(Circulation. 1999;99:2633-2638.)
© 1999 American Heart Association, Inc.
Clinical Investigation and Reports |
Coronary Calcium Does Not Accurately Predict Near-Term Future Coronary Events in High-Risk Adults
From the Division of Cardiology, Department of Medicine, Harbor-UCLA Medical Center, Torrance (R.C.D., T.M.D., W.T., L.E.G., M.J.B., K.A.N.); the Heart Disease Prevention Program, Department of Medicine, University of California, Irvine (N.D.W.); and the Department of Statistics, University of California, Riverside (R.M.S.), Calif.
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Abstract |
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Background—Prognostic risk models have had limited success in predicting coronary events in subjects with multiple risk factors. We and others have proposed an alternative approach using radiographically detectable coronary calcium. We evaluated and compared the predictive value of these 2 approaches for determining coronary event risk in asymptomatic adults with multiple coronary risk factors. In addition, we assessed the predictive value of a risk model that included calcium score and cardiac risk-factor data.
Methods and Results—We recruited 1196 asymptomatic high-coronary-risk subjects who then underwent risk-factor assessment and cardiac electron-beam CT (EBCT) scanning and were followed up for 41 months with a 99% success rate. We applied the Framingham model and our data-derived risk model to determine the 3-year likelihood of a coronary event. The mean age of our cohort was 66 years, and mean 3-year Framingham risk was 3.3±3.6%. Sixty-eight percent (818 subjects) had detectable coronary calcium. There were 17 coronary deaths (1.4%) and 29 nonfatal infarctions (2.4%). The receiver operating characteristic (ROC) curve areas calculated from the Framingham model, our data-derived risk model, and the calcium score were 0.69±0.05, 0.68±0.05, and 0.64±0.05, respectively (P=NS). When calcium score was included as a variable in the data-derived model, the ROC area did not change significantly (0.68±0.05 to 0.71±0.04; P=NS).
Conclusions—Neither risk-factor assessment nor EBCT calcium is an accurate event predictor in high-risk asymptomatic adults. EBCT calcium score does not add significant incremental information to risk factors, and its use in clinical screening is not justified at this time.
Key Words: risk factors • calcium • coronary disease • tomography
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Introduction |
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TopAbstractIntroductionMethodsResultsDiscussionReferences |
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Although coronary atherosclerosis is the leading cause of morbidity and mortality in persons with coronary risk factors,1 the majority of these individuals never develop coronary symptoms. Often, the first indication that coronary atherosclerosis is present is acute myocardial infarction or sudden death. Identification of those subjects with a high probability of suffering such a catastrophe is therefore of great interest, particularly because coronary disease is an increasingly treatable pathological entity.
Asymptomatic persons with risk factors stand to benefit from aggressive risk-factor modification and/or further testing to reduce morbidity and mortality. Grover et al2 found that an algorithm derived from the Framingham Heart Study was an accurate predictor when applied to future events in the Lipid Research Clinic cohort.3
Recently, an alternative approach to risk stratification in this subset has been proposed4 : noninvasive evaluation of coronary calcium by electron beam CT (EBCT). This approach is based on the close histopathological association of calcium with coronary atherosclerosis.4 5 Although coronary calcium assessment has been reported to be of moderate value in predicting coronary events,5 it is not known whether EBCT calcium scanning offers a significant advantage over either information obtained from risk factors or application of the Framingham algorithm.
The primary aim of this investigation was to prospectively compare calcium scanning with risk-factor assessment for predicting coronary heart disease events in asymptomatic high-risk subjects.
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Methods |
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Recruitment of Subjects
The South Bay Heart Watch is a government-funded, prospective study designed to appraise the value of risk-factor assessments and coronary calcium or predicting coronary outcomes in asymptomatic adults. This study received approval of the Harbor-UCLA Human Subjects Committee, and all participating subjects gave informed consent.
After a preliminary advertising campaign, we mailed 100 000 letters of
invitation to households whose heads were 
45 years old, inviting
subjects with 2 coronary risk factors to participate in a
coronary research project. The Heart Watch screening clinic
evaluated 5023 respondents between December 1990 and December 1992.
