Skip main navigation

Predictors of Carotid Thickness and Plaque Progression During a Decade

The Multi-Ethnic Study of Atherosclerosis
Originally publishedhttps://doi.org/10.1161/STROKEAHA.114.005669Stroke. 2014;45:3257–3262

Abstract

Background and Purpose—

Carotid artery intima-media thickness (IMT) and plaque are noninvasive markers of subclinical arterial injury that predict incident cardiovascular disease. We evaluated predictors of longitudinal changes in IMT and new plaque during a decade in a longitudinal multiethnic cohort.

Methods—

Carotid IMT and plaque were evaluated in Multi-Ethnic Study of Atherosclerosis (MESA) participants at exams 1 and 5, a mean (standard deviation) of 9.4 (0.5) years later. Far wall carotid IMT was measured in both common and internal carotid arteries. A plaque score was calculated from all carotid segments. Mixed-effects longitudinal and multivariate regression models evaluated associations of baseline risk factors and time-updated medication use with IMT progression and plaque formation.

Results—

The 3441 MESA participants were aged 60.3 (9.4) years (53% women; 26% blacks, 22% Hispanic, 13% Chinese); 1620 (47%) had carotid plaque. Mean common carotid artery IMT progression was 11.8 (12.8) μm/year, and 1923 (56%) subjects developed new plaque. IMT progressed more slowly in Chinese (β=−2.89; P=0.001) and Hispanic participants (β=−1.81; P=0.02), and with higher baseline high-density lipoprotein cholesterol (per 5 mg/dL; β=−0.22; P=0.03), antihypertensive use (β=−2.06; P=0.0004), and time on antihypertensive medications (years; β=−0.29; P<0.0001). Traditional risk factors were associated with new plaque formation, with strong associations for cigarette use (odds ratio, 2.31; P<0.0001) and protection by black ethnicity (odds ratio, 0.68; P<0.0001).

Conclusions—

In a large, multiethnic cohort with a decade of follow-up, ethnicity was a strong, independent predictor of carotid IMT and plaque progression. Antihypertensive medication use was associated with less subclinical disease progression.

Introduction

Carotid artery intima-media thickness (IMT) and plaque presence are noninvasive markers of subclinical arterial injury that predict incident cardiovascular disease (CVD).13 Although clinical trials have used short-term change in carotid IMT as a surrogate end point to assess the impact of pharmacotherapeutic agents in homogenous populations with high levels of CVD risk factors, little is known about the predictors of carotid IMT progression in large, heterogeneous populations.4 Carotid plaque represents a later stage of arterial injury. Its presence and extent also are associated with incident CVD, yet little is known about the predictors of carotid plaque progression.1,58 The predictors of carotid IMT and plaque progression in an ethnically diverse population are unknown. We hypothesized that CVD risk factors are the major predictors of longitudinal changes in carotid IMT and plaque progression, but that race/ethnicity and use of antihypertensive and lipid-lowering medications also would affect progression.

Methods

Participants

The Multi-Ethnic Study of Atherosclerosis (MESA) is a prospective cohort of 6814 participants free of known CVD at baseline. The aim of MESA is to investigate risk factors and subclinical CVD progression in an ethnically diverse population.9 MESA enrolled participants from 6 different field centers located in Baltimore, Maryland; Chicago, Illinois; Forsyth County, North Carolina; Los Angeles County, California; New York, New York; and St. Paul, Minnesota. Details of MESA’s design have been published previously.9 The study was approved by the institutional review boards of all MESA field centers, the University of Washington Data Coordinating Center, and the University of Wisconsin Atherosclerosis Imaging Research Program. All participants provided informed consent. Our analysis was restricted to those participants with both baseline (examination 1; July 2000 to August 2002) and follow-up (examination 5; March 2010 to February 2012) risk factor and carotid ultrasound data. Baseline laboratory samples were collected after a 12-hour fast.

