 100%.22, 24
Other indications for coronary angiography included recent myocardial infarction,
evaluation for valvular disease, and preoperative risk assessments. One study
evaluated the accuracy of EBCT exclusively in patients with a decreased ejection
fraction (<0.40) to assess its ability in distinguishing between nonischemic
and ischemic causes of systolic dysfunction.26
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Table 2. Summary Characteristics of Included Studies*
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Similarities in EBCT protocols among the studies included the use of
Agatston scoring, a standard definition of significant attenuation at 130
Hounsfield units, 100-millisecond scanning times, 3-mm slice thickness, and
a scan acquisition trigger gated to 80% of the R-R interval. Variations between
the study protocols existed and, most important, included different definitions
of the minimum area of tissue attenuation required for a lesion to be considered
calcium and not artifact; minimum areas ranged in size from 0.520, 24-25
to 2 mm2.23 In general, study protocols
were unclear as to the number of tomograms obtained in each examination (range,
20-40) and whether a standard inspiration or expiration breath-hold was used
during image acquisition.
All studies except 1 assessed obstructive CAD similarly, defining it
as at least a 50% diameter stenosis in any vessel.20
Kajinami et al20 used computer-assisted cinevideodensitometry
to define significant angiographic obstruction as at least 75% densitometric
narrowing. However, in cases where accurate densitometric measurements could
not be made, a definition of obstructive CAD similar to the other studies
(ie, 50% diameter stenosis) was used. Only 2 studies explicitly stated
that blinding occurred between EBCT and the coronary angiogram readings.20, 26 Subjects in all studies underwent
EBCT and coronary angiography, with no direct evidence that individuals were
referred to angiography based on EBCT results. However, the possibility of
verification bias could not be excluded definitively from any of the studies.
DATA ANALYSES
Pooled sensitivity for EBCT was 92.3% (95% CI, 90.7%-94.0%) and the
pooled specificity was 51.2% (95% CI, 47.5%-54.9%). The summary ROC curve
shown in Figure 1 summarizes joint
TP and FP rates for EBCT from the included reports across a range of observed
positivity thresholds. If a positivity threshold is used that yields a sensitivity
of 80% for EBCT, specificity is likely to be 71%. If the positivity threshold
is adjusted to increase sensitivity to 90%, specificity can be expected to
fall to 54%. The maximum joint sensitivity and specificity rate for EBCT—the
upper-left-most point in the summary ROC curve where sensitivity equals specificity—is
75%. This point is the maximum attainable common value of sensitivity and
specificity for EBCT.
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Summary receiver operating characteristic curve for electron-beam
computed tomography in the diagnosis of obstructive coronary artery disease.
TPR indicates true-positive results; FPR, false-positive results. Numbers
in graph identify the following individual studies: Budoff et al,18 Yao et al,19 Kajinami
et al,20 Yaghoubi et al,21
Baumgart et al,22 Bielak et al,23
Braun et al,24 Rumberger et al,25
and Budoff et al.26 For Budoff et al,18 a indicates State University
of New York–Buffalo; b, Harbor–University
of California–Los Angeles, Torrance; c, University
of Illinois, Chicago; d, University of Iowa, Iowa
City; e, Mount Sinai Hospital, Miami, Fla; and f, Washington State University, Spokane.
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The only study characteristic found to have a significant impact on
the discriminatory power of EBCT was sample size. Studies with more than 100
subjects reported higher discriminatory powers for EBCT than smaller studies
(ß coefficient, 0.81; 95% CI, 0.18-1.44; P =
.01). The Spearman correlation coefficient between the TP and FP rates was
0.27 (P = .35), suggesting that it was appropriate
to combine results using summary ROC analysis.8
TESTING FOR HETEROGENEITY
Results from 4 reports demonstrated substantial heterogeneity (2 reports
were from sites in the multicenter trial by Budoff and colleagues [State University
of New York–Buffalo and University of Iowa]).18, 24, 26
In 3 of the reports, no obvious differences in study design or patient characteristics
could be identified, with predicted discriminatory powers for the report falling
just outside the 95% CIs of the observed discriminatory powers for the report.18, 24 One study, however, examined the
use of EBCT exclusively in patients with documented systolic dysfunction and
reported a much greater discriminatory power for EBCT than predicted, which
suggests that its accuracy in these individuals may be better than that in
other groups.26 More important, we found no
substantial effect on the final results of the model after repeating our analysis
with these 4 reports excluded. Our final results therefore include all 14
reports from the 9 studies.