A nurse administered a previously described angina questionnaire,6 assessed cardiac history (prior myocardial infarction or revascularization), and recorded an ECG. Subjects with ECG evidence of infarction or a clinical history of infarction, revascularization, or typical angina were excluded. The nurse administered a risk-factor questionnaire and measured blood pressures and blood cholesterol level. The nurse used the risk-factor information to calculate the risk of coronary events during an 8-year period according to the Framingham risk equation7 and excluded subjects found to have a <10% risk. The 1461 subjects (29% of respondents) without symptoms or evidence of prior coronary disease and at highest risk were enrolled in the cohort and followed clinically with yearly visits or phone calls.
Thirty months after enrollment, we asked surviving subjects to undergo a second medical and risk-factor evaluation, as well as EBCT examinations for coronary calcification. The study sample of the present report consisted of the 1196 subjects (82%) who were still asymptomatic and who agreed to return for testing and be followed up for an additional 3 years.
Risk-Factor Evaluations
Risk-factor and medical evaluations, including phlebotomy for
total and HDL cholesterol and ECG, were done at enrollment
and were repeated before the EBCT examination performed 30 months
later. These latter values were used in this report. Details of
risk-factor assessment methodology have been reported
previously.8 ECGs were reviewed independently by 3
board-certified cardiologists who had no knowledge of EBCT or other
results.
EBCT Scanning
We performed EBCT scans within 2±2 days after
risk-factor evaluation, using an Imatron C-100 scanner. Exposure time
was 100 ms per image slice, and total skin radiation was <600 mrad per
scan. ECG triggering was used to acquire images at 80% of the RR
interval. A standardized and reproducible thick-slice protocol using
6-mm image slices was used. In an initial preliminary report, we
confirmed that this protocol has an accuracy for predicting events
equivalent to that of more variable 3-mm
protocols.9
EBCT Analysis
A cardiologist experienced in coronary angiography and
tomographic imaging assessed each scan. A region of interest 66
mm2 in area10 was created that was
precisely centered on each locus of calcification, defined as a volume
of 8.16 mm3 with a CT number >130
Hounsfield units (HU)11 within the distribution of a
coronary artery. The mean and peak CT number and the area of
the subsets of pixels with a CT number >130 HU within these regions
were calculated. The calcium score was calculated according to the
method of Agatston et al.11
Risk Factors
Framingham Risk Model
Anderson et al7 12 derived prognostically useful
regression models from the Framingham data based on age, sex, and risk
factors. The model we applied predicts the hard end points of acute
myocardial infarction or coronary death12 and is
summarized in Table 1
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Data-Derived Risk Model
To determine the data-derived risk-factor model, we fit an
accelerated failure time (AFT) model to the time of coronary
death or infarction with independent variables as listed in Table 2.12 13 14 An AFT model
assumes that the effect of independent variables on an event-time
distribution is multiplicative on the event time. The scale function is
exp -(BxX), where X is the vector of covariate values and B is the
vector of parameters shown in Table 1
. A positive
value for a parameter implies that an increase in the value
of its associated covariate will decrease the time scale and thus lower
the risk of an event; the opposite is true for a decrease in the
covariate. Similarly, a negative value for a parameter
implies that an increase in its associated covariate will increase the
time scale and thus increase the risk.
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Here, the baseline survival distribution was taken to be Weibull
distribution, so as to closely approximate the derivation of the
Framingham model. Although the Framingham model was based on a
nonproportional hazards Weibull AFT,14 we chose to fit the
simpler (constant-variance) model. Each model was fit by use of the
1196 time intervals until coronary death or infarction or until
censoring occurred. Stepwise regression was used to choose
variables for this model from the list of risk factors in Table 1 and their first-degree interactions. The criterion for entry
into the model was a value of P<0.05.
To appropriately determine the accuracy of a probability model in determining risk in a given population, the model should be derived and tested in separate samples. To accomplish this and preserve maximum statistical power, we used a modified bootstrap approach,15 as follows. A recursive macro computer program deleted 1 observation, refit the accelerated failure time model to the remaining 1195 observations, and predicted the response value (probability of coronary death or infarction) for the deleted observation. This procedure was repeated for all 1196 observations. The resulting response values (risks) were used to determine sensitivities and false-positive rates for predicting myocardial infarction or coronary death.
