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Original Investigation |

Calcium Density of Coronary Artery Plaque and Risk of Incident Cardiovascular Events FREE

Michael H. Criqui, MD, MPH1,2; Julie O. Denenberg, MA1; Joachim H. Ix, MD, MAS2; Robyn L. McClelland, PhD3; Christina L. Wassel, PhD4; Dena E. Rifkin, MD, MS2; Jeffrey J. Carr, MD, MS5; Matthew J. Budoff, MD6; Matthew A. Allison, MD, MPH1
[+] Author Affiliations
1Department of Family and Preventive Medicine, University of California, San Diego, La Jolla
2Department of Medicine, University of California, San Diego, La Jolla
3Department of Biostatistics, University of Washington, Seattle
4Department of Epidemiology, University of Pittsburgh, Pittsburgh, Pennsylvania
5Department of Radiology and Radiological Sciences, Vanderbilt University, Nashville, Tennessee
6Division of Cardiology, Los Angeles Biomedical Research Institute at Harbor-UCLA Medical Center, Los Angeles
JAMA. 2014;311(3):271-278. doi:10.1001/jama.2013.282535.
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Published online

Importance  Coronary artery calcium (CAC), measured by computed tomography (CT), has strong predictive value for incident cardiovascular disease (CVD) events. The standard CAC score is the Agatston, which is weighted upward for greater calcium density. However, some data suggest increased plaque calcium density may be protective for CVD.

Objective  To determine the independent associations of CAC volume and CAC density with incident CVD events.

Design, Setting, and Participants  Multicenter, prospective observational MESA study (Multi-Ethnic Study of Atherosclerosis), conducted at 6 US field centers of 3398 men and women from 4 race/ethnicity groups; non-Hispanic white, African American, Hispanic, and Chinese. Participants were aged 45-84 years, free of known CVD at baseline, had CAC greater than 0 on their baseline CT, and were followed up through October 2010.

Main Outcomes and Measures  Incident coronary heart disease (CHD) and all CVD events

Results  During a median of 7.6 years of follow-up, there were 175 CHD events and an additional 90 other CVD events for a total of 265 CVD events. With both lnCAC volume and CAC density scores in the same multivariable model, the lnCAC volume score showed an independent association with incident CHD, with a hazard ratio (HR) of 1.81 (95% CI, 1.47-2.23) per standard deviation (SD = 1.6) increase, absolute risk increase 6.1 per 1000 person-years, and for CVD an HR of 1.68 (95% CI, 1.42-1.98) per SD increase, absolute risk increase 7.9 per 1000 person-years. Conversely, the CAC density score showed an independent inverse association, with an HR of 0.73 (95% CI, 0.58-0.91) per SD (SD = 0.7) increase for CHD, absolute risk decrease 5.5 per 1000 person-years, and an HR of 0.71 (95% CI, 0.60-0.85) per SD increase for CVD, absolute risk decrease 8.2 per 1000 person years. Area under the receiver operating characteristic curve analyses showed significantly improved risk prediction with the addition of the density score to a model containing the volume score for both CHD and CVD. In the intermediate CVD risk group, the area under the curve for CVD increased from 0.53 (95% CI, 0.48-0.59) to 0.59 (95% CI, 0.54-0.64), P = .02.

Conclusions and Relevance  CAC volume was positively and independently associated with CHD and CVD risk. At any level of CAC volume, CAC density was inversely and significantly associated with CHD and CVD risk. The role of CAC density should be considered when evaluating current CAC scoring systems.

Figures in this Article

The standard methodology for scoring the amount of coronary artery calcium (CAC) from computed tomography (CT) scans is the Agatston method,1 and software that applies this semiautomated scoring system is widely used. The Agatston score is the product of the within-slice CAC plaque area and a plaque-specific density factor of 1, 2, 3, or 4, summed for all cardiac CT slices. The density factor reflects increasing categories of Hounsfield units (Hu). Thus, the Agatston score is weighted upward for greater CAC density.

Despite the strong predictive value of CAC for cardiovascular disease (CVD),2 there has been little rigorous comparison of what specific measure of CAC is most predictive, or whether upweighting a CAC score for greater density is appropriate.

An increasing body of evidence suggests that greater calcium density in plaques is associated with decreased CVD risk. Several studies comparing acute heart disease with stable coronary heart disease (CHD) have shown denser calcified plaque in stable CHD.37 A recent study of CT angiography showed that the majority of individuals with CAC had calcified plaques, and that the CHD risk in this group was markedly lower than in patients with some or all plaques uncalcified.8 Randomized trials of statin therapy have reported a consistent tendency for the statin group to have more CAC progression,9,10 consistent with stabilizing plaque.11

To test the role of CAC density in CVD risk prediction, we used data from the MESA trial (Multi-Ethnic Study of Atherosclerosis) and derived a formula using the individual Agatston scores and the volume scores to create a per-participant CAC density score. We then evaluated the independent associations of the volume and density scores with risk of incident CVD events. We hypothesized that at any given volume of CAC plaque burden, greater CAC density would be inversely related to incident CVD events.

