Abstract
Objectives
By examining the distribution of CAC across FRS strata in a large, multi-ethnic, community-based sample of men and women, we sought to determine if lower risk persons could potentially benefit from CAC screening.
Background
The 10-year Framingham risk scores (FRS) and coronary artery calcium (CAC) are predictors of coronary heart disease (CHD). CAC ≥300 is associated with the highest risk for CHD even in low risk (FRS <10%) persons; however expert groups have suggested CAC screening only in intermediate risk (FRS 10–20%) groups.
Methods
We included 5660 MESA participants. The number needed to screen [number of people that need to be screened to detect one person with CAC above the specified cut-point (NNS)] was used to assess the yield of screening for CAC. CAC prevalence was compared across FRS strata using chi-square tests.
Results
CAC >0, ≥100 and ≥300 were present in 46.4%, 20.6% and 10.1% of participants, respectively. Prevalence and amount of CAC increased with higher FRS. CAC ≥300 was observed in 1.7% and 4.4% of those with FRS 0–2.5% and 2.6–5%, respectively (NNS =59.7 and 22.7). Likewise, CAC ≥300 was observed in 24% and 30% of those with FRS 15.1–20% and >20%, respectively (NNS =4.2 and 3.3). Trends were similar when stratified by age, gender and race/ethnicity.
Conclusions
Our study suggests that in very low risk individuals (FRS ≤5%), the yield of screening and probability of identifying persons with clinically significant levels of CAC is low, but becomes greater in low and intermediate risk persons (FRS 5.1–20%).
Keywords: Framingham risk score, coronary calcium, coronary heart disease, number needed to screen, risk factors, population, atherosclerosis, low risk
Introduction
In current clinical practice of preventive cardiology, intensity of treatment is matched to the severity of the patient’s overall (global) cardiovascular risk status based on the principle that the highest risk patients will benefit the most from drug treatments, with less absolute benefit for lower risk patients. The FRS is considered a useful tool in the estimation of 10-year risk of CHD but fails to identify many people destined to develop a CHD event.[1] Thus, additional tests of cardiovascular risk such as CAC scoring have been evaluated as possible ways to improve global CHD risk assessment. CAC has been shown to provide incremental CHD risk prediction beyond traditional risk factors, and patients with advanced CAC burden (CAC scores ≥ 300 or 400) have the greatest risk.[2–6]
While proposed as an adjunctive tool for risk assessment, CAC scoring has not been recommended for widespread population screening in recent consensus statements,[5, 7, 8] and has instead been regarded as most promising in modifying risk assessment primarily in intermediate risk patients in whom the estimated 10-year CHD risk is between 10–20% by FRS.[5, 8] Recent data from the Multi-Ethnic Study of Atherosclerosis (MESA) suggested that in low risk women, a very high CAC score (≥300) was associated with an adjusted hazard ratio of 8 for major coronary events compared to those without detectable CAC.[3] However, whether lower risk patients might benefit from CAC testing is not yet answered.
Although a few studies have examined the relationship between FRS and CAC prevalence/amount,[2, 9–14] it is still not yet known whether additional CAC testing in low to intermediate risk patients would be a useful way to find additional high-risk patients who might merit more intensive risk factor treatments. These previous studies have been limited by small sample size, referral-based samples, homogenous racial and sex compositions, and self-report of risk factors, with sparse data on stratification by age, sex and race/ethnicity. In addition, it is unclear how many people at selected levels of risk would require screening in order to detect one person with CAC ≥300.
The aim of the present study is to ascertain the prevalence and distribution of CAC across Framingham risk strata in a large, multi-ethnic, multi-center, community-based sample of men and women; stratified by age, gender and race/ethnicity. Based on these relationships, the yield of screening, and therefore FRS ranges where CAC scoring might be beneficial in risk assessment, may become apparent and aid further risk stratification for the large number of asymptomatic individuals predicted to be at low or intermediate 10-year risk by traditional risk factors alone.
Methods
The MESA is a prospective cohort study examining measures of subclinical atherosclerosis, progression of subclinical atherosclerosis, and conversion to clinical events. Details of the study design, as well as inclusion/exclusion criteria and baseline characteristics have been described previously.[15] Briefly, at baseline the cohort included 6814 participants (3213 men and 3601 women) aged 45 to 84 years from four different racial/ethnic groups (38% white, 28% African American, 22% Hispanic and 12% Chinese) in six US communities including Baltimore, Maryland; Chicago, Illinois; Forsyth, North Carolina; Los Angeles, California; New York, New York; and St. Paul, Minnesota. The participants were free of clinical cardiovascular disease at first examination (July 2000 to August 2002).