Follow-Up
One, 2, and 3 years after the EBCT examinations, we contacted
participants by telephone. At that time, we assessed coronary
heart disease using questions concerning intervening hospital
admissions and review of medical records for these admissions. We
considered a follow-up attempt successful when surviving subjects
either returned to the clinic or completed a telephone interview and
all relevant medical records were obtained. For deceased subjects,
we defined successful follow-up as the procurement of relevant medical
records, transcribed conversation with next of kin, death
certificate, or autopsy report.
A committee of 3 board-certified cardiologists reviewed medical records and transcripts of conversations with next of kin, without knowledge of other data, and applied majority rule to determine the occurrence of myocardial infarction or coronary heart disease death.
Event Definitions
We defined myocardial infarction as the presence of 2 of the
following 3 factors: (1) prolonged chest pain prompting hospital
admission, (2) diagnostic evolutionary ECG changes, and (3)
elevation of serum creatine kinase to twice the upper limits of normal
or a positive serum creatine kinase MB fraction.
The research team confirmed all deaths with medical records or death certificates. The committee reviewing medical records considered coronary heart disease death to have occurred if the death (1) was proved to be due to coronary atherosclerosis by autopsy, (2) occurred within 1 hour after the onset of prolonged severe chest pain, or (3) occurred during hospital admission for acute myocardial infarction. Coronary heart disease was considered to be present if either myocardial infarction or coronary heart disease death had occurred.
Incremental Value of Calcium Score
To test the incremental effect of coronary calcium score
on prognosis after risk factors had been considered, we repeated the
derivation and testing of the AFT model described above, but with the
calcium score as an additional variable. Once again, we applied the
recursive bootstrap method to ensure independence between the training
and testing sets.
Study Power
We prospectively determined that a study sample of 1200 subjects
would be needed to detect ROC curve area differences of between 0.1 and
0.2. With this sample size, we calculated that the study would have a
power of between 72% and 100% with an 
error of 0.05. Thus, this
investigation had sufficient power to detect clinically important
differences in discrimination if these existed.
Statistical Comparisons
We compared categorical data using 
2
tests or 2 tests for trends, as appropriate.
We constructed receiver operating characteristic (ROC) curves in the
following manner. The probability values determined from the Framingham
and data-derived models and the calcium scores were used as thresholds
to categorize the results as either positive (higher than this
threshold) or negative (no higher than this threshold). We thus
determined true- and false-positive rates for each threshold and
constructed ROC curves. We applied the method of Hanley and
McNeil16 to calculate and compare areas under these
curves. These areas represent the probability that the approach
can discriminate between those who will suffer events from those who
will not. An area of 1 represents perfect; an area of 0.5,
random discrimination.
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Results |
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Patient Characteristics
Of the 1461 subjects, 1196 (82%) were in the reconstituted study sample. The ethnic distribution of the study sample was similar to that of the population of the South Bay suburbs.17 The health and vital status of all but 1 of those who did not return for the EBCT scan were successfully determined in a manner identical to that described above. Of these 265 subjects, 67 had died, 78 had developed symptoms of coronary heart disease (either angina or acute myocardial infarction), and the remaining 119 had either moved from the Los Angeles area or for other reasons did not return for the EBCT study. The 119 surviving subjects who did not undergo scanning had a mean Framingham risk that was not significantly different from our cohort of subjects who did undergo scanning.
Follow-Up
All but 2 of the 1196 subjects who underwent scanning were
successfully followed up for 41±5 months. The mean age of the subjects
at the time of scanning was 66±8 years; 89% were men. Table 2
shows the demographics and risk factors for these subjects. The
enrollment strategy had aimed for a high-risk cohort; accordingly, the
percentages of subjects with risk factors were high.
Coronary Events
Fifty coronary heart disease events occurred in 46
subjects (3.8%) during the 41±5-month period after scanning. These
events included 17 coronary heart disease deaths and 33 acute
myocardial infarctions (4 fatal). In addition, there were 46 deaths not
attributable to coronary heart disease. Forty-two subjects
underwent revascularization after their scans; all
had complained of chest discomfort, prompting further evaluation
leading to coronary angiography. Eighteen of these
revascularizations were performed in subjects who
did not have coronary events (myocardial infarction or
coronary death) either before or after
revascularization. Thus, 64 subjects either
suffered a serious coronary event or underwent
revascularization.