Study Participants

MESA is a prospective cohort study of individuals aged 45 to 84 years, who were free of known clinical CVD at baseline. First examinations were conducted from 2000 to 2002 at 6 field centers: Baltimore, MD; Chicago, IL; Los Angeles, CA; New York, NY; St Paul, MN; and Winston-Salem, NC. The study design, recruitment methods, examination components, and data collection have been described12 and are available at http://www.mesa-nhlbi.org. MESA was approved by each of the institutional review boards at the participating centers, and all participants provided written informed consent.

Risk Factor Assessment

Standardized questionnaires were used to obtain information about participant demographics, medical history, and medication usage including current blood pressure and cholesterol-lowering medications. Resting blood pressure was measured in a standardized manner. Blood measures obtained after a 12-hour fast included glucose, total cholesterol, and high-density lipoprotein cholesterol (HDL-C). Diabetes was defined as a fasting blood glucose level greater than 125 mg/dL or use of hypoglycemic medications. Smoking status was classified as never, former, or current use of cigarettes. The variables of age, sex, total cholesterol, HDL-C, systolic blood pressure, antihypertensive medication use, current smoking, and diabetes status were used to calculate the general Framingham Risk Score (FRS), which is a validated score for predicting CHD and other CVD events.13

CAC Measurement

The methodology for acquisition and interpretation of the CAC scans, as well as the reproducibility of the readings, has been reported previously.14 Scanning centers assessed CAC using either an electron-beam CT scanner (Chicago, Los Angeles, and New York) or a multidetector CT system (Baltimore, St Paul, and Winston-Salem). All scanners were cardiac gated. Slice thickness was 3 mm using the electron-beam CT scanners and 2.5 mm using the multidetector CT scanners. Each participant was scanned twice for CAC, which was measured during the same examination using the same site-specific scanners. CAC scans were read centrally at the MESA CT Reading Center and were brightness adjusted using a standard phantom to control for any scanner differences.15 In addition to the Agatston score, a volume score was also calculated.16 To qualify as a calcified plaque using CAC scoring, the plaque calcium density, measured in Hounsfield units, must be 130 Hu or higher. The Agatston scoring method for CAC measures each such discrete plaque area in square millimeters. Each discrete plaque area is then multiplied by 1, 2, 3, or 4, depending on the highest density measurement in Hu anywhere in the plaque. Plaques with a maximum density of 130 to 199 Hu are multiplied by 1, those with 200 to 299 Hu by 2, those with 300 to 399 by 3, and those with 400 Hu or greater by 4. These plaque-specific scores are then summed for all slices of the heart to give the Agatston score, which is thus an area score upweighted for increased plaque density. The participants received their Agatston score, were told that the presence of CAC represented hardening of the coronary arteries, and told of their amount of CAC (less than average, average, or greater than average).

The MESA database does not contain the individual area score for each participant. Thus, to calculate the individual area scores, the volume scores in cubic millimeters were divided by the appropriate slice thickness, 2.5 mm or 3 mm, resulting in the area score in square millimeters. The Agatston score was then divided by the area score and the quotient was the average CAC density score for each participant. The formula was: Agatston score/area score = density score. The density score thus ranged from 1 to 4 and reflected the average plaque density for all CT slices from that participant.

CVD and Mortality Follow-up

Follow-up began at the time of the baseline examination and continued until the first CVD event, death, loss to follow-up, or the ninth follow-up call, which took place between May 2008 and October 2010. Details of CVD event ascertainment have been published.17 For this report, we analyzed 2 separate end points: (1) hard CHD, defined as myocardial infarction, resuscitated cardiac arrest, or CHD death; and (2) hard CVD, defined as hard CHD, stroke, or stroke death. Softer end points such as angina and revascularization were not included in these analyses since such outcomes could have been biased by participants’ knowledge of their CAC scores at baseline.

Statistical Analysis

Spearman correlation coefficients were used to evaluate the degree of association between the Agatston, volume, area, and density scores. Cox proportional hazard regression was used to estimate hazard ratios (HRs) for time to CHD and CVD events for both the volume score and the density score, adjusting for covariates. Cox models were run adjusting initially for age, sex, and ethnicity, and then additionally for the general FRS, which includes age, HDL-C, total cholesterol, systolic blood pressure stratified by treatment, smoking, and diabetes. In addition, we included a term for statin use at baseline. We included race/ethnicity in the model since MESA had a diverse cohort. We defined statistical significance as a 2-tailed α of less than 0.05. We performed tests for nonproportional hazards using Schoenfeld residuals. All results were nonsignificant.18

The incremental value of the CAC density score for the prediction of CVD events was evaluated by the increase in the area under the receiver operating characteristic curve (AUC [area under the curve]).19 Analyses were performed using STATA version 10.1 (StataCorp, LP) statistical software and SAS version 9.2 (SAS Institute, Inc). The natural logarithm (ln) of the Agatston, area, and volume scores were used since previous analyses in MESA have shown log linear relationships between CAC and CVD risk.20

Because this analysis was focused on the predictive value of different components of calcified plaques, of necessity we restricted analyses to the 3398 MESA participants (1964 [58%] men and 1434 [42%] women) with a CAC score greater than zero at baseline. The MESA has previously reported that individuals without detectable CAC had very low rates of incident CHD.21 The race/ethnicity distribution was 44% non-Hispanic white, 24% African American, 20% Hispanic, and 12% Chinese. We excluded 4 individuals who were lost to follow-up, leaving 3394 for analysis. The median follow-up was 7.6 years with a mean of 7.0 years. There were a total of 23 204 person-years of follow-up.