COMMENT
We summarized the discriminatory performance of EBCT in diagnosing obstructive
CAD through the use of a summary ROC curve, a new methodological tool for
diagnostic meta-analyses.8-9 Although
a previous meta-analysis of EBCT accuracy in CAD has been published,27 our evaluation was substantially different because
we addressed the important issue of overlap between study groups and used
summary ROC curve analysis to combine data. Summary ROC curves, like conventional
ROC curves, graphically represent sets of sensitivity and specificity rates
for a diagnostic test as the positivity threshold of a test is varied. However,
although a conventional ROC curve summarizes the performance of a test in
a single study population, a summary ROC curve describes a single set of operating
characteristics for a test across multiple studies. Results from its summary
ROC curve suggest that the diagnostic accuracy of EBCT in detecting obstructive
CAD is reasonable with sensitivity and specificity rates comparable to those
for traditional exercise stress testing.28
Although the maximum joint sensitivity and specificity of EBCT from
our analysis is near 75%, a single set of ideal sensitivity and specificity
rates for EBCT cannot be determined from the summary ROC curve alone. The
choice of an effective set of operating characteristics will need to be based
on a clinician's desire for a particular specificity (increasing likelihood
of false assumption of CAD with 50% angiographic stenosis) or sensitivity
(assurance of not missing CAD with 50% angiographic stenosis). Clinicians,
for instance, may use lower threshold criteria to increase the sensitivity
of EBCT for detecting obstructive CAD in younger patients with atypical chest
pain and no risk factors (ie, a low pretest probability of obstructive CAD).
Conversely, higher positivity thresholds may be set when greater specificity
is desired, as when examining older individuals with a higher likelihood of
obstructive CAD. Unfortunately, our meta-analysis is unable to tell us how
to set positivity thresholds explicitly to alter sensitivity and specificity
rates in distinct patient populations or at different clinical centers. Although
additional research is needed, the ease of altering positivity thresholds,
through adjusting minimum size criteria for lesions or calcium scores,4, 16-17,23 is
a potential advantage for EBCT compared with traditional noninvasive tests
for CAD.
As a diagnostic test, EBCT has other desirable features. These include
a brief and simplified testing protocol, a reasonable cost (estimated at $375-$450),
and results that are reproducible and independent of the patient's effort
or the test operator's experience.1, 4, 6
Moreover, calcium scores from EBCT have been shown to correlate with the angiographic
severity of CAD and may be useful in predicting left main or 3-vessel coronary
disease.16, 18, 29
Although evidence is still conflicting, EBCT results may also yield prognostic
information about an individual's likelihood of future coronary events.14, 30-31 Finally, since hemodynamically
significant lesions are required for a positive result in traditional noninvasive
tests, EBCT may be the best and only noninvasive instrument that can accurately
identify nonsignificant but clinically important CAD lesions. Although this
may eventually become EBCT's most important advantage compared with traditional
diagnostic tests for CAD, our meta-analysis was unable to address this issue
because of a lack of current data on the accuracy of EBCT at detecting "subcritical"
lesions in asymptomatic individuals.
There are several important limitations to the current use of EBCT that
should be noted. First, there continues to be a wide variation in protocols
for performing EBCT, which could lead to problems with its reproducibility
and accuracy across facilities.23 Prospective
studies have also been unable to demonstrate that EBCT can localize "culprit"
lesions. Furthermore, EBCT provides no physiologic or functional data and
gives little or no information about left ventricular function or valvular
disease.1, 4 Advanced imaging strategies,
which include the use of intravenous contrast and/or stress images, are being
developed to address several of these limitations.
In addition to summarizing the accuracy of EBCT, our study attempted
to identify any study characteristics that could have influenced its performance.