Coronary Events and Risk Factors
The median 3-year Framingham risk of infarction or
coronary death was 4.4%. The relative risk of a value higher
than this for predicting these outcomes was 2.5 (P=0.003).
The median data-derived risk was 2.7%. Subjects with data-derived
risks >2.7% were 3.6 times as likely to suffer an event
(P<0.001).
Coronary Events and EBCT Calcium Scores
Two-thirds of the subjects had detectable coronary calcium
(score >0). The median coronary calcium score was 44. Subjects
with a calcium score >44 were 2.3 times as likely to suffer infarction
or coronary death than subjects with lower scores. Subjects
were divided into equal tertiles based on risk or calcium scores. Table 3 shows the distributions of Framingham
and data-derived risks and calcium scores in each tertile. Figures 1 and 2
show the distributions of coronary events and
revascularizations by tertiles of Framingham risk
and data-derived risk and calcium scores. The trends toward higher
event incidence with increasing Framingham risk are significant for
infarction (P<0.001), either coronary death or
infarction (P<0.001),
revascularizations (P=0.004), and any of
these (P<0.001), and marginally significant for
coronary death alone (P=0.04). These trends are
significant for all types of events for the data-derived risks
(P<0.001). Figures 1 and 2 show the
distribution of events by tertiles of coronary calcium score.
There was a significant trend toward greater frequency of infarctions
(P=0.003), but not for coronary deaths
(P=0.14). The composite end points of coronary death
or infarction and coronary death, infarction, or
revascularization were significantly increased in
the higher tertiles of calcium score (P<0.01).
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ROC Curve Analysis
Table 4 shows the ROC curve areas
for predicting events (infarction or coronary death) calculated
by risk-factor assessment (Framingham and data-derived risk models) and
EBCT calcium scanning (calcium score). These areas are the probability
of discriminating subjects who will have an event from those who will
not. An area of 1 represents perfect discrimination, whereas an
area of 0.5 indicates random discrimination. We also calculated the ROC
area of a risk model including the calcium score.
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The area under the curve for our data-derived model for predicting infarction or coronary heart disease death was not significantly higher than the areas under the other 2 curves (0.68±0.05 for data-derived model; 0.69±0.05 for Framingham; 0.64±0.05 for calcium score; P=NS). The area under the curve representing the data-derived model including the calcium score was 0.71±0.04. This ROC curve area also was not significantly higher than the areas under the other ROC curves. The similarity of the ROC curve areas for risk-factor assessment and calcium score indicates that both of these have equivalent discriminatory ability in predicting coronary death or infarction.
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Discussion |
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TopAbstractIntroductionMethodsResultsDiscussionReferences |
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The results of this investigation demonstrate that, in high-risk asymptomatic adults with risk factors, EBCT coronary calcium score is equivalent to risk-factor assessment in distinguishing individuals who will suffer coronary death or infarction from those who will not. Furthermore, coronary calcium assessment with EBCT added no prognostic information beyond that obtained by assessment of standard risk factors. Both approaches predicted death or infarction with only fair accuracy, as indicated by the magnitudes of the ROC curve areas.
Our subjects represented a subset of the spectrum of coronary risk in that they had relatively high coronary risk, and the distribution of risk factors was somewhat blunted at the lower end. Although a result of study design and power considerations, this somewhat select risk-factor distribution may not wield the same prognostic and discriminative power as in other cohorts with wider distributions of risk factors. For example, Grover et al2 applied the Framingham risk model in the Lipid Research Clinics subjects and found a better association between calculated and actual risk with an ROC curve area of 0.85, compared with 0.65 for our high-risk cohort. We attribute the relatively poorer performance of risk-factor assessment in our subjects to the uniformly high risk-factor levels seen in our subjects compared with that of the Lipid Research Clinics.2
For example, our subjects were older than those in the Lipid Research Clinics trial (mean age, 66 compared with 47 years). Of pertinence, other studies have shown that hypercholesterolemia and low HDL cholesterol are only weak predictors of coronary mortality or infarction in older patients.18 Similarly, the relationship between hypertension and mortality has been found to be weaker in elderly subjects,19 and a history of diabetes was not significantly correlated with coronary disease in men or women >62 years old.20 It has been suggested that these findings may be attributed at least in part to the increased prevalence of chronic diseases and their correlated mortality, which are associated with aging.20 Thus, the effects of coronary risk factors on a chronic basis may in some cases result in mortality from diseases not directly related to coronary heart disease and preclude the occurrence of a cardiac end point.