Table 1 shows CVD risk factors, CAC scores, and CHD and CVD outcomes in the study cohort by quartile of volume score. The mean age was 66 years. Age, proportion of men, and proportion of non-Hispanic white participants increased across volume scores, as did blood pressure treatment, systolic blood pressure, diabetes, statin use, and the general FRS. The volume score, by definition, is between 2.5 and 3 times the area score, since it is the area score multiplied by the CT slice thickness. The density score was lower in the first quartile of volume but similar in the upper 3 quartiles. During follow-up, there were 175 CHD events and 90 other CVD events totalling 265 CVD events. CHD and CVD rates increased monotonically across the 4 quartiles of volume score.

Table Graphic Jump LocationTable 1.  CVD Risk Factors, CAC Measurements, and CVD Outcomes in Men and Women in MESA With Nonzero CAC Scores, by Quartile of CAC Volume Score

Table 2 shows the same data by quartile of density score. The density score can theoretically range between 1 and 4. The actual range was quite close, 0.83 to 4.00, varying slightly from expected due to minor software differences for measuring the Agatston and volume scores. The fourth quartile of density showed the lowest proportion of non-Hispanic white participants and the highest percentage of Chinese. Age and the general FRS were lower in the first quartile of density, but similar across quartiles 2, 3, and 4. Agatston, area, and volume scores increased across quartiles 1 2, and 3 of density, but were slightly lower in the fourth quartile compared with the third. CHD and CVD rates increased across the first 3 quartiles of density but were much lower in quartile 4.

Table Graphic Jump LocationTable 2.  CVD Risk Factors, CAC Measurements, and CVD Outcomes in Men and Women in MESA With Nonzero CAC Scores, by Quartile of CAC Density Score

Table 3 shows a Spearman correlation matrix for the various CAC scores. The Agatston, volume, and area scores were all highly correlated (coefficient for bivariate analysis, r >0.99). The density score was positively correlated with the other 3 scores, but only moderately, with correlations of 0.623, 0.560, and 0.539 for the Agatston, volume, and area scores respectively. The somewhat higher correlation of the density score with the Agatston score reflects the density upweighting of the Agatston score.

Table Graphic Jump LocationTable 3.  Spearman Correlation Coefficients for 4 CAC Scoresa

Table 4 shows the associations of the 4 CAC scores individually (lnAgatston, lnvolume, lnarea, and density) for both CHD and CVD, using Cox proportional hazard models with the hazard ratios (HRs) reflecting 1 standard deviation of the independent variable. The standard deviations for lnAgatston, lnvolume, lnarea, and density were 1.8, 1.6, 1.6, and 0.7 respectively. P values and 95% CIs are shown. The values at the top of the table are adjusted for age, sex, and race/ethnicity, and at the bottom of the table are fully adjusted for race/ethnicity, the general FRS, and statin use. One person was missing data on statin use, leaving 3393 for these analyses. In the age, sex, and ethnicity-adjusted models, the Agatston, volume, and area scores all showed similar and significant associations for both outcomes. The similarity for the associations reflects the high correlation (r >0.99) of these 3 CAC scores. The associations were somewhat stronger for CHD than for CVD. The density score showed no association for CHD or for CVD. When additionally adjusted for the general FRS and statin use, associations were modestly attenuated for the Agatston, volume, and area scores. The associations for the density score were essentially unchanged.

Table Graphic Jump LocationTable 4.  Adjusted HRs for 4 Separate CAC Scores for Hard CHD and Hard CVD

Table 5 shows the results for fully adjusted Cox models with the volume score and density score placed in the same models, and with the HRs again reflecting a 1 standard deviation difference. With the density score included in the models, the HRs for the volume score increased for both end points from 1.52 (95% CI, 1.29-1.80) to 1.81 (95% CI, 1.47-2.23), absolute risk increase 6.1 per 1000 person-years for CHD and from 1.38 (95% CI, 1.21-1.58) to 1.68 (95% CI, 1.42-1.98), absolute risk increase 7.9 per 1000 person-years, for CVD, and remained significant. The density score became significantly and inversely associated with CHD (HR, 0.73; 95% CI, 0.58-0.91), absolute risk decrease 5.5 per 1000 person-years, and with CVD (HR, 0.71; 95% CI, 0.60-0.85), absolute risk decrease 8.2 per 1000 person-years. Thus, the strength of the volume score was increased when accounting for the density score in the model, and at any given CAC volume score, a 1 standard deviation higher CAC density score was associated with a significantly lower risk for CHD and CVD. Additional models including interaction terms for the density score with sex and race/ethnicity revealed no significant interactions. The P values for interaction for CHD and CVD respectively were 0.50 and 0.55 for sex and 0.71 and 0.59 for race/ethnicity. Additional stratified analyses showed an inverse density association at both high and low CAC volume levels, although somewhat more so at lower volume levels. However, CAC volume × CAC density interaction terms were not significant for either CHD (P = .80) or CVD (P = .95). The general FRS was independently associated with both CHD and CVD. Statin use was inversely but nonsignificantly associated with both CHD and CVD. None of the race/ethnicity associations were significant.