We found that larger studies (>100 subjects) reported small but significantly
greater discriminatory powers, which suggests that a study group's size may
influence the final outcomes. Although it has been suggested that the accuracy
of EBCT may be improved in certain age and sex groups,15
we found no evidence to support such an association. Unfortunately, the small
number of studies in this analysis limited our ability to detect such differences.
The results of our meta-analysis should be interpreted in context of
the following limitations. First, studies included in our analysis varied
widely in terms of study group demographics, prevalence of obstructive CAD,
and EBCT protocol. Despite this variability, tests for heterogeneity did not
indicate that the studies were significantly different except in 4 reports,
and repeating our analysis after excluding these reports did not substantially
affect our overall results. Second, all studies included in our analysis used
study groups that consisted of individuals referred for coronary angiography.
Given the current clinical indications for coronary angiography, it is likely
that subjects from these studies were at high risk for obstructive CAD; thus,
sensitivity and specificity rates could be different if this test was used
in groups with a lower pretest probability of obstructive CAD. Third, several
of the studies in our analysis had important limitations in study design that
could have influenced their reported results. The lack of universal blinding
between clinicians reading EBCT studies and the reference test, for instance,
could have overestimated the accuracy of EBCT. Also, all studies were conducted
in symptomatic patients who had their CAD status verified using coronary angiography
findings and all studies were therefore subject to verification bias. This
would have biased results toward an overestimation of sensitivity and an underestimation
of specificity.32 Fourth, we estimated the
sensitivity and specificity rates for EBCT at detecting at least a 50% diameter
stenosis in any coronary vessel. We were not able to estimate its accuracy
in lesions across a range of anatomic severity. Finally, publication bias
is a possible weakness of any meta-analysis.9, 33
Although we attempted to locate unpublished studies, none were found. If studies
with favorable results have a greater likelihood of being published, overall
accuracy for EBCT may be inflated.
CONCLUSIONS
Our meta-analysis summarizes currently available data on the performance
of EBCT in diagnosing obstructive CAD. Based on our results, EBCT appears
to be reasonably accurate at detecting obstructive CAD in patients undergoing
coronary angiography, with sensitivity and specificity rates comparable to
those reported for traditional exercise stress testing. Of course, further
studies are needed to clarify the accuracy of EBCT across atherosclerotic
lesions of lesser or greater severity than those with a 50% diameter stenosis,
at different explicit positivity thresholds, and to determine its exact role
among the current armamentarium of noninvasive tests for CAD. Until then,
however, our results provide clinicians with estimates of the overall accuracy
of EBCT, allowing them to better interpret results from this rapidly diffusing
diagnostic innovation.
AUTHOR INFORMATION
Accepted for publication October 2, 2000.
Dr Nallamothu completed this work while under grant support from the
Agency for Healthcare Research and Quality, Rockville, Md. This study was
also supported in part by grant R01 HL-46292 from the National Institutes
of Health, Bethesda, Md.
Presented in part at the 23rd Annual Meeting of the Society of General
Internal Medicine, Boston, Mass, May 6, 2000.
We thank Matthew Budoff, MD, for providing original data for our analysis
and for his review of the manuscript and helpful suggestions and Robert Detrano,
MD, PhD, for his review of the manuscript and helpful suggestions.
Corresponding author and reprints: Brahmajee K. Nallamothu, MD, MPH,
B1F245 University Hospital, Ann Arbor, MI 48109-0022 (e-mail: bnallamo{at}umich.edu).
From the Divisions of General Medicine (Drs Nallamothu, Saint, and
Fendrick) and Cardiology (Drs Nallamothu and Rubenfire), Department of Internal
Medicine, the Department of Surgery (Dr Sonnad), and the Consortium for Health
Outcomes, Innovation, and Cost-Effectiveness Studies (Drs Sonnad and Fendrick),
University of Michigan Medical School, and the Department of Epidemiology,
University of Michigan School of Public Health (Drs Bielak and Peyser), Ann
Arbor.
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Cost-effectiveness of Electron-Beam Computed Tomography in the Diagnosis of Coronary Artery Disease
Tsung O. Cheng
Arch Intern Med. 2001;161(21):2624.
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Electron-Beam Computed Tomography as a Population Screening Tool
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Arch Intern Med. 2001;161(21):2624-2625.
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