Although it has been proposed that EBCT may be useful as a screening tool to prospectively identify high-risk subjects with preclinical atherosclerosis, studies conducted with asymptomatic patients are scarce8 21 and show conflicting results. A recent scientific advisory of the American Heart Association5 suggested that EBCT scanning should be applied clinically only to symptomatic subjects. The results of the present investigation support this advisory; the predictive value of coronary calcification, at least in high-risk subjects, is no better than that of evaluation of standard coronary risk factors—an approach that is simpler and cheaper and yields treatable entities.
Limitations
Our study cohort was predominantly male, and all subjects were
45 years old. Moreover, the distributions of risk factors in our
subjects were, by design, limited because individuals with relatively
low risk were excluded. Further prospective investigations addressing
the prognostic significance of coronary calcium in women, as
well as subjects of diverse ethnicity, age, and coronary risk,
are clearly needed. Coronary calcium may have a different
significance in other populations, such as those with lower Framingham
risk.
Subjects were advised as to their calcium scores and their risk factors. Although they were counseled to modify their risk factors accordingly, they were told that the calcium scores were research results of uncertain significance. Still, knowledge of risk factors and calcium scores might have caused behavioral changes and a bias of the results toward either of the approaches to screening.
The duration of follow-up (41 months) is the longest reported to date of any prospective investigation that used EBCT calcium scanning. Nevertheless, it is relatively short compared with other epidemiological studies. Further follow-up could demonstrate EBCT to be of value in selected asymptomatic subjects, and such follow-up is ongoing in our cohort.
Conclusions
The results of this investigation indicate that EBCT screening,
although intuitively logical,7 is not more effective than
the less expensive approach using risk-factor information in
asymptomatic adults at high risk by conventional
risk-factor analysis. Furthermore, the magnitude of the ROC
curve areas reported here (
0.65) indicates that neither EBCT nor
risk-factor assessment discriminates, with high accuracy, those
destined to suffer coronary death or infarction from those who
will not. These results may not be valid for patients with chest pain
syndromes for whom coronary calcium has been shown to have
clinical validity.5
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Acknowledgments |
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This study was supported by grant 7R01-HL-43277-02 from the National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, Md, and grants from Saint John's Heart Institute, Santa Monica, Calif, and the Kenneth T. and Eileen L. Norris Foundation, Los Angeles, Calif. We gratefully acknowledge the assistance and support of William J. French, MD, Chief of the Division of Cardiology at Harbor-UCLA Medical Center.
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Footnotes |
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Reprint requests to Robert C. Detrano, MD, PhD, Harbor-UCLA Medical Center, Cardiology Division, Bldg RB-2, 1124 W Carson St, Torrance, CA 90502-2064.
Received November 16, 1998; revision received February 18, 1999; accepted February 23, 1999.