Table Graphic Jump LocationTable 5.  Multivariable HRs for the ln(Volume Score), Density Score, the General FRS, Race/Ethnicity, and Statin Use for CHD and CVD

The Figure shows the associations of volume score and density score in quartiles with CHD (panel A) and CVD (panel B). Data are adjusted for the general FRS, race/ethnicity, and statin use. Volume score quartiles are adjusted for the density score and the density score quartiles for the ln(volume score). The cut points for the volume score quartiles were 24.5, 85.2 and 273.4 mm3, and the cut points for the density score quartiles were 2.23, 2.80, and 3.18 Hu category units. HRs with 95% CIs are shown, plotted on a log scale. There was a stepwise increase in CHD risk by quartile of volume score, with HRs of 1.99 (95% CI, 1.08-3.67), 3.10 (95% CI, 1.68-5.73), and 4.50 (95% CI, 2.35-8.61) compared with the first quartile. There was a stepwise decrease in risk across the density score quartiles, with HRs of 0.89 (95% CI, 0.53-1.47), 0.79 (95% CI, 0.45-1.37), and 0.50 (95% CI, 0.27-0.90). For CVD, the left side of panel B shows a similar stepwise increase in CVD risk by volume score quartiles, with HRs of 1.51 (95% CI, 0.95-2.39), 2.27 (95% CI, 1.43-3.62), and 3.36 (95% CI, 2.05-5.51). For the density score quartiles, a similar stepwise decrease is shown with HRs of 0.76 (95% CI, 0.51-1.13), 0.66 (95% CI, 0.43-1.02), and 0.47 (95% CI, 0.30-0.75).

Place holder to copy figure label and caption
Figure.
Adjusted Hazard Ratios of Volume and Density Score Quartiles for Coronary Heart Disease and Cardiovascular Disease

Hazard ratios (HRs) for volume score quartiles are adjusted for density score, race/ethnicity, statin use, and general Framingham Risk Score (FRS). HRs for density score quartiles are adjusted for natural logarithm volume score, race/ethnicity, statin use, and general FRS. Error bars indicate 95% CIs. Hu indicates Hounsfield unit.

Graphic Jump Location

Table 6 shows the AUC analyses. The base model contained the general FRS, race/ethnicity, and statin use. For CHD, the AUC for the base model was 0.668 (95% CI, 0.629-0.726), which increased to 0.700 (95% CI, 0.664-0.735; P = .01) by adding the volume score, and to 0.711 (95% CI, 0.675-0.746; P = .05) with further addition of the density score. For CVD, the AUC for the base model was 0.669 (95% CI, 0.637-0.700), which increased to 0.691 (95% CI, 0.661-0.721; P = .01) by adding the volume score, and to 0.704 (95% CI, 0.675-0.734; P = .02) by further addition of the density score. In comparison, addition of the Agatston score to the base model improved the AUC to only 0.696 (95% CI, 0.660-0.732; P = .02) for CHD and only 0.688 for CVD (95% CI, 0.658-0.718; P = .02). Additional AUC analyses were performed separately in annual CVD risk groups: low (0%-0.99%,), medium (1.0%-1.99%), and high (≥2.0%). For CHD, numbers were insufficient for these analyses. For CVD, the AUC increase with the density score added did not provide significant additional discrimination in either the low (P = .41; n = 1859) or high (P = .74; n = 501) risk groups. For the intermediate-risk group (n = 1021), where incremental risk prediction may be most clinically relevant, the AUC for CVD increased from 0.532 (95% CI, 0.477-0.587) to 0.590 (95% CI, 0.538-0.642; P = .017), with addition of the density score. In the intermediate-risk group 908 participants did not have CVD events and 113 participants did. In those with events, addition of the density score correctly reclassified 179 individuals to the low-risk group and incorrectly classified 85 individuals to the high-risk group, for a net correct reclassification of 94 individuals (10.4%). In participants who had CVD events, addition of the density score correctly classified 14 to the high-risk group and incorrectly classified 10 of them to the low-risk group, for a net correct reclassification of 4 individuals (3.5%).

Table Graphic Jump LocationTable 6.  Areas Under the ROC Curve for the Base Model and Various CAC Measures

Measurement of CAC has consistently proven to be the best subclinical CVD measure in terms of improving CHD risk prediction.2,Table 4 shows that there are only minor differences in CHD and CVD risk prediction with different CAC scoring algorithms due to the very high correlation of the Agatston score with other CAC scores (Table 3). However, the data here suggest that the Agatston area or volume scores alone are not optimal measures to use in CVD risk prediction since the demonstrated inverse association with density also needs consideration.

Measurement of CAC appears particularly useful in individuals at intermediate CVD risk, generally considered to be in the range of 1.0% to 2.0% per year, in whom treatment decisions may be influenced by improved CVD risk prediction based on measuring CAC.2 In these data, stratified analysis by CVD risk group showed that the largest improvement in the AUC with the addition of the density score was in the intermediate-risk group.