For the current study, we included men and women aged ≤79 years at baseline (n = 6526) because FRS could not be calculated in individuals older than 79 years. Participants with diabetes were excluded from our analyses (n = 811) since they were considered high-risk in current NCEP-ATP III guidelines,[16] and our paper focuses on evaluating ‘yield of screening’ in individuals at lower risk. Finally, 55 additional participants were excluded due to missing FRS equation covariates (n = 7), and absence of measured CAC (n = 48). Baseline examination, laboratory data and cardiac CT methods have been described elsewhere.[15, 17]
Definitions
Body mass index was defined as weight in kilograms divided by height in meters squared. Presence or absence of family history of heart attack was determined at baseline and further described in detail during the second examination. Current smoking was defined as smoking cigarettes within the past 30 days. Medication use was derived from medication lists and clinical staff entry of prescribed medications. Aspirin use was defined as ≥ 3 days per week at baseline.
Agatston CAC measurement and scoring have been previously described.[18] There was excellent agreement between and within readers for presence and amount of calcified plaque (kappa >0.90 and > 0.99, respectively). For this study, Agatston CAC scores were obtained from baseline MESA examination 1 (2000–2002). CAC scores were categorized as CAC >0, ≥100 or ≥300. Concurrent FRS 10-year risk for CHD [16] was calculated and stratified as follows: 0–2.5%, 2.6–5%, 5.1–7.5%, 7.6–10%, 10.1–15%, 15.1–20% and >20%. We chose these defined CAC cut-points rather than mutually exclusive CAC categories because the study aimed to examine screening, rather than risk prediction thresholds.
Statistical Analysis
All analyses were performed using SAS software, version 9.2 (SAS Institute, Cary, NC). A 2-tailed value of P < 0.05 was considered statistically significant. The Framingham 10-year risk estimates for all participants at examination 1 were calculated based on age, total and high density lipoprotein cholesterol levels, current smoking status, systolic blood pressure and the use of antihypertensive medication using the risk prediction functions from the NCEP ATP-III guidelines.[16] Baseline characteristics were compared according to FRS 10-year risk categories and by CAC classification using general linear models for continuous variables and cross-tabulations for categorical variables. The prevalence of CAC strata across FRS 10-year risk strata were compared using the Chi-square test. The comparison was further assessed after stratification by age, sex and race. The yield of screening for CAC was assessed using the NNS, which was calculated by dividing the total number of participants within each FRS stratum by the number of people with CAC >0, ≥100 or ≥300 within that FRS stratum. The NNS defines the number of people that need to be screened in order to identify one individual with CAC value above the specified CAC cut-point within each FRS category. For the purposes of our study, CAC amount is represented by median CAC scores within FRS groups.
Multivariable analyses were carried out in order to determine the relationship between CAC ≥300 (advanced CAC) and FRS distributions. The associations of FRS 10-year risk levels with CAC ≥300 were examined (separately) using logistic regression models; and the multivariable-adjusted odds ratios and their 95% confidence intervals were assessed. Covariates included race/ethnic background, body mass index, family history of heart attack, use of aspirin, family income, education, health insurance, marital status, beta blocker, calcium channel blockers and ace inhibitors/angiotensin receptor blockers; as shown in table 1. A model containing these covariates plus strata of FRS 10-year risk covariates were fitted to estimate their association. This model was chosen based on known associations of certain racial/ethnic groups with increased CAC and/or FRS; risk factors known to be associated with CHD, but not included in the FRS model; and socio-economic factors. We focused our multivariable analysis on CAC ≥300 because advanced CAC (CAC score ≥300 or 400) has been associated with the highest risk for CHD events.[2–4, 6, 19]
Table 1.