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 J. C. Nelson, R. A. Kronmal, J. J. Carr, M. F. McNitt-Gray, N. D. Wong, C. M. Loria, J. G. Goldin, O. D. Williams, and R. Detrano Measuring Coronary Calcium on CT Images Adjusted for Attenuation Differences Radiology, May 1, 2005; 235(2): 403 - 414. [Abstract] [Full Text] [PDF]
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 N. R Mollet, F. Cademartiri, and P. J de Feyter Non-invasive multislice CT coronary imaging Heart, March 1, 2005; 91(3): 401 - 407. [Full Text] [PDF]
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 S. K Prasad, R. G Assomull, and D. J Pennell Recent developments in non-invasive cardiology BMJ, December 11, 2004; 329(7479): 1386 - 1389. [Full Text] [PDF]
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 R. Erbel, A. Schmermund, M. Abedin, Y. Tintut, and L. L. Demer Clinical Significance of Coronary Calcification Arterioscler. Thromb. Vasc. Biol., October 1, 2004; 24(10): e172 - e172. [Full Text] [PDF]
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M. Abedin, Y. Tintut, and L. L. Demer Vascular Calcification: Mechanisms and Clinical Ramifications Arterioscler. Thromb. Vasc. Biol., July 1, 2004; 24(7): 1161 - 1170. [Abstract] [Full Text] [PDF]
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 J. Golledge, M. McCann, S. Mangan, A. Lam, and M. Karan Osteoprotegerin and Osteopontin Are Expressed at High Concentrations Within Symptomatic Carotid Atherosclerosis Stroke, July 1, 2004; 35(7): 1636 - 1641. [Abstract] [Full Text] [PDF]
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G. B. J. Mancini, B. Dahlof, and J. Diez Surrogate Markers for Cardiovascular Disease: Structural Markers Circulation, June 29, 2004; 109(25_suppl_1): IV-22 - IV-30. [Full Text] [PDF]
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M. J. Pletcher, J. A. Tice, M. Pignone, and W. S. Browner Using the Coronary Artery Calcium Score to Predict Coronary Heart Disease Events: A Systematic Review and Meta-analysis Arch Intern Med, June 28, 2004; 164(12): 1285 - 1292. [Abstract] [Full Text] [PDF]
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J. E. Hokanson, T. MacKenzie, G. Kinney, J. K. Snell-Bergeon, D. Dabelea, J. Ehrlich, R. H. Eckel, and M. Rewers Evaluating Changes in Coronary Artery Calcium: An Analytic Method That Accounts for Interscan Variability Am. J. Roentgenol., May 1, 2004; 182(5): 1327 - 1332. [Abstract] [Full Text] [PDF]
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 P. Greenland, L. LaBree, S. P. Azen, T. M. Doherty, and R. C. Detrano Coronary Artery Calcium Score Combined With Framingham Score for Risk Prediction in Asymptomatic Individuals JAMA, January 14, 2004; 291(2): 210 - 215. [Abstract] [Full Text] [PDF]
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R. F. Redberg, G. T. Kondos, A. Sevrukov, S. S. Devries, E. V. Chomka, J. A. Hoff, M. L. Daviglus, D. B. Garside, and K. Liu Coronary Artery Calcium and Cardiac Events * Response Circulation, December 23, 2003; 108 (25): e167 - e168. [Full Text] [PDF]
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P. G. O'Malley and A. J. Taylor Prognostic Value of Coronary Artery Calcification Circulation, December 23, 2003; 108 (25): e169 - e169. [Full Text] [PDF]
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 J. J. Fenton and R. A. Deyo Patient Self-Referral for Radiologic Screening Tests: Clinical and Ethical Concerns J Am Board Fam Med, November 1, 2003; 16(6): 494 - 501. [Abstract] [Full Text] [PDF]
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R. Vliegenthart, B. Song, A. Hofman, J. C. M. Witteman, and M. Oudkerk Coronary Calcification at Electron-Beam CT: Effect of Section Thickness on Calcium Scoring in Vitro and in Vivo Radiology, November 1, 2003; 229(2): 520 - 525. [Abstract] [Full Text] [PDF]
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L. R. Van Hoe, K. G. De Meerleer, P. Ph. Leyman, and P. K. Vanhoenacker Coronary Artery Calcium Scoring Using ECG-Gated Multidetector CT: Effect of Individually Optimized Image-Reconstruction Windows on Image Quality and Measurement Reproducibility Am. J. Roentgenol., October 1, 2003; 181(4): 1093 - 1100. [Abstract] [Full Text] [PDF]
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 T. M. Doherty, K. Asotra, L. A. Fitzpatrick, J.-H. Qiao, D. J. Wilkin, R. C. Detrano, C. R. Dunstan, P. K. Shah, and T. B. Rajavashisth Calcification in atherosclerosis: Bone biology and chronic inflammation at the arterial crossroads PNAS, September 30, 2003; 100(20): 11201 - 11206. |