The data presented here—that CAC density was inversely related to CVD events at a given CAC volume and that CAC volume was more predictive when adjusted for CAC density—are novel observations. Our data are consistent with numerous prior observations including the modest correlation between CAC and coronary stenoses,1,22 autopsy data showing that although there was a good correlation between calcium area (not weighted for density) and plaque area, there was a poor correlation between residual histologic lumen area and calcium area,23 and studies showing that patients with stable angina were more likely to have calcified and less likely to have echolucent plaques than patients with unstable angina.37 Also consistent with our data are clinical trials of statin therapy vs placebo reporting that CAC progression using the Agatston score was greater in the statin group than in the placebo group.9,10 Statins appear to have their salutary effects on CVD risk by reducing the lipid core in unstable plaque,11 and statin therapy may increase calcium density in such plaques, along with a more favorable prognosis. Similarly, a recent report from MESA showed that favorable changes in LDL-C were correlated with a significant increase in CAC progression.24 A recent report of 4425 referred patients evaluated with both CT for CAC and CT angiography showed that 1021 had only calcified plaque, 183 had only noncalcified plaque, and 685 had both calcified and noncalcified plaque. The incidence of CVD events after a median follow-up of 3 years in these 3 groups was 5.5%, 22.7%, and 37.7%, respectively.8 These results suggest that higher calcium density of plaques may be protective.

Results of other CAC scoring systems have been reported, showing predictive capability similar to or slightly better than the Agatston score.2528 Importantly and to our knowledge, no CAC score has previously evaluated the relationship of plaque calcium density with CVD risk.

CAC is present in more than half of middle-aged US residents and by age 70, the probability of CAC exceeds 90%.2931 Many patients have had serial CAC scans to evaluate progression. The use of the Agatston score in assessing CAC progression is problematic since an increase in CAC could be due to an increase in volume, an increase in density, or both.

Our study has limitations. Although the data suggest that CAC density at a given CAC volume is independently and inversely associated with risk, and thus should to be assessed along with plaque volume, the assessment of density was crude, using an arbitrary 4-point scale rather than a continuous Hu scale. The highest score (4) was for densities of 400 Hu or greater when in fact, CAC density can be greater than 3000 Hu. In addition, for each plaque, the maximum density noted (in Hounsfield units) was used to define the multiple, and thus some plaques that were primarily low density, and possibly at increased risk, were rated as maximum density. However, such misclassification would have produced an underestimate of the inverse association with denser CAC and so this association is likely underestimated in our data. Participants were told their CAC scores at baseline, which could have led to increased intervention in those with high CAC scores. However, we minimized any ascertainment bias by using hard CHD and hard CVD as end points for analysis. The AUC values observed for CAC in this study are modestly lower than previous reports because of the population considered here, namely participants with CAC greater than 0. The distinction between individuals with and without CAC is a large component of the predictive ability of CAC and thus, exclusion of individuals with CAC equal to 0 results in lower predictive measures. However, the importance of plaque density is clearly only a relevant concept for individuals with some measured plaque and thus, our analysis was restricted to this population.

In conclusion, CAC volume was positively and independently associated with CHD and CVD risk. At any level of CAC volume, CAC density was inversely and significantly associated with CHD and CVD risk. The role of CAC density should be considered when evaluating current CAC scoring systems.

Corresponding Author: Michael H. Criqui, MD, MPH, Department of Family and Preventive Medicine, University of California, San Diego, 9500 Gilman Dr, MC 0607, La Jolla, CA 92093-0607 (mcriqui@ucsd.edu).

Published Online: November 18, 2013. doi:10.1001/jama.2013.282535.

Author Contributions: Dr Criqui had full access to all of the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.

Study concept and design: Criqui, Denenberg, Allison, Wassel, Ix.

Acquisition of data: Criqui, Carr, Budoff.

Analysis and interpretation of data: Denenberg, Ix, McClelland, Wassel, Rifkin, Carr, Budoff, Allison, Criqui.

Drafting of the manuscript: Criqui.

Critical revision of the manuscript for important intellectual content: Ix, McClelland, Wassel, Rifkin, Carr, Budoff, Allison, Criqui.

Statistical analysis: Denenberg, McClelland, Wassel.

Obtained funding: Carr, Criqui, Budoff.

Administrative, technical, or material support: Carr, Criqui, Denenberg, McClelland, Budoff.

Study supervision: Carr, Budoff, Criqui, McClelland.

Conflict of Interest Disclosures: Dr Criqui reports receipt of a grant to his institution from the National Institutes of Health/National Heart, Lung, and Blood Institute (NIH/NHLBI). Ms Denenberg reports receipt of a grant to her institution from NHLBI. Dr Ix reports receipt of a grant or pending grant from NIH and NHLBI, and support for travel and lectures at scientific conferences from Shire. Dr McClelland reports receipt of a grant to her institution and of support for travel to meetings for the Multi-Ethnic Study of Atherosclerosis (MESA) steering committee from NHLBI/NIH. Dr Rifkin reports receipt of K23 support from a grant from the National Institute of Diabetes and Digestive and Kidney Diseases. Dr Carr reports receipt of a grant to his institution from NIH/NHLBI. Dr Budoff reports receipt of a consulting fee or honorarium from GE. Drs Wassel and Allison report no disclosures. All authors have completed and submitted the ICMJE Form for Disclosure of Potential Conflicts of Interest.

Funding/Support: The MESA study was supported by contracts N01-HC-95159, N01-HC-95160, N01-HC-95161, N01-HC-95162, N01-HC-95163, N01-HC-95164, N01-HC-95165, and N01-HC-95169 from the NHLBI.

Role of the Sponsors: The NHLBI participated in the design and conduct of MESA, but did not participate in the analysis or interpretation of the data in the manuscript. Members of the NHLBI staff saw an oral slide presentation of the manuscript presented prior to submission. The NHLBI did not review the manuscript, participate in the decision to submit it, or approve it prior to publication.

Additional Contributions: We thank the other investigators, the staff, and the participants of the MESA study for their valuable contributions. A full list of participating MESA investigators and institutions can be found at http://www.mesa-nhlbi.org. We thank Nova Rogers, BA, for assisting in manuscript preparation. Ms Rogers was not additionally compensated for completion of work associated with this article.

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Inoue  K, Motoyama  S, Sarai  M,  et al.  Serial coronary CT angiography-verified changes in plaque characteristics as an end point. JACC Cardiovasc Imaging. 2010;3(7):691-698.
PubMed   |  Link to Article
Bild  DE, Bluemke  DA, Burke  GL,  et al.  Multi-ethnic study of atherosclerosis: objectives and design. Am J Epidemiol. 2002;156(9):871-881.
PubMed   |  Link to Article
D’Agostino  RB  Sr, Vasan  RS, Pencina  MJ,  et al.  General cardiovascular risk profile for use in primary care: the Framingham Heart Study. Circulation. 2008;117(6):743-753.
PubMed   |  Link to Article
Carr  JJ, Nelson  JC, Wong  ND,  et al.  Calcified coronary artery plaque measurement with cardiac CT in population-based studies. Radiology. 2005;234(1):35-43.
PubMed   |  Link to Article
Nelson  JC, Kronmal  RA, Carr  JJ,  et al.  Measuring coronary calcium on CT images adjusted for attenuation differences. Radiology. 2005;235(2):403-414.
PubMed   |  Link to Article
Detrano  RC, Anderson  M, Nelson  J,  et al.  Coronary calcium measurements: effect of CT scanner type and calcium measure on rescan reproducibility—MESA study. Radiology. 2005;236(2):477-484.
PubMed   |  Link to Article
Folsom  AR, Kronmal  RA, Detrano  RC,  et al.  Coronary artery calcification compared with carotid intima-media thickness in the prediction of cardiovascular disease incidence. Arch Intern Med. 2008;168(12):1333-1339.
PubMed   |  Link to Article
Grambsch  P, Therneau  T.  Proportional hazards tests and diagnostics based on weighted residuals. Biometrika. 1994;81(3):515-526. doi:10.1093/biomet/81.3.515
Link to Article
Pencina  MJ, D’Agostino  RB  Sr, D’Agostino  RB  Jr, Vasan  RS.  Evaluating the added predictive ability of a new marker: from area under the ROC curve to reclassification and beyond. Stat Med. 2008;27(2):157-172.
PubMed   |  Link to Article
Detrano  R, Guerci  AD, Carr  JJ,  et al.  Coronary calcium as a predictor of coronary events in four racial or ethnic groups. N Engl J Med. 2008;358(13):1336-1345.
PubMed   |  Link to Article
Budoff  MJ, McClelland  RL, Nasir  K,  et al.  Cardiovascular events with absent or minimal coronary calcification. Am Heart J. 2009;158(4):554-561.
PubMed   |  Link to Article
Detrano  R, Hsiai  T, Wang  S,  et al.  Prognostic value of coronary calcification and angiographic stenoses in patients undergoing coronary angiography. J Am Coll Cardiol. 1996;27(2):285-290.
PubMed   |  Link to Article
Sangiorgi  G, Rumberger  JA, Severson  A,  et al.  Arterial calcification and not lumen stenosis is highly correlated with atherosclerotic plaque burden in humans. J Am Coll Cardiol. 1998;31(1):126-133.
PubMed   |  Link to Article
Arguelles W, Llabre MM, Penedo FJ, et al. Does change in cardiometabolic risk factors relate to change in coronary artery calcification? findings from the Multi-Ethnic Study of Atherosclerosis (MESA) [AHA abstract 9110]. Circulation. 2011;124:A9110. http://circ.ahajournals.org/cgi/content/meeting_abstract/124/21_MeetingAbstracts/A9110?sid=80cfeb09-585f-401b-9cdc-5467292b4cc0. Accessed November 13, 2013.
Brown  ER, Kronmal  RA, Bluemke  DA,  et al.  Coronary calcium coverage score: determination, correlates, and predictive accuracy in the Multi-Ethnic Study of Atherosclerosis. Radiology. 2008;247(3):669-675.
PubMed   |  Link to Article
Williams  M, Shaw  LJ, Raggi  P,  et al.  Prognostic value of number and site of calcified coronary lesions compared with the total score. JACC Cardiovasc Imaging. 2008;1(1):61-69.
PubMed   |  Link to Article
Shemesh  J, Henschke  CI, Shaham  D,  et al.  Ordinal scoring of coronary artery calcifications on low-dose CT scans of the chest is predictive of death from cardiovascular disease. Radiology. 2010;257(2):541-548.
PubMed   |  Link to Article
Liang  CJ, Budoff  MJ, Kaufman  JD, Kronmal  RA, Brown  ER.  An alternative method for quantifying coronary artery calcification. BMC Med Imaging. 2012;12:14.
PubMed   |  Link to Article
Allison  MA, Criqui  MH, Wright  CM.  Patterns and risk factors for systemic calcified atherosclerosis. Arterioscler Thromb Vasc Biol. 2004;24(2):331-336.
PubMed   |  Link to Article
McClelland  RL, Chung  H, Detrano  R, Post  W, Kronmal  RA.  Distribution of coronary artery calcium by race, gender, and age. Circulation. 2006;113(1):30-37.
PubMed   |  Link to Article
Hoffmann  U, Massaro  JM, Fox  CS, Manders  E, O’Donnell  CJ.  Defining normal distributions of coronary artery calcium in women and men (from the Framingham Heart Study). Am J Cardiol. 2008;102(9):1136-1141, e1.
PubMed   |  Link to Article

Figures

Place holder to copy figure label and caption
Figure.
Adjusted Hazard Ratios of Volume and Density Score Quartiles for Coronary Heart Disease and Cardiovascular Disease

Hazard ratios (HRs) for volume score quartiles are adjusted for density score, race/ethnicity, statin use, and general Framingham Risk Score (FRS). HRs for density score quartiles are adjusted for natural logarithm volume score, race/ethnicity, statin use, and general FRS. Error bars indicate 95% CIs. Hu indicates Hounsfield unit.

Graphic Jump Location

Tables

Table Graphic Jump LocationTable 1.  CVD Risk Factors, CAC Measurements, and CVD Outcomes in Men and Women in MESA With Nonzero CAC Scores, by Quartile of CAC Volume Score
Table Graphic Jump LocationTable 2.  CVD Risk Factors, CAC Measurements, and CVD Outcomes in Men and Women in MESA With Nonzero CAC Scores, by Quartile of CAC Density Score
Table Graphic Jump LocationTable 3.  Spearman Correlation Coefficients for 4 CAC Scoresa
Table Graphic Jump LocationTable 4.  Adjusted HRs for 4 Separate CAC Scores for Hard CHD and Hard CVD
Table Graphic Jump LocationTable 5.  Multivariable HRs for the ln(Volume Score), Density Score, the General FRS, Race/Ethnicity, and Statin Use for CHD and CVD
Table Graphic Jump LocationTable 6.  Areas Under the ROC Curve for the Base Model and Various CAC Measures

References

Agatston  AS, Janowitz  WR, Hildner  FJ, Zusmer  NR, Viamonte  M  Jr, Detrano  R.  Quantification of coronary artery calcium using ultrafast computed tomography. J Am Coll Cardiol. 1990;15(4):827-832.
PubMed   |  Link to Article
Yeboah  J, McClelland  RL, Polonsky  TS,  et al.  Comparison of novel risk markers for improvement in cardiovascular risk assessment in intermediate-risk individuals. JAMA. 2012;308(8):788-795.
PubMed   |  Link to Article
Hodgson  JM, Reddy  KG, Suneja  R, Nair  RN, Lesnefsky  EJ, Sheehan  HM.  Intracoronary ultrasound imaging. J Am Coll Cardiol. 1993;21(1):35-44.
PubMed   |  Link to Article
Schoenhagen  P, Ziada  KM, Kapadia  SR, Crowe  TD, Nissen  SE, Tuzcu  EM.  Extent and direction of arterial remodeling in stable versus unstable coronary syndromes. Circulation. 2000;101(6):598-603.
PubMed   |  Link to Article
Leber  AW, Knez  A, White  CW,  et al.  Composition of coronary atherosclerotic plaques in patients with acute myocardial infarction and stable angina pectoris determined by contrast-enhanced multislice computed tomography. Am J Cardiol. 2003;91(6):714-718.
PubMed   |  Link to Article
Shemesh  J, Apter  S, Itzchak  Y, Motro  M.  Coronary calcification compared in patients with acute versus in those with chronic coronary events by using dual-sector spiral CT. Radiology. 2003;226(2):483-488.
PubMed   |  Link to Article
Ehara  S, Kobayashi  Y, Yoshiyama  M,  et al.  Spotty calcification typifies the culprit plaque in patients with acute myocardial infarction. Circulation. 2004;110(22):3424-3429.
PubMed   |  Link to Article
Hou  ZH, Lu  B, Gao  Y,  et al.  Prognostic value of coronary CT angiography and calcium score for major adverse cardiac events in outpatients. JACC Cardiovasc Imaging. 2012;5(10):990-999.
PubMed   |  Link to Article
Houslay  ES, Cowell  SJ, Prescott  RJ,  et al.  Progressive coronary calcification despite intensive lipid-lowering treatment. Heart. 2006;92(9):1207-1212.
PubMed   |  Link to Article
Terry  JG, Carr  JJ, Kouba  EO,  et al.  Effect of simvastatin (80 mg) on coronary and abdominal aortic arterial calcium (from the coronary artery calcification treatment with zocor [CATZ] study). Am J Cardiol. 2007;99(12):1714-1717.
PubMed   |  Link to Article
Inoue  K, Motoyama  S, Sarai  M,  et al.  Serial coronary CT angiography-verified changes in plaque characteristics as an end point. JACC Cardiovasc Imaging. 2010;3(7):691-698.
PubMed   |  Link to Article
Bild  DE, Bluemke  DA, Burke  GL,  et al.  Multi-ethnic study of atherosclerosis: objectives and design. Am J Epidemiol. 2002;156(9):871-881.
PubMed   |  Link to Article
D’Agostino  RB  Sr, Vasan  RS, Pencina  MJ,  et al.  General cardiovascular risk profile for use in primary care: the Framingham Heart Study. Circulation. 2008;117(6):743-753.
PubMed   |  Link to Article
Carr  JJ, Nelson  JC, Wong  ND,  et al.  Calcified coronary artery plaque measurement with cardiac CT in population-based studies. Radiology. 2005;234(1):35-43.
PubMed   |  Link to Article
Nelson  JC, Kronmal  RA, Carr  JJ,  et al.  Measuring coronary calcium on CT images adjusted for attenuation differences. Radiology. 2005;235(2):403-414.
PubMed   |  Link to Article
Detrano  RC, Anderson  M, Nelson  J,  et al.  Coronary calcium measurements: effect of CT scanner type and calcium measure on rescan reproducibility—MESA study. Radiology. 2005;236(2):477-484.
PubMed   |  Link to Article
Folsom  AR, Kronmal  RA, Detrano  RC,  et al.  Coronary artery calcification compared with carotid intima-media thickness in the prediction of cardiovascular disease incidence. Arch Intern Med. 2008;168(12):1333-1339.
PubMed   |  Link to Article
Grambsch  P, Therneau  T.  Proportional hazards tests and diagnostics based on weighted residuals. Biometrika. 1994;81(3):515-526. doi:10.1093/biomet/81.3.515
Link to Article
Pencina  MJ, D’Agostino  RB  Sr, D’Agostino  RB  Jr, Vasan  RS.  Evaluating the added predictive ability of a new marker: from area under the ROC curve to reclassification and beyond. Stat Med. 2008;27(2):157-172.
PubMed   |  Link to Article
Detrano  R, Guerci  AD, Carr  JJ,  et al.  Coronary calcium as a predictor of coronary events in four racial or ethnic groups. N Engl J Med. 2008;358(13):1336-1345.
PubMed   |  Link to Article
Budoff  MJ, McClelland  RL, Nasir  K,  et al.  Cardiovascular events with absent or minimal coronary calcification. Am Heart J. 2009;158(4):554-561.
PubMed   |  Link to Article
Detrano  R, Hsiai  T, Wang  S,  et al.  Prognostic value of coronary calcification and angiographic stenoses in patients undergoing coronary angiography. J Am Coll Cardiol. 1996;27(2):285-290.
PubMed   |  Link to Article
Sangiorgi  G, Rumberger  JA, Severson  A,  et al.  Arterial calcification and not lumen stenosis is highly correlated with atherosclerotic plaque burden in humans. J Am Coll Cardiol. 1998;31(1):126-133.
PubMed   |  Link to Article
Arguelles W, Llabre MM, Penedo FJ, et al. Does change in cardiometabolic risk factors relate to change in coronary artery calcification? findings from the Multi-Ethnic Study of Atherosclerosis (MESA) [AHA abstract 9110]. Circulation. 2011;124:A9110. http://circ.ahajournals.org/cgi/content/meeting_abstract/124/21_MeetingAbstracts/A9110?sid=80cfeb09-585f-401b-9cdc-5467292b4cc0. Accessed November 13, 2013.
Brown  ER, Kronmal  RA, Bluemke  DA,  et al.  Coronary calcium coverage score: determination, correlates, and predictive accuracy in the Multi-Ethnic Study of Atherosclerosis. Radiology. 2008;247(3):669-675.
PubMed   |  Link to Article
Williams  M, Shaw  LJ, Raggi  P,  et al.  Prognostic value of number and site of calcified coronary lesions compared with the total score. JACC Cardiovasc Imaging. 2008;1(1):61-69.
PubMed   |  Link to Article
Shemesh  J, Henschke  CI, Shaham  D,  et al.  Ordinal scoring of coronary artery calcifications on low-dose CT scans of the chest is predictive of death from cardiovascular disease. Radiology. 2010;257(2):541-548.
PubMed   |  Link to Article
Liang  CJ, Budoff  MJ, Kaufman  JD, Kronmal  RA, Brown  ER.  An alternative method for quantifying coronary artery calcification. BMC Med Imaging. 2012;12:14.
PubMed   |  Link to Article
Allison  MA, Criqui  MH, Wright  CM.  Patterns and risk factors for systemic calcified atherosclerosis. Arterioscler Thromb Vasc Biol. 2004;24(2):331-336.
PubMed   |  Link to Article
McClelland  RL, Chung  H, Detrano  R, Post  W, Kronmal  RA.  Distribution of coronary artery calcium by race, gender, and age. Circulation. 2006;113(1):30-37.
PubMed   |  Link to Article
Hoffmann  U, Massaro  JM, Fox  CS, Manders  E, O’Donnell  CJ.  Defining normal distributions of coronary artery calcium in women and men (from the Framingham Heart Study). Am J Cardiol. 2008;102(9):1136-1141, e1.
PubMed   |  Link to Article
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