Baseline Characteristics by Coronary Artery Calcium Score Categories, n = 5660
| Characteristics | Coronary Artery Calcium Score Categories | ||||||||
|---|---|---|---|---|---|---|---|---|---|
| 0 (N =3034) |
>0 (N =2626) |
p value |
<100 (N =4497) |
≥100 (N =1163) |
p value |
<300 (N =5086) |
≥300 (N =574) |
p value |
|
| Mean age (years) | 57.4 ± 8.8 | 65.0 ± 9.0 | <0.01 | 59.2 ± 9.2 | 67.8 ± 8.1 | <0.01 | 60.3 ± 9.4 | 68.9 ± 7.6 | <0.01 |
| Female sex (%) | 63.6 | 41.4 | <0.01 | 58.2 | 34.4 | <0.01 | 56.1 | 28.4 | <0.01 |
| Race (%) | <0.01 | <0.01 | <0.01 | ||||||
| White | 35.8 | 47.8 | 37.8 | 55.1 | 39.4 | 59.1 | |||
| Black | 29.3 | 22.2 | 12.4 | 9.4 | 26.8 | 19 | |||
| Chinese Am | 11.8 | 11.8 | 27.7 | 19.8 | 12.4 | 6.5 | |||
| Hispanic | 23.1 | 18.2 | 22.2 | 15.7 | 21.4 | 15.5 | |||
| SBP (mmHg) | 121.4 ± 20.2 | 129.1 ± 20.9 | <0.01 | 123.3 ± 20.4 | 131.6 ± 21.3 | <0.01 | 124.1 ± 20.6 | 133.2 ± 21.5 | <0.01 |
| DBP (mm/Hg) | 71.2 ± 10.3 | 73 ± 10.2 | <0.01 | 71.6 ± 10.3 | 73.3 ± 10.1 | <0.01 | 71.8 ± 10.3 | 74 ± 10 | <0.01 |
| BMI (kg/m2) | 28 ± 5.5 | 28.1 ± 5.2 | 0.58 | 28.1 ± 5.5 | 28.1 ± 5 | 0.63 | 28.1 ± 5.4 | 28.1 ± 4.7 | 0.96 |
| Total cholesterol (mg/dL) | 194.5 ± 34.7 | 196 ± 35.4 | 0.10 | 195 ± 35 | 195.8 ± 35.3 | 0.50 | 195.2 ± 35 | 195.1 ± 35.1 | 0.95 |
| HDL-cholesterol (mg/dL) | 53 ± 15.2 | 49.9 ± 14.5 | <0.01 | 52.1 ± 15 | 49.8 ± 14.7 | <0.01 | 51.8 ± 15 | 49.6 ± 14.5 | <0.01 |
| LDL-cholesterol (mg/dL) | 116.6 ± 30.3 | 120.1 ± 31.8 | <0.01 | 117.8 ± 30.9 | 120 ± 31.6 | 0.03 | 118.1 ± 31 | 119.1 ± 31.5 | 0.46 |
| Current smoking (%) | 13.3 | 13.8 | 0.59 | 13.5 | 13.2 | 0.79 | 13.4 | 13.9 | 0.73 |
| HTN treatment (%) | 23 | 36.1 | <0.01 | 25.9 | 41.2 | <0.01 | 27.5 | 43.2 | <0.01 |
| Lipid treatment (%) | 9.6 | 19.6 | <0.01 | 12.2 | 22.4 | <0.01 | 13.2 | 23.3 | <0.01 |
| Family history (%) | 35.5 | 46 | <0.01 | 37.9 | 49.9 | <0.01 | 39 | 52.6 | <0.01 |
| Physical activity (MET-min/wk) | 927 ± 2714 | 1055 ± 3076 | 0.09 | 977 ± 2937 | 1022 ± 2691 | 0.63 | 970 ± 2893 | 1135 ± 2837 | 0.19 |
| Education (%) | 0.04 | 0.01 | 0.51 | ||||||
| Less than high school | 16.1 | 15.8 | 16.5 | 13.9 | 16.1 | 14.5 | |||
| High school | 16.3 | 19.1 | 16.9 | 20.3 | 17.4 | 19.2 | |||
| College | 48.4 | 45.6 | 47.5 | 45.5 | 47.2 | 46 | |||
| Graduate school | 19.3 | 19.5 | 19.2 | 20.3 | 19.3 | 20.4 | |||
| Married (%) | 61.5 | 62.9 | 0.30 | 62 | 62.6 | 0.73 | 62.1 | 62.9 | 0.70 |
| Annual income (%) | <0.01 | 0.02 | 0.32 | ||||||
| < $25,000 | 26.2 | 31.2 | 27.6 | 32.4 | 28.1 | 31.9 | |||
| $25,000 – $50,000 | 28.9 | 28.8 | 29.1 | 28 | 29 | 27.7 | |||
| $50,000 – $75,000 | 19 | 16.4 | 18.1 | 16.5 | 17.9 | 17 | |||
| > $75,000 | 25.9 | 23.6 | 25.3 | 23.1 | 25 | 23.4 | |||
| Health insurance (%) | 74.2 | 69 | <0.01 | 72.9 | 67.6 | <0.01 | 72.2 | 67.8 | 0.02 |
| Medications (%) | |||||||||
| Aspirin | 13.5 | 23.9 | <0.01 | 15.4 | 29.6 | <0.01 | 16.7 | 32.9 | <0.01 |
| ACEI/ARB | 7 | 13.2 | <0.01 | 8.2 | 16.2 | <0.01 | 8.9 | 18.1 | <0.01 |
| Beta Blocker | 7 | 10.8 | <0.01 | 8 | 12 | <0.01 | 8.4 | 12.2 | <0.01 |