Carotid Ultrasonography

At baseline, B-mode ultrasound images of the right and left common, bifurcation, and internal carotid artery (ICA) segments were recorded on Super-VHS videotape with a Logiq 700 ultrasound system using the M12L transducer (General Electric Medical Systems; common carotid artery [CCA] frequency, 13 MHz). Video images were digitized at high resolution and frame rates using a Medical Digital Recording device (PACSGEAR, Pleasanton, CA) and converted into DICOM-compatible digital records. The same ultrasound system and digitizing equipment were used at examination 5; however, the video output was directly digitized using the same recorder settings without videotape. Trained, certified sonographers used preselected reference images from examination 1 to match the scanning conditions of the initial study, including display depth, angle of approach, internal landmarks, degree of jugular venous distension, and ultrasound system settings. Ultrasound images were reviewed and interpreted by the University of Wisconsin Atherosclerosis Imaging Research Program MESA Carotid Ultrasound Reading Center. Images were imported into syngo Ultrasound Workplace reading stations loaded with Arterial Health Package software (Siemens Medical, Malvern, PA) for IMT measurement and plaque scoring. Measurements of examination 1 and examination 5 carotid ultrasound images were performed simultaneously. Images were matched side by side on a video monitor and measured contemporaneously; however, examination 1 IMT measurements were not considered in choosing the examination 5 site or making the examination 5 measurements

This analysis primarily focused on CCA IMT and carotid plaque score. Internal carotid artery IMT data are presented in the online-only Data Supplements I and II. The distal CCA was defined as the distal 10 mm of the vessel. IMT was defined as the IMT measured as the mean of the mean left and right mean far wall distal CCA wall thicknesses. Carotid plaque score (0–12) was defined as the number of carotid plaques in the internal, bifurcation, and common segments of both carotid arteries.10 Carotid plaque was defined as a discrete, focal wall thickening ≥1.5 cm or focal thickening ≤50% greater than the surrounding IMT.1

Ultrasound Quality Assurance

The intraclass correlation coefficient for intrareader reproducibility for mean CCA IMT was 0.99. The intraclass correlation coefficient for inter-reader CCA IMT reproducibility was 0.95. For mean ICA, intrareader reproducibility was between 0.98 and 0.99 and inter-reader reproducibility was 0.93. To assess scan–rescan reproducibility, 44 scans were repeated by 3 sonographers. The Pearson correlation coefficient was 0.94. Mean (SD) differences were 0.006 (0.036–0.760) mm. There were no outliers noted on limit of agreement analysis for matched segments. For carotid plaque presence and score, intrareader reproducibility was κ=0.83 (95% confidence interval, 0.70–0.96) and inter-reader reproducibility was κ=0.89 (95% confidence interval, 0.72–1.00).

Statistical Methods

Descriptive statistics are reported as means (SDs) for continuous and percentages for categorical variables. Paired t tests were used to compare examination 1 and 5 continuous variables; χ2 tests for categorical variables. Plaque score progression by ethnicity was compared using a Kruskal–Wallis test.

For IMT progression, 2 sets of complimentary models were created. First, a multivariate linear regression model with scaled change of carotid IMT (micrometers per year) as the outcome measure was created. Scaled change accounted for variability in participant follow-up times. Second, a mixed-effects longitudinal change model with adjustment for estimated baseline with the outcome modeled as a continuous variable (micrometers) was created (online-only Data Supplement III).11 This model was fit with random slopes and intercepts for each participant and contained 3 components: cross-sectional, longitudinal, and transient.11 The cross-sectional component analyzed the association of baseline CVD risk factors with estimated carotid IMT at baseline, whereas the longitudinal component analyzed this association with IMT progression (micrometers per year) during the observation period. When modeling associations of change, inclusion of the measured baseline as a covariate can result in measurement error, so measured baseline IMT was not included as a covariate in either model to avoid bias.12 In the mixed-effects model, baseline IMT was accounted by the cross-sectional term to estimate the baseline IMT using both fixed and random effects. The mixed-effects model permits improved statistical efficiency given subject-specific random effects and maximum use of available data even among those with missing data. To demonstrate the consistency between the 2 models, both sets of results are shown.

For new carotid plaque formation, a multivariate logistic regression model was created. Because we desired to construct the most informative model, all models for carotid IMT progression and plaque formation included the covariates listed in the online-only Data Supplement IV and also included baseline antihypertensive and statin pharmacotherapy or their time-varying use (years). Statistical significance was set at 2-sided P<0.05. Analyses were performed in SAS (version 9.2, SAS Institute Inc, Cary, NC).

Results

Descriptive Characteristics

Participants were followed for a mean (SD) of 9.4 (0.5) years. Their characteristics are described in Table 1.

Table 1. Baseline and Follow-Up Descriptive Statistics

VariableExamination 1 (n=3441)Examination 5 (n=3441)P Value
Age, y60.3 (9.4)69.8 (9.3)<0.0001
Male sex, % (n)47.0% (1618)
Race/ethnicity, % (n)
 White39.2% (1350)
 Black26.4% (909)
 Hispanic21.5% (740)
 Chinese12.9% (442)
Annual income, % (n)
 <$16 00014.6 (490)15.3 (509)<0.0001
 $16 000–$34 99924.2 (812)25.0 (831)
 $35 000–$99 99945.1 (1509)42.1 (1398)
 ≥$100 00016.0 (537)17.6 (586)
Smoking, % (n)
 Current11.4% (390)7.31% (250)<0.0001
 Former36.6% (1258)47.1% (1610)
 Never52.0% (1788)45.7% (1562)
Systolic blood pressure, mm Hg124.4 (20.2)124.3 (20.8)0.73
High-density lipoprotein cholesterol, mg/dL51.01 (14.9)55.93 (16.9)<0.0001
Total cholesterol, mg/dL194.1 (35.1)182.7 (36.9)<0.0001
Glucose, mg/dL95.1 (26.0)102.1 (27.8)<0.0001
Body mass index, kg/m228.3 (5.3)28.5 (5.5)<0.0001
Diabetes mellitus, % (n)10 (345)19.7 (674)<0.0001
Family history of coronary heart disease, % (n)43.5 (1415)N/AN/A
Use of antihypertensive medication, % (n)34.9 (1200)55.8 (1919)<0.0001
Use of statin medication, % (n)15.1 (519)37.4 (1287)<0.0001
Mean–mean CCA IMT, μm754.6 (179.8)865.5 (198.2)<0.0001
Left CCA IMT, μm756.4 (210.4)866.1 (233.8)<0.0001
Right CCA IMT, μm753.6 (190.2)866.5 (215.2)<0.0001
Left CCA IMT absolute progression, μm109 (160.2)0.17*
Right CCA IMT absolute progression, μm114.2 (141.8)
Carotid plaque presence, % (n)47.1% (1620)68.0% (2338)<0.0001
Carotid plaque score1.11 (1.64)2.29 (2.45)<0.0001

Values are mean (SD) unless noted otherwise. CCA indicates common carotid artery; IMT, intima-media thickness; and N/A, not available.

*P value represents the comparison between left CCA and right CCA absolute progression.

Carotid IMT Progression: Multivariate Model of Scaled Change

At examination 1, several traditional CVD risk factors were associated with CCA IMT (Table 2). Predictors of IMT progression were similar in models using baseline antihypertensive and statin pharmacotherapy and time-varying use of these medications (Tables 3 and 4). Diabetes mellitus (β=2.85; P=0.02) and time on statin pharmacotherapy (β=−0.16; P=0.04) were additional predictors of IMT progression in the time-varying model. In both models, antihypertensive medication use was associated with slower IMT progression (P<0.0001) as were Chinese (P=0.001) and Hispanic ethnicities (P=0.02) (Figure). Predictors of ICA IMT progression were similar to CCA IMT progression (online-only Data Supplements I and II).

Table 2. Baseline Traditional Risk Factors and Baseline (Examination 1) Carotid Intima-Media Thickness

PredictorMultivariate Linear Regression Model* (Model R2=0.29)Mixed-Effects Longitudinal Model* (Estimated Baseline)
Parameter Estimate (SE)P ValueParameter Estimate (SE)P Value
Age (per decade)74.49 (3.49)<0.000173.62 (3.34)<0.0001
Male sex39.35 (6.75)<0.000139.03 (6.41)<0.0001
Body mass index (per 5 kg/m2)17.45 (3.27)<0.000114.59 (3.06)<0.0001
Systolic blood pressure (per 10 mm Hg)14.21 (1.60)<0.000114.80 (1.53)<0.0001
Fasting glucose (per 10 mg/dL)3.54 (1.59)0.033.12 (1.49)0.04
High-density lipoprotein cholesterol (per 5 mg/dL)−3.06 (1.14)0.007−3.33 (1.09)0.002
Total cholesterol (per 10 mg/dL)4.12 (0.86)<0.00014.12 (0.82)<0.0001
Black ethnicity29.78 (7.80)0.000128.72 (7.46)0.0001
Current cigarette use22.26 (9.50)0.0223.59 (9.17)0.01
Former cigarette use20.90 (6.40)0.00120.20 (6.13)0.001

*Outcome modeled in micrometers.

Table 3. Predictors of Carotid Intima-Media Thickness Progression: Baseline Use of Antihypertensive and Statin Medications

PredictorsMultivariate Linear Regression Model*Mixed-Effects Longitudinal Model*
Parameter Estimates (SE)P ValueParameter Estimates (SE)P Value
Chinese ethnicity−2.89 (0.88)0.001−2.29 (0.90)0.01
Hispanic ethnicity−1.81 (0.76)0.02−1.40 (0.79)0.08
High-density lipoprotein cholesterol (per 5 mg/dL)−0.22 (0.10)0.03−0.18 (0.10)0.08
Antihypertensive medication use (baseline)−2.06 (0.58)0.0004−2.11 (0.60)0.0004
Statin medication use (baseline)1.31 (0.73)0.07 (NS)1.59 (0.75)0.03

NS indicates nonsignificant.

*Outcome modeled in micrometers per year.

Table 4. Predictors of Carotid Intima-Media Thickness Progression With Antihypertensive and Statin Medications Modeled as Time-Varying Covariates

PredictorsMultivariate Linear Regression Model*Mixed Effects Longitudinal Model*
Parameter Estimates (SE)P ValueParameter Estimates (SE)P Value
Chinese ethnicity−2.93 (0.88)0.0009−2.34 (0.90)0.009
Hispanic ethnicity−2.09 (0.76)0.006−1.59 (0.79)0.04
High-density lipoprotein cholesterol (per 5 mg/dL)−0.24 (0.10)0.02−0.19 (0.10)0.06
Antihypertensive medication use, y−0.29 (0.07)<0.0001−2.04 (0.72)0.005
Statin medication use, y−0.16 (0.08)0.04−0.95 (0.74)0.20
Diabetes mellitus2.85 (1.23)0.021.89 (1.23)0.13

*Outcome modeled in micrometers per year unless noted.

Modeled in micrometers of change over observation period.

Figure.

Figure. Adjusted carotid intima-media thickness (CIMT) progression by ethnicity. Error bars represent estimated means±SE of the mean. Models adjusted for age, sex, body mass index, systolic blood pressure, tobacco use, total cholesterol, high-density lipoprotein, glucose, income, education, family history, diabetes mellitus, antihypertensive medication use, and statin medication use. ±Adjusted IMT progression rate differs compared with white ethnicity (P<0.05).

Carotid IMT Progression: Mixed-Effects Longitudinal Model

Similar to the multivariate models, in the cross-sectional component of the mixed-effects model, traditional CVD risk factors were associated with estimated baseline CCA IMT (Table 2). The estimated CCA IMT baseline in the mixed-effects model yielded the same risk factor associations with similar parameter estimates when compared with a cross-sectional analysis using a multivariate linear model and examination 1 IMT. Also, predictors of IMT progression were similar between models using baseline antihypertensive and statin pharmacotherapy, as well as time-varying use of these medications (Tables 3 and 4). The only slight difference was that baseline statin use was a statistically significant predictor in the mixed-effects model (β=1.59; P=0.03; Table 3). Antihypertensive medication use was strongly associated with slower IMT progression modeled as either baseline (P=0.0004) or time-varying (P=0.005) use as was Chinese ethnicity (P=0.01).

Carotid Plaque Formation

There were 1923 (56%) participants that formed new carotid plaque. Several traditional CVD risk factors were associated with carotid plaque formation. Whites had higher plaque score. More than 59% of whites formed new plaque; Chinese had the lowest new plaque formation rate (49.8%; online-only Data Supplement V). There only were slight differences between the baseline antihypertensive and statin pharmacotherapy models (online-only Data Supplement VI) and the time-varying models (Table 5). Current cigarette smoking was a strong predictor of new plaque formation (odds ratio, 2.31; P<0.0001). Compared with white ethnicity, black, Hispanic, and Chinese ethnicities were associated with less plaque formation.

Table 5. Predictors of New Carotid Plaque: Antihypertensive and Statin Medications as Time-Varying Covariates

VariableOR (95% CI)P Value
Age (per decade)1.63 (1.49–1.79)<0.0001
Current cigarettes2.31 (1.79–2.99)<0.0001
Total cholesterol (per 10 mg/dL)1.03 (1.01–1.06)0.005
Black0.68 (0.55–0.83)0.0002
Chinese0.69 (0.53–0.91)0.008
Hispanic0.75 (0.59–0.95)0.016
Former cigarettes1.27 (1.08–1.51)0.004
Systolic blood pressure (per 10 mm Hg)1.1 (1.05–1.15)<0.0001
Fasting glucose (per 10 mg/dL)1.05 (1.01–1.1)0.022
High-density lipoprotein cholesterol (per 5 mg/dL)0.97 (0.94–1.0)0.021

Maximum rescaled R2 for new carotid plaque=0.15; area under the curve for new carotid plaque=0.70. CI indicates confidence interval; and OR, odds ratio.

Discussion

In this large, multiethnic cohort with nearly a decade of prospective observation, Hispanic and Chinese ethnicity as well as antihypertensive medication use at baseline and throughout the observation period consistently were associated with slower carotid IMT progression. Cigarette smoking at baseline was associated with an increase in new carotid plaque formation, whereas black ethnicity was associated with less carotid plaque formation.

Numerous clinical trials have evaluated the short-term effects of pharmacotherapeutic interventions on carotid IMT progression in homogenous populations with increased levels of a specific risk factor. However, few studies examined longitudinal IMT progression in a heterogeneous population that is more representative of US population and healthier individuals than clinical trial participants. Previous investigations have been limited by factors including low inter- and intrareader correlations (0.59–0.75), low interscan reproducibility measures, use of lower-frequency ultrasound transducers, manual IMT measurement, restriction to 1 carotid artery, and homogenous cohorts.6

Consistent associations between CVD risk factors and prevalent carotid IMT have been described; however, few studies investigated progression of carotid IMT and plaque. Our model of cross-sectional associations between CCA IMT and risk factors had 1 of the highest adjusted R2 values reported to date (0.29).5,1315 Despite relatively strong associations of traditional risk factors and baseline IMT, in the fully adjusted model only Chinese and Hispanic ethnicities and use of antihypertensive medications were consistent, independent predictors of slower IMT progression. The scaled change and mixed-effects models yielded similar results with similar parameter estimates. Inter- and intrareader reliability and scan reproducibility measures were among the highest reported with precision as high as those attained in clinical trials.6,16,17

In the fully adjusted model, we observed a strong, independent protective effect of Chinese and Hispanic ethnicity on IMT progression. MESA is a unique cohort, because no previous cohort has had the ethnic diversity to demonstrate ethnic associations with IMT progression.5 We found a persistent and strong inverse effect of antihypertensive medications on progression of subclinical carotid disease. The strong protective effect of antihypertensive medication use is consistent with current knowledge of compensatory changes to arterial walls to elevated systemic blood pressures. In clinical trials, the use of antihypertensive medications is associated with decreased IMT progression.18,19 Based on these data, antihypertensive medication use may be the strongest modifiable predictor of slowing IMT progression over time. In contrast with antihypertensive medication use, statin medication use at baseline was weakly and positively associated with IMT progression; however, when modeled as a time-updated covariate, time on statin medication was inversely associated with IMT progression. Statin medication use at baseline may be a marker of an increased antecedent burden of CVD risk factors before study enrollment. We did not find a significant effect on plaque progression and use of statin medications.

Traditional CVD risk factors are associated with carotid plaque presence and burden; however, few studies have analyzed the predictors of carotid plaque progression over time.2022 In our study, current cigarette smoking was a strong predictor of new plaque across ethnicities. When risk of new plaque formation was adjusted for traditional CVD risk factors, Hispanic, blacks, and Chinese ethnicities had lower risks of new carotid plaque. These ethnic differences in carotid plaque progression are novel and clinically relevant findings because prior investigations were of whites. Our carotid plaque findings are similar to those in other arterial territories. In the coronary arteries, black ethnicity is associated with less calcification and slower calcium progression, despite more adverse risk factor profiles.23,24 In our study, black ethnicity was associated with thicker CCA IMT but with less carotid plaque formation than whites. Because of pathophysiological differences between arterial wall thickening and plaque formation, it is not surprising that the predictors for progression of these markers differ.

Limitations

As an observational study, the described associations do not confirm causation. Our participants were a subset of the MESA who returned for examination 5 and may be biased based on survival to this examination. Examination 5 participants were healthier and less likely to have a nonfatal CVD event than the original MESA cohort, which could have reduced the strength of the associations we identified. Carotid IMT and plaque progression are surrogate markers for CVD risk; however, they provide important insights into the pathophysiology of arterial injury, the substrate for cerebrovascular disease and cognitive decline. Carotid artery disease also is strongly associated with and reflective of changes in other arterial beds. This investigation focused on CCA IMT. Only half as many participants had ICA images available for analysis given the inability to match ICA segments across examinations, yet the results (online-only Data Supplements I and II) were similar. Although regression models were adjusted for measured risk factor and sociodemographic variables, unmeasured lifestyle exposures and risk factors that may be specific to each ethnicity cannot be accounted for. We cannot exclude a systematic error in measurement because of nonblinding; however, the random error associated with measuring such a small quantity on 1 examination would be the most prominent source of bias, rather than any systematic measurement bias. Any systematic measurement error that did occur would be nondifferential in nature and, therefore, would bias the results toward the null. Also, segments were traced with semiautomated border detection tool with minimal edits by the reader, except when interface determination by the software was incorrect. Finally, MESA is a US cohort, so the generalizability of these findings to populations outside the United States may be limited.

Conclusions

Ethnicity is associated independently with progression of carotid wall thickening and plaque formation, subclinical markers of arterial injury and CVD risk. The most powerful pharmacological and modifiable risk factors impacting progressive carotid wall injury are use of antihypertensive medications and cigarette smoking.

Acknowledgments

A full list of Multi-Ethnic Study of Atherosclerosis investigators and institutions can be found at http://www.mesa-nhlbi.org.

Footnotes

Presented in part at the American Heart Association Scientific Sessions, Dallas, TX, November 16–20, 2013.

The online-only Data Supplement is available with this article at http://stroke.ahajournals.org/lookup/suppl/doi:10.1161/STROKEAHA.114.005669/-/DC1.

Correspondence to James H. Stein, MD, University of Wisconsin School of Medicine and Public Health, 600 Highland Ave, Room H4/520 CSC (MC 3248), Madison, WI 53792. E-mail

References

  • 1. Stein JH, Korcarz CE, Hurst RT, Lonn E, Kendall CB, Mohler ER, et al; American Society of Echocardiography Carotid Intima-Media Thickness Task Force. Use of carotid ultrasound to identify subclinical vascular disease and evaluate cardiovascular disease risk: a consensus statement from the American Society of Echocardiography Carotid Intima-Media Thickness Task Force. Endorsed by the Society for Vascular Medicine.J Am Soc Echocardiogr. 2008; 21:93–111, quiz 189.CrossrefMedlineGoogle Scholar
  • 2. Lorenz MW, Markus HS, Bots ML, Rosvall M, Sitzer M. Prediction of clinical cardiovascular events with carotid intima-media thickness: a systematic review and meta-analysis.Circulation. 2007; 115:459–467.LinkGoogle Scholar
  • 3. Den Ruijter HM, Peters SA, Anderson TJ, Britton AR, Dekker JM, Eijkemans MJ, et al. Common carotid intima-media thickness measurements in cardiovascular risk prediction: a meta-analysis.JAMA. 2012; 308:796–803.CrossrefMedlineGoogle Scholar
  • 4. Espeland MA, O’Leary DH, Terry JG, Morgan T, Evans G, Mudra H. Carotid intimal-media thickness as a surrogate for cardiovascular disease events in trials of HMG-CoA reductase inhibitors.Curr Control Trials Cardiovasc Med. 2005; 6:3.CrossrefMedlineGoogle Scholar
  • 5. Herder M, Johnsen SH, Arntzen KA, Mathiesen EB. Risk factors for progression of carotid intima-media thickness and total plaque area: a 13-year follow-up study: the Tromsø Study.Stroke. 2012; 43:1818–1823.LinkGoogle Scholar
  • 6. Bots ML, Baldassarre D, Simon A, de Groot E, O’Leary DH, Riley W, et al. Carotid intima-media thickness and coronary atherosclerosis: weak or strong relations?Eur Heart J. 2007; 28:398–406.CrossrefMedlineGoogle Scholar
  • 7. Chambless LE, Folsom AR, Davis V, Sharrett R, Heiss G, Sorlie P, et al. Risk factors for progression of common carotid atherosclerosis: the Atherosclerosis Risk in Communities Study, 1987-1998.Am J Epidemiol. 2002; 155:38–47.CrossrefMedlineGoogle Scholar
  • 8. Inaba Y, Chen JA, Bergmann SR. Carotid plaque, compared with carotid intima-media thickness, more accurately predicts coronary artery disease events: a meta-analysis.Atherosclerosis. 2012; 220:128–133.CrossrefMedlineGoogle Scholar
  • 9. Bild DE, Bluemke DA, Burke GL, Detrano R, Diez Roux AV, Folsom AR, et al. Multi-ethnic study of atherosclerosis: objectives and design.Am J Epidemiol. 2002; 156:871–881.CrossrefMedlineGoogle Scholar
  • 10. Hollander M, Bots ML, Del Sol AI, Koudstaal PJ, Witteman JC, Grobbee DE, et al. Carotid plaques increase the risk of stroke and subtypes of cerebral infarction in asymptomatic elderly: the Rotterdam study.Circulation. 2002; 105:2872–2877.LinkGoogle Scholar
  • 11. Adar SD, Sheppard L, Vedal S, Polak JF, Sampson PD, Diez Roux AV, et al. Fine particulate air pollution and the progression of carotid intima-medial thickness: a prospective cohort study from the multi-ethnic study of atherosclerosis and air pollution.PLoS Med. 2013; 10:e1001430.CrossrefMedlineGoogle Scholar
  • 12. Yanez ND, Kronmal RA, Shemanski LR, Psaty BM; Cardiovascular Health Study. A regression model for longitudinal change in the presence of measurement error.Ann Epidemiol. 2002; 12:34–38.CrossrefMedlineGoogle Scholar
  • 13. Rundek T, Blanton SH, Bartels S, Dong C, Raval A, Demmer RT, et al. Traditional risk factors are not major contributors to the variance in carotid intima-media thickness.Stroke. 2013; 44:2101–2108.LinkGoogle Scholar
  • 14. O’Leary DH, Polak JF, Kronmal RA, Savage PJ, Borhani NO, Kittner SJ, et al. Thickening of the carotid wall. A marker for atherosclerosis in the elderly? Cardiovascular Health Study Collaborative Research Group.Stroke. 1996; 27:224–231.LinkGoogle Scholar
  • 15. Polak JF, Pencina MJ, Meisner A, Pencina KM, Brown LS, Wolf PA, et al. Associations of carotid artery intima-media thickness (IMT) with risk factors and prevalent cardiovascular disease: comparison of mean common carotid artery IMT with maximum internal carotid artery IMT.J Ultrasound Med. 2010; 29:1759–1768.CrossrefMedlineGoogle Scholar
  • 16. Dogan S, Duivenvoorden R, Grobbee DE, Kastelein JJ, Shear CL, Evans GW, et al; Radiance 1 and Radiance 2 Study Groups. Ultrasound protocols to measure carotid intima-media thickness in trials; comparison of reproducibility, rate of progression, and effect of intervention in subjects with familial hypercholesterolemia and subjects with mixed dyslipidemia.Ann Med. 2010; 42:447–464.CrossrefMedlineGoogle Scholar
  • 17. Dogan S, Plantinga Y, Crouse JR, Evans GW, