Author + information
- Received November 13, 2015
- Revision received March 2, 2016
- Accepted March 3, 2016
- Published online December 1, 2016.
- Michael J. Blaha, MD, MPHa,∗ (, )
- Matthew J. Budoff, MDb,
- Rajesh Tota-Maharaj, MDa,c,
- Zeina A. Dardari, MSa,
- Nathan D. Wong, PhDd,
- Richard A. Kronmal, PhDe,
- John Eng, MDf,
- Wendy S. Post, MD, MSa,
- Roger S. Blumenthal, MDa and
- Khurram Nasir, MD, MPHa,g
- aJohns Hopkins Ciccarone Center for the Prevention of Heart Disease, Baltimore, Maryland
- bDivision of Cardiology, Los Angeles Biomedical Research Institute at Harbor-UCLA, Torrance, California
- cDivision of Cardiology, Danbury Hospital, Danbury, Connecticut
- dDivision of Cardiology, University of California-Irvine, Irvine, California
- eDepartment of Biostatistics, University of Washington, Seattle, Washington
- fDepartment of Radiology, Johns Hopkins, Baltimore, Maryland
- gCenter for Prevention and Wellness Research, Baptist Health Medical Group, Miami Beach, Florida
- ↵∗Reprint requests and correspondence:
Dr. Michael J. Blaha, Blalock 524D1, Division of Cardiology, 600 North Wolfe Street, Baltimore, Maryland 21287.
Objectives The aim of this study was to investigate whether inclusion of simple measures of calcified plaque distribution might improve the ability of the traditional Agatston coronary artery calcium (CAC) score to predict cardiovascular events.
Background Agatston CAC scoring does not include information on the location and distributional pattern of detectable calcified plaque.
Methods We studied 3,262 (50%) individuals with baseline CAC >0 from MESA (Multi-Ethnic Study of Atherosclerosis). Multivessel CAC was defined by the number of coronary vessels with CAC (scored 1 to 4, including the left main). The “diffusivity index” was calculated as: 1 − (CAC in most affected vessel/total CAC), and was used to group participants into concentrated and diffuse CAC patterns. Multivariable Cox proportional hazards regression, area under the curve, and net reclassification improvement analyses were performed for both coronary heart disease (CHD) and cardiovascular disease (CVD) events to assess whether measures of regional CAC distribution add to the traditional Agatston CAC score.
Results Mean age of the population was 66 ± 10 years, with 42% women. Median follow-up was 10.0 (9.5 to 10.7) years and there were 368 CHD and 493 CVD events during follow-up. Considerable heterogeneity existed between CAC score group and number of vessels with CAC (p < 0.01). Addition of number of vessels with CAC significantly improved capacity to predict CHD and CVD events in survival analysis (hazard ratio: 1.9 to 3.5 for 4-vessel vs. 1-vessel CAC), area under the curve analysis (C-statistic improvement of 0.01 to 0.033), and net reclassification improvement analysis (category-less net reclassification improvement 0.10 to 0.45). Although a diffuse CAC pattern was associated with worse outcomes in participants with ≥2 vessels with CAC (hazard ratio: 1.33 to 1.41; p < 0.05), adding this variable to the Agatston CAC score and number of vessels with CAC did not further improve global risk prediction.
Conclusions The number of coronary arteries with calcified plaque, indicating increasingly “diffuse” multivessel subclinical atherosclerosis, adds significantly to the traditional Agatston CAC score for the prediction of CHD and CVD events.
Coronary artery calcium (CAC) scores derived from noncontrast cardiac computed tomography (CT) are one of the strongest individual predictors of adverse cardiovascular events (1). The association of CAC with cardiovascular disease (CVD) is thought to be driven by the strong correlation between detectable subintimal coronary calcium and total coronary atherosclerosis burden (1). Indeed, several studies have suggested a direct relationship between the quantity of calcium and the total amount of coronary atherosclerotic plaque (2,3).
CAC is usually scored by the method of Agatston et al. (4). The Agatston score is calculated as a summed product of the within-slice area of calcium multiplied by a weighting factor derived from the maximal CT attenuation of individual calcified lesions. Although elegant and simple, the Agatston score and other current CAC scoring algorithms (5–7) do not account for the distribution of CAC within the coronary tree. Therefore, 2 patients with the same CAC score may have significantly different patterns of CAC involvement (8). The implication of the heterogeneity in coronary atherosclerosis distribution within patients with similar CAC scores is not well known.
Given the large body of evidence supporting worse prognosis with diffuse coronary artery disease (9), we hypothesized that measures of diffuse CAC distribution might be associated with worse prognosis compared with identical CAC scores with a more concentrated pattern. To test this hypothesis, we sought to study the potential incremental prognostic value of adding simple measures of CAC distribution to the traditional Agatston score in a multiethnic population free of baseline CVD.
Study design and population
MESA (Multi-Ethnic Study of Atherosclerosis) is a multicenter population-based prospective cohort study aimed at describing the prevalence, progression, and clinical significance of subclinical atherosclerosis. In brief, MESA includes 6,814 men and women age 45 to 84 years from different ethnic origins (white, black, Hispanic, and Chinese) with no known baseline clinical CVD at the time of enrollment. Full details of the MESA study design and methods have been previously published (10). The study protocol was approved by each institutional review board, and all participants provided written informed consent.
As part of the baseline examination, staff members at each of the 6 centers collected information about cardiovascular risk factors, including medical history, smoking history, blood pressure measurement, anthropometric measurements, and laboratory data, as previously described (10). A central laboratory (University of Vermont, Burlington, Vermont) measured plasma glucose and high-sensitivity C-reactive protein, and levels of total and high-density lipoprotein cholesterol and triglycerides were measured after a 12-h fast at the Collaborative Studies Clinical Laboratory at Fairview-University Medical Center (Minneapolis, Minnesota).
Event ascertainment (follow-up)
Participants were followed for a median of 10.0 years (interquartile range: 9.5 to 10.7 years) for the first occurrence of a coronary heart disease (CHD) or CVD event. At intervals of 9 to 12 months, an interviewer contacted each participant or family member by telephone to inquire about interim revascularization, hospital admission, or death. To verify self-reported diagnoses, MESA obtained medical records for approximately 98% of hospital events and 95% of outpatient diagnoses. Two physicians from the MESA mortality and morbidity review committee independently classified events.
A CHD event was defined as myocardial infarction, death from CHD, resuscitated cardiac arrest definite angina, or revascularization if there was adjudicated preceding or concurrent angina. A CVD event was defined as a CHD event or stroke (not transient ischemic attack), cardiovascular death, or other atherosclerotic death. Full details of the MESA follow-up methods are available at the MESA website.
All MESA study participants underwent baseline measurement of CAC using noncontrast cardiac CT. Participants were scanned twice, and the score was reported as the average of the 2 scans. CAC scores were reported as the Agatston score, which is a single summary score reflecting the summed product of the within-slice calcified plaque area and a density weighting factor representing the peak CT attenuation within the individual calcified plaque (4). Regional distribution of CAC is not a factor in traditional Agatston CAC scoring. Subjects were told after the baseline visit (2000 to 2002) whether they had no, less than average, average, or greater than average CAC and were encouraged to discuss the results with their physicians.
Definition of CAC parameters
Vessel-specific CAC measurements were performed in 6,540 MESA participants (96%). A total of 3,262 (50%) individuals had baseline CAC >0 and form the population for this analysis.
We tested 2 approaches to accounting for the regional distribution of CAC. The number of vessels with CAC, a measure of multivessel disease, was calculated as an ordinal variable (1 to 4) indicating CAC involvement of the left main, left anterior descending, left circumflex, and right coronary arteries (11).
In participants with CAC in ≥2 vessels, we calculated a “diffusivity index” representing the degree of dispersion of CAC within the coronary tree. A higher diffusivity index represents a more diffuse pattern of CAC, whereas a smaller diffusivity index represents a great percentage of the total CAC in a single artery. The diffusivity index was calculated as a continuous variable by dividing the CAC score of the most affected vessel (the single vessel with the highest individual CAC score) by the total Agatston CAC score, and subtracting this quantity from 1 (equation: 1 − CAC in most affected vessel/total CAC). For example, for an individual with 3-vessel CAC and a total score of 300 with 200 in the left anterior descending, 50 in the left circumflex, and 50 in the right coronary artery, the diffusivity index would be: (1 − [200/300]) = 0.33, or 33%. If the same individual with total CAC score of 300 had 100 in the left anterior descending, 100 in the left circumflex, and 100 in the right coronary artery the diffusivity index would be: (1 − [100/300]) = 0.67, or 67%.
A categorical variable representing CAC pattern was calculated using thresholds of the diffusivity index. Concentrated CAC pattern was considered to be present when the diffusivity index was <25th percentile for a given number of vessels with CAC. Diffuse CAC pattern was defined as a diffusivity index >75th percentile for a given number of vessels with CAC.
Baseline characteristics are presented according to the number of vessels with CAC. Frequencies and proportions were calculated for categorical variables, and either means with standard deviations or medians with interquartile ranges calculated for continuous variables. Differences between the groups were calculated using the chi-square test, 1-way analysis of variance, or nonparametric testing where appropriate.
Absolute CHD and CVD event rates were calculated by dividing the total number of events by the total number of person-years at risk (expressed per 1,000 person-years). These rates were displayed graphically and in tabular form across increasing number of vessels with CAC and across concentrated versus intermediate versus diffuse CAC distribution pattern in those with ≥2 vessels with CAC.
Cox proportional hazards regression was used to model time-to-first CHD or CVD event. The proportionality assumption was confirmed graphically using both the log-log plot and by comparison of Kaplan-Meier and predicted survival plots. The overall analytical goal was to test whether measures of CAC distribution add to the traditional Agatston CAC score for event prediction. First, measures of CAC distribution were added to a model including age, sex, race, and the total Agatston CAC score. Baseline total Agatston CAC was modeled in 3 ways: 1) by CAC score group (1 to 100, 101 to 300, >300); 2) as a continuous variable; and 3) as a log-transformed variable (ln [CAC + 1]) (12). Additional models were then conducted adding adjustment for cardiovascular risk factors including body mass index, cigarette smoking status, diabetes, systolic blood pressure, antihypertensive medication use, total cholesterol, high-density lipoprotein cholesterol, and lipid-lowering medication use.
The incremental predictive value of regional CAC measures beyond the traditional total Agatston CAC score was tested using area under the receiver operating curve (AUC) and net reclassification improvement index (NRI) analyses. Incremental AUC analyses were calculated from logistic regression models, and were conducted for each of the described baseline total CAC definitions in unadjusted, age/sex/race-adjusted, and fully adjusted models. The NRI was calculated in fully adjusted models as the category-less continuous NRIc (13). Continuous NRIc was selected because the thresholds, size, and interpretation of conventional risk categories vary by old and new risk assessment guidelines and therefore by the use of CHD or CVD as the primary outcome.
The incremental value of identifying which particular coronary artery is afflicted with CAC was also modeled. For this analysis, individual coronary artery involvement was modeled with binary variables (yes/no) and with exact CAC scores. Cox proportional hazards regression models were used entering terms for involvement in each coronary artery after controlling for the total CAC score and the percentage of the total CAC score in the individual coronary arteries.
All statistical analyses were conducted using STATA 13 (Stata Corp., College Station, Texas). A 2-tailed p value of <0.05 was considered significant.
The mean age of the study population was 66 ± 10 years with 58% men. Approximately 43% were white persons, 12% Chinese, 24% African American, and 20% Hispanic. In general, with increasing number of vessels with CAC, there was a greater number of cardiovascular risk factors present and with greater risk factor severity (Table 1).
The mean CAC score of the population was 291 ± 555 Agatston units, with a median and interquartile range of 86 (22 to 294). The mean number of vessels with CAC was 2.2 ± 1.0. The mean diffusivity index (% of CAC in the most affected vessel) was 24 ± 15% for 2-vessel CAC, 38 ± 15% for 3-vessel CAC, and 46 ± 13% for 4-vessel CAC. By definition, 25% of participants in each group (2-, 3-, and 4-vessel) were assigned to the diffuse CAC pattern. Complete CAC characteristics of the population are shown in Table 1 and Online Tables 1 and 2.
There was considerable heterogeneity between conventional CAC groups and number of vessels with CAC (Figure 1). Heterogeneity was predominantly noted in the intermediate CAC score 1 to 300 range. In contrast, most individuals with CAC >300 had at least 3-vessel CAC (91%).
There were a total of 368 CHD and 493 CVD events during follow-up, of which 154 were myocardial infarctions, 19 were resuscitated cardiac arrests, 65 were CHD deaths, 130 were revascularizations with angina, 89 were strokes, and 36 were other cardiovascular/other atherosclerotic deaths. Figures 2A and 2B show the absolute CHD and CVD event rates across increasing number of vessels with CAC after stratifying by traditional total Agatston CAC score groups. Event rates increased with an increasing number of vessels with CAC. Within subpopulations defined by the number of vessels with CAC, event rates were lowest in those with a concentrated CAC pattern, and progressively higher with an intermediate and diffuse pattern (Figures 2C and 2D).
Table 2 shows the results of the Cox proportional hazards models for both CHD and CVD adding number of vessels with CAC to the total traditional Agatston CAC score. In models adjusted for age, sex, and race, there was 2.5- to 3.5-fold increase in CHD risk and a 2- to 2.5-fold increase in CVD risk with 4-vessel CAC compared with 1-vessel CAC across models adjusting for CAC as a categorical variable, continuous variable, and as a log-transformed variable (all p < 0.05). Improvement in risk stratification adding the number of vessels with CAC was only noted in the intermediate CAC score range (1 to 300) (Online Table 3). With CAC scores >300, where there was little heterogeneity between CAC score group and regional CAC distribution (Figure 1), the number of vessels with CAC provided no added prognostic value. Interaction of number of vessels with CAC and CAC score group is shown in Online Table 4.
In incremental AUC analysis (Table 3), addition of number of vessels with CAC to the total traditional Agatston CAC score resulted in a statistically significant improvement in risk discrimination for both CHD (improvement in C statistic of 0.016 to 0.030) and CVD (improvement in C statistic of 0.010 to 0.022) in unadjusted models. The results were attenuated, but generally remained statistically significant, after complete risk factor adjustment. The magnitude of improvement in the C statistic was largest when CAC was intermediate (CHD, 0.036; CVD, 0.024 to 0.025). However, the improvements in this smaller subset (n = 2,458) no longer reached statistical significance after complete risk factor adjustment (Online Table 5).
Table 3 also shows the results of the NRIc analysis adding number of vessels with CAC to the total CAC score. In age, sex, and race adjusted models, addition of number of vessels with CAC led to an NRIc of between 0.14 and 0.41 for CHD and of between 0.11 and 0.35 for CVD (p < 0.05). The NRIc values were mildly attenuated in the fully adjusted model, but remained statistically significant. Online Table 5 shows that NRIc values were higher when CAC was in the intermediate 1 to 300 range (log [CAC +1] model).
Table 4 shows the results of the Cox proportional hazards model adding the diffusivity index and the categorical measure of CAC pattern to the total traditional Agatston CAC score in participants with ≥2 vessels with CAC. In all models, the diffusivity index was positively associated with cardiovascular outcomes (hazard ratio [HR]: 1.01 [95% confidence interval (CI): 1.00 to 1.02] per 1% change), suggesting higher risk with an increasingly diffuse CAC pattern. In addition, there was a graded increase in the risk of both CVD and CHD with advancement from a concentrated to an intermediate to a diffuse CAC pattern. However, addition of the diffusivity index and the CAC pattern to the total traditional Agatston CAC score and the number of vessels with CAC did not lead to further improvement in the C statistic (Online Tables 6 and 7).
Table 5 shows the results of the analysis testing the prognostic significance associated with which specific coronary artery is afflicted with CAC. In models adjusting for the total Agatston CAC score and the percent of the total CAC score in the coronary arteries, only presence of CAC in the right coronary artery remained a significant predictor of CHD and CVD (HR: 2.10 [95% CI: 1.51 to 2.90] for CHD; HR: 1.62 [95% CI: 1.24 to 2.14] for CVD). For the left main coronary artery, the point estimate signaled an increase in events; however, this did not reach statistical significance. Modeling the exact CAC score in the individual coronary arteries did not change the overall conclusions. Addition of involvement of individual coronary arteries, or just the right coronary artery, to the Agatston score did not improve the AUC for CHD or CVD events (data not shown).
In our study of a well-defined multiethnic cohort free of baseline CVD, we have shown that measures of diffuse CAC distribution add predictive value to the Agatston CAC score, particularly when traditional CAC scores are in the intermediate range (1 to 300). This incremental predictive value is of similar magnitude to that commonly attributed to adding novel serum biomarkers to traditional risk factors in intermediate-risk patients (14).
The most important finding is that simple addition of the number of vessels with CAC to the traditional Agatston score improves both the AUC and the NRI for prediction of CHD and CVD events. This simple measure of multivessel CAC does not require remeasurement or a complicated calculation, and is available on all CAC scores that report CAC on a per-vessel basis (11). Our results therefore point to a parsimonious method for improving CAC scoring, and have direct implications for clinical risk prediction and for future development of improved CAC scoring.
Traditional CAC scoring
Arthur Agatston and Warren Janowitz developed CAC scoring in 1990 (4). Their CAC score, reported as a single number, is elegant and has withstood more than 2 decades of scientific scrutiny. However, this algorithm makes 2 implicit assumptions about the relationship of detectable calcium to incident CVD events (8).
First, Agatston scoring assumes that an increased local density of calcium is associated with more coronary artery disease and greater CVD risk. This is inherent in the increased weight Agatston scoring places on denser, more highly attenuating plaque. However, it is now appreciated that less dense local calcium may signal greater risk, perhaps caused by the inverse association between CAC density and a quantity of low-attenuation lipid-rich core (15).
Second, Agatston scoring implicitly assumes that identical CAC scores are equal with regard to their relationship to coronary artery disease and CVD events. For example, an Agatston CAC score of 200 situated entirely in the proximal left anterior descending is implicitly considered equivalent to a CAC score of 200 spread across all 3 epicardial coronary arteries. The regional distribution of CAC, including both spatial distribution across arteries and along the length of individual arteries, is not accounted for (Figure 3).
It is important to note that these assumptions are in fact related (8). For a given Agatston CAC score, presence of overall less dense calcium translates into lower CAC scores for individual plaques, and therefore by definition translates into more plaques and a diffusely distributed pattern of disease. These assumptions have distinct implications for the optimal way to express the CAC score.
Importance of total atherosclerosis burden and plaque type
The close association between CAC and CVD events has traditionally been explained by the close relationship between CAC and total atherosclerosis burden (16). Indeed, pathology studies and imaging studies dating back several decades have suggested a direct relationship between the amount of CAC and the total volume of atherosclerosis (2). Recent event-driven studies in several different patient populations have shown that it is the total atherosclerosis burden, rather than the presence of obstructive coronary artery disease or inducible ischemia, that is the most important predictor of CVD events (17–20).
A recent study by Tota-Maharaj et al. (21) suggests a mechanism for our primary finding. In this cross-sectional analysis of 920 patients undergoing concomitant CAC scoring and coronary CT angiography, addition of number of vessels with CAC improved the relationship of the traditional Agatston CAC score to the segment involvement score, a validated coronary CT angiography measure of total coronary atherosclerosis. The greatest improvement in the association with total atherosclerosis occurred when traditional Agatston CAC scores were in the intermediate range (1 to 400). The results of the Tota-Maharaj et al. (21) study reinforce older data showing that the number of vessels with CAC is strongly associated with the number of vessels with obstructive coronary disease on invasive angiography (22).
In addition to improving the association with total atherosclerosis burden, addition of measures of regional CAC distribution may also indicate presence of higher risk plaque types. For a given Agatston CAC score, more diffuse CAC correlates with lower attenuation plaque (on average), including a greater frequency of mixed plaque (higher risk) compared with fully calcified plaque. Studying similar participants from MESA, Criqui et al. (23) found that a CAC “density score” was inversely related to CVD events, and adding the density score to the traditional Agatston CAC score improved global risk prediction.
Prior outcome studies of CAC distribution
In a retrospective clinical cohort of ∼25,000 patients without known CHD referred for CAC scoring, Budoff et al. (24) found that the number of vessels with CAC was strongly related to all-cause mortality. In another retrospective study of nearly 15,000 patients referred for clinical CAC scoring, Williams et al. (25) found that the number of CAC lesions (another surrogate for diffuse CAC) was associated with greater all-cause mortality after adjusting for traditional risk factors. Both the Budoff and Williams papers were limited by their retrospective design, potential for referral bias, and study of only all-cause mortality. In a prior study from MESA, Brown et al. (26) derived a novel measure of CAC distribution called the “calcium coverage score.” This score quantifies the percent length of the coronary arteries that is afflicted with CAC. This score differs from considering number of vessels with CAC by prioritizing CAC distribution along the length of individual arteries rather than spatially across the major epicardial arteries. At 41-month median follow-up, the calcium coverage score was strongly associated with hard CHD events. However, after this limited follow-up period, the p value for the calcium coverage score versus the Agatston score was 0.074 (AUC, 0.68 vs. 0.66). No specific analysis was undertaken in participants with intermediate CAC scores. Likely because of its complexity, the calcium coverage score has not been widely adopted.
In a small proof of principle case-control study, Qian et al. (27) calculated a “lesion-specific” CAC score including data on the number of vessels with CAC, the number of lesions with CAC, spatial distribution of lesions, and lesion-specific morphology. In 60 patients with CAC, the lesion-specific CAC score outperformed traditional CAC scoring for prediction of cardiac events.
Future of CAC scoring
First, our results must be validated in other cohort studies that have made CAC measurements on a per-vessel basis. This should include registry studies of clinical CAC scanning, because most clinical cardiac CT centers have routinely reported CAC on a per-vessel basis (28).
These findings have implications for the future of clinical CAC scoring. The traditional Agatston CAC score has persisted for decades, but emerging evidence has suggested novel ways of improving the score (28). An advantage of simple consideration of number of vessels with CAC is that it also is easy to quantify on nongated chest CTs ordered for noncardiac indications, which is a rapidly expanding application of CAC scoring (29).
Although we considered the number of coronary vessels with CAC (a measure of diffuse CAC across coronary arteries), data were not available to test indices of proximal versus distal CAC (a measure of diffuse CAC within an individual coronary artery), the total number of CAC lesions, or a per-segment CAC involvement score. These measures may be superior to the diffusivity index. Although proximal coronary artery disease is considered to be a higher risk presentation on invasive coronary angiography, it is unknown if proximal CAC or an increased number of distinct CAC lesions confers a worse prognosis.
We have shown that readily available measures of diffuse CAC distribution add to the traditional Agatston CAC score for the prediction of CHD and CVD events. While we await development of a new comprehensive CAC scoring algorithm, clinicians may consider reporting and interpreting the number of vessels with CAC in addition to a total CAC burden score on routine ungated and gated noncontrast chest and cardiac CT scans, particularly when CAC burden is intermediate.
COMPETENCY IN MEDICAL KNOWLEDGE: The traditional Agatston CAC score does not account for the regional distribution of calcified plaque in the coronary tree. In this study, we have shown that after adjustment for the total Agatston score, a more diffuse distribution of calcified plaque is associated with a worse cardiovascular prognosis compared with a more localized, concentrated CAC phenotype.
TRANSLATIONAL OUTLOOK: In the future, there will likely be improvements in the way the CAC score is calculated in clinical practice. Future research is needed to define how best to incorporate total CAC volume, CAC density, and the regional distribution of CAC into a single improved CAC score that best predicts cardiovascular events beyond standard risk scoring algorithms.
The authors 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.
For supplemental tables, please see the online version of this article.
This research 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, N01-HC-95166, N01-HC-95167, N01-HC-95168, and N01-HC-95169 from the National Heart, Lung, and Blood Institute and by grants UL1-TR-000040 and UL1-TR-001079 from the National Center for Research Resources. Dr. Budoff has received grant support from General Electric. Dr. Nasir is a consultant for Regeneron. All other authors have reported that they have no relationships relevant to the contents of this paper to disclose.
- Abbreviations and Acronyms
- area under the curve
- coronary artery calcium
- coronary heart disease
- computed tomography
- cardiovascular disease
- net reclassification improvement
- Received November 13, 2015.
- Revision received March 2, 2016.
- Accepted March 3, 2016.
- American College of Cardiology Foundation
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