| Nitrates | 0.1 | 0.2 | 0.36 | 0.1 | 0.2 | 0.76 | 0.2 | 0.0 | 0.34 |
| CCB | 8 | 13.7 | <0.01 | 9.5 | 15 | <0.01 | 10.1 | 15.5 | <0.01 |
ACEI = ace inhibitor; ARB = angiotensin receptor blocker; BMI = body mass index; CCB = calcium channel blocker; DBP = diastolic blood pressure; HDL = high density lipoprotein; HTN = hypertension; LDL = low density lipoprotein; MET = metabolic equivalent; SBP = systolic blood pressure
Results
Baseline Characteristics
Our study sample was made up of a total of 5660 MESA men and women (mean age 60.9 years, 53% women) from 4 different racial/ethnic groups (41% white, 26% black, 12% Chinese and 21% Hispanic). There were significant differences in most traditional risk factors, socio-demographic factors and medications usage between participants using all 3 CAC cut-points (CAC >0 versus CAC =0, CAC ≥100 versus CAC <100 and CAC ≥300 versus CAC <300 – table 1). As expected, most of the baseline characteristics, including traditional cardiovascular risk factors, were significantly different across FRS strata (data not shown).
Distribution of CAC Prevalence and Amount Compared across FRS Strata
Table 2 displays the comparison of CAC prevalence and amount using different cut-points across FRS strata. The median CAC scores (among those with CAC >0) with interquartile ranges across FRS strata are also shown. For the whole cohort, the median CAC scores were greater with higher FRS (Spearman correlation coefficient =0.45, p <0.01). Similarly, CAC prevalence (for each CAC cut-point) increased with greater FRS (Figure 1; all p for trend <0.01). Within each CAC category, the NNS to detect one participant with CAC above the selected CAC cut-point decreased with higher FRS (Table 2). For example, among those with CAC ≥300, the NNS decreased from 59.7 for FRS 0–2.5% to 3.3 for FRS >20%. Likewise, within each FRS stratum, the NNS increased with increasing CAC severity category. The pattern of results was similar when we used CAC ≥400 as the cut-point for advanced CAC.
Table 2.
Coronary Artery Calcium Prevalence, Amount and ‘Number Needed to Screen’ Compared with Framingham Risk Score Categories
| CAC Score Group | Framingham Risk Score Categories (N =5660) | |||||||
|---|---|---|---|---|---|---|---|---|
| 0–2.5% (N =1730) |
2.6–5% (N =1045) |
5.1–7.5% (N =442) |
7.6–10% (N =779) |
10.1–15% (N =617) |
15.1–20% (N =793) |
> 20% (N =254) |
p value | |
|
Median CAC score* (IQR) |
28.6 (7.4, 91.6) |
39.7 (11.9, 140.6) |
62.5 (15.9, 211.2) |
71.5 (19.3, 257) |
111.6 (27.7, 284.1) |
134.6 (33.5, 427.6) |
198.6 (56.5, 483.7) |
|
|
CAC > 0 (%) N =2626 |
22.3 | 39.3 | 44.8 | 57.6 | 63.9 | 73 | 82.3 | <0.01 |
| NNS (CAC > 0) | 4.5 | 2.5 | 2.2 | 1.7 | 1.6 | 1.4 | 1.2 | |
|
CAC ≥ 100 (%) N =1163 |
5.1 | 12.6 | 18.3 | 24.8 | 33.2 | 40.9 | 54.7 | <0.01 |
| NNS (CAC ≥ 100) | 19.4 | 7.9 | 5.5 | 4.0 | 3.0 | 2.5 | 1.8 | |
|
CAC ≥ 300 (%) N =574 |
1.7 | 4.4 | 7.5 | 13.1 | 15.6 | 24.1 | 30.3 | <0.01 |
| NNS (CAC ≥ 300) | 59.7 | 22.7 | 13.4 | 7.6 | 6.4 | 4.2 | 3.3 | |
Among those with CAC >0.
Abbreviations for Tables 2 and 3: IQR = Interquartile Range (25th percentile, 75th percentile); NNS: Number needed to screen to identify one individual with CAC value above a specified CAC cutoff point, within each specified FRS stratum
Figure. Coronary calcium prevalence by Framingham risk score.
The prevalence of categories of coronary artery calcium scores (CAC >0, ≥100 and ≥300) are compared across 10-year Framingham risk score strata.
Data were further stratified by sex (Table 3), and revealed that the prevalence of CAC >0, ≥100 and ≥300 and median CAC scores were higher in women than in men for the lower FRS strata, equivocal between men and women in the intermediate FRS strata, and generally slightly higher in men than in women for the higher FRS strata. Stratification by age (45 – 54 years, 55 – 64 years and 65 – 79 years) generally followed the same pattern as the overall cohort (data not shown) with median CAC scores and prevalence of CAC >0, CAC ≥100 and CAC ≥300 increasing across advancing age groups. When stratified by race/ethnicity, whites exhibited the highest median CAC scores and the highest prevalence of CAC >0, CAC ≥100 and CAC ≥300 in each FRS stratum, with higher disparity between whites and the rest of the racial/ethnic groups as CAC severity increased.
Table 3.
Coronary Artery Calcium Prevalence and Amount Compared with Framingham Risk Score ategories, Stratified by Sex
| CAC Score Group | Framingham Risk Score Categories (N =5660) | |||||||
|---|---|---|---|---|---|---|---|---|
| 0–2.5% (N =1730) |
2.6–5% (N =1045) |
5.1–7.5% (N =442) |
7.6–10% (N =779) |
10.1–15% (N =617) |
15.1–20% (N =793) |
> 20% (N =254) |
p value | |
| Men (N =3067) | ||||||||
| Median CAC score* (IQR) | 37.1 (9.3, 128.3) | 19.1 (5.9, 51) | 32.8 (10.5, 175.7) | 72 (18.9, 257) | 111.7 (27.6, 279.7) | 142.4 (35.5, 455.6) | 207.9 (64.9, 586.7) | |
| CAC > 0 (%) N =1538 | 20 | 29.5 | 40 | 56.7 | 64.7 | 72.8 | 82.1 | p <0.01 |
| CAC ≥ 100 (%) N =763 | 5.7 | 5.5 | 12.8 | 25 | 33.6 | 41.1 | 55.1 | p <0.01 |
| CAC ≥ 300 (%) N =411 | 1.4 | 2.2 | 6.4 | 12.7 | 15.2 | 24.5 | 32.4 | p <0.01 |
| Women (N =3404) | ||||||||
| Median CAC score* (IQR) | 27.8 (7.3, 91.5) | 52 (18.1, 158.9) | 95.1 (30.1, 231.4) | 63 (20.1, 262.7) | 111.5 (28, 314.7) | 104.4 (15.2, 364.5) | 176.9 (41.1, 313.7) | |
| CAC > 0 (%) N =1088 | 22.4 | 44.6 | 50.2 | 60.8 | 61.9 | 75.4 | 83 | p <0.01 |
| CAC ≥ 100 (%) N =400 | 5.1 | 16.5 | 24.6 | 24 | 32.3 | 38.5 | 53.2 | p <0.01 |
| CAC ≥ 300 (%) N =163 | 1.7 | 5. | 8.7 | 14.6 | 16.4 | 20 | 21.3 | p <0.01 |
Among those with CAC >0.
Univariate and Multivariate Analyses for Odds of Advanced CAC (CAC ≥300) Across FRS Strata
Compared with FRS >20% as the referent group, the unadjusted odds ratios for CAC ≥300 were significantly lower with lower FRS, and increased steadily with higher FRS (Table 4). The multivariable odds ratios for CAC across FRS strata followed the same pattern, with significantly increasing odds ratios for CAC ≥300 with greater FRS; even after adjusting for race/ethnicity, socio-economic factors, as well as other cardiovascular risk factors not included in the FRS equation.
Table 4.
Univariate and Multivariable Odds Ratios and 95% Confidence Intervals for Coronary Artery Calcium Score ≥300 by Framingham Risk Score Strata
| Odds Ratios (95% CI) for CAC ≥300 | ||
|---|---|---|
| FRS Categories | Unadjusted | Adjusted* |
| > 20% | 1.0 | 1.0 |
| 15–20% | 0.73 (0.53, 1.00) | 0.68 (0.48, 0.95) |
| 10.1–15% | 0.42 (0.30, 0.60) | 0.39 (0.27, 0.57) |
| 7.6–10% | 0.35 (0.25, 0.49) | 0.32 (0.22, 0.46) |
| 5–7.5% | 0.19 (0.12, 0.29) | 0.19 (0.12, 0.31) |
| 2.6 –5% | 0.11 (0.07, 0.16) | 0.10 (0.06, 0.15) |
| 0 –2.5% | 0.04 (0.03, 0.06) | 0.04 0.02, 0.06) |
Model adjusted for race/ethnicity, body mass index, family history of heart attack, aspirin use, education, marital status, income and health insurance
CI= confidence interval
Discussion
Major Findings
We found a significant direct relationship between 10-year predicted FRS and CAC prevalence and amount such that the lower FRS risk strata had lower prevalence of CAC and lower median CAC scores. With higher FRS strata, prevalence of CAC and CAC burden increased in a stepwise fashion, and demonstrated good linear correlation. For the overall cohort, among those with FRS 0–2.5% and 2.6–5%, only 1.7% and 4.4% of our study population respectively had CAC score ≥300. On the other hand, 24% and 30% of participants had CAC ≥300 in the 15.1–20% and >20% FRS strata respectively. Similar to the trend in CAC prevalence, the yield of screening for CAC decreased in a stepwise fashion across greater FRS strata: the numbers of people that need to be screened to identify one person with CAC ≥300 (NNS for CAC ≥300) were 59.7 and 22.7 in individuals with FRS of 0–2.5% and 2.6–5% respectively, compared with 4.2 and 3.3 in those with FRS of 15.1–20% and >20% respectively. Data remained essentially unchanged when stratified by age, sex or race/ethnicity. Likewise, multivariable analysis showed significantly increasing odds for CAC ≥300 with greater FRS strata.
Potential Clinical Implications
CAC score is directly related to incidence of CHD events such that advanced CAC burden (CAC ≥300 or 400) poses the highest risk for CHD events.[2–4, 6, 19] As such, we focus our discussion on association of FRS with CAC ≥300 which is the definition of advanced CAC employed in the current study.
According to current NCEP ATP-III guidelines,[20] individuals with FRS >20% are considered high risk for CHD events, and should be appropriately managed with drug therapy and lifestyle modifications. Therefore, no further risk assessment is considered necessary in these individuals. However, for the large proportion of low to intermediate risk populations, the intervention goals are less clearly defined and may be difficult to interpret in the absence of additional information such as that provided by a CAC score. Hence, our data address the potential for modification of risk category in the low and intermediate predicted risk patient populations. The high rate of CAC ≥300 in the FRS category with predicted risk of 15.1–20% suggests a group at high CHD risk, which may particularly benefit from screening for CAC ≥300 to aid further risk factor interventions; especially in situations where there is uncertainty regarding the use of drug therapy. On the other hand, the low rate of CAC ≥300 in the lowest FRS risk categories (FRS 0–5%) suggests that this group is far less likely to yield a high CAC score on further (CAC) testing.
For this study, we chose the NNS as a tool to help evaluate potential thresholds or the yield of screening for CAC across FRS strata. The NNS (an extension of the concept of the number needed to treat) has been described in the literature as the number of people that need to be screened to prevent one death or one adverse event.[21] This initial definition has been modified in the literature,[22, 23] but to our knowledge, has not been employed in screening for subclinical CHD. For the purposes of this study, NNS is defined as the number of individuals that would have to be screened to find one person with either CAC >0, ≥100 or ≥300, depending on the CAC category. The NNS in this case weighs the yield of screening for CAC within each FRS category from a public health perspective. Among those with CAC ≥300 in our study, the NNS was 59.7 and 22.7 for individuals with FRS of 0–2.5% and 2.6–5%, respectively; and 4.2 and 3.3 for those with FRS of 15.1–20% and >20%, respectively. This represents an 18-fold difference in NNS for CAC ≥300 (absolute difference of 56) - between the lowest risk FRS stratum (FRS 0–2.5%) and the high risk stratum (FRS >20%). This difference remained reasonably large - 7-fold (absolute difference of 19) between the subsequent lowest FRS risk stratum (FRS 2.6–5%) and the high risk stratum, but became much smaller beyond that. It likely suggests a substantial difference (with minimal yield of screening) in the very low risk groups (FRS 0–5%) compared with the higher risk groups. To put our NNS findings in context, it should be noted that among those screened, the NNS to prevent one death secondary to abdominal aortic aneurysm was 20.4 in the Multicentre Aneurysm Screening Study (MASS).[24] This study utilized abdominal ultrasound to evaluate the benefit of screening for abdominal aortic aneurysms. Future studies using mortality and cardiovascular events data in the distribution of CAC by FRS strata to evaluate the concept of the NNS for CAC screening are clearly warranted.
Taken together, our prevalence and NNS data suggest the benefit of CAC testing for further risk stratification in asymptomatic low risk (FRS of 5.1–10%) and intermediate risk (FRS 10.1–20%) persons. Based on empiric observations, this is in agreement with several recommendations for the use of CAC testing for further risk stratification in asymptomatic people who are found to be at intermediate risk (FRS 10–20%).[5, 8] Our study data suggests that CAC measurement should be carried out within the context of traditional cardiovascular risk factors, rather than in isolation; and provides support for avoidance of radiation exposure as well as time, money and effort spent on CAC measurement and scoring for clinical guidance in very low-risk patients.
Other Findings
The patterns of CAC distribution differed by sex. With lower FRS, women exhibited higher CAC prevalence and amount than men. The prevalence of CAC became similar in both genders at intermediate FRS scores, and switched at higher FRS so that men (as would be expected) showed higher CAC prevalence and amount than women. This pattern is likely due to the fact that at any given age, FRS is significantly lower for women than men. Consequently, there are more women than men at lower FRS, as most women remain at low calculated FRS 10-year risk until age 70.[25–27] Also, our analysis was truncated at age 79. Men have higher FRS than women regardless of age, and are therefore more evenly distributed across the spectrum of FRS strata. They therefore comprise much of the higher FRS strata relative to women.
As expected, CAC amount and prevalence increased across FRS strata and with increasing age which is purported to be the best surrogate marker for ‘accumulated exposure’ to CHD risk factors.[13] Similar to findings in other studies,[28–32] the highest prevalence and severity of CAC was observed among whites in our study, while the lowest prevalence was observed among blacks.
CAC ≥400 is suggested as a reasonable definition of advanced CAC.[5] However because we had few participants in the CAC ≥400 category, we employed CAC ≥300 as used in other studies[2, 6] in defining advanced CAC for this study. Regardless, in our analysis, the distribution of CAC by FRS strata and the trend for yield of screening for CAC ≥400 within FRS strata were similar to what we observed when we defined advanced CAC using CAC ≥300 cut-point.
Study Limitations
Due to the small numbers of participants in each age/sex/race category, we could not make meaningful assessments of the findings using simultaneous stratification by age, sex and race/ethnicity. Furthermore, these cross-sectional observational data cannot provide definitive information about the cost-benefit of CAC measurement.
Conclusions
Our study showed that in a large, multi-ethnic, multi-center, community-based cohort of men and women, CAC prevalence was closely associated with FRS strata after multivariable analysis irrespective of age, sex or race/ethnicity. It suggests a low probability of having a high CAC score in the very low risk population with FRS ≤5%. Consequently, the yield of screening for advanced CAC burden (CAC ≥300) is lesser in this population of very low risk persons, but appears to be higher in low to intermediate risk individuals with FRS of 5.1–20%.
Acknowledgements
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.
Source of Funding and Acknowledgements: This research was supported by contracts N01-HC-95159 through N01-HC-95169 from the National Heart, Lung, and Blood Institute, Bethesda, MD.
Abbreviations and Acronyms
- FRS
Framingham Risk Score
- CHD
Coronary heart disease
- CAC
Coronary artery calcium
- MESA
Multi-Ethnic Study of Atherosclerosis
- NCEP-ATP III
National Cholesterol Education Program Adult Treatment Panel III
- NNS
Number needed to screen
Footnotes
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Disclosures
Greenland – Honoraria: GE/Toshiba (<$5001) in 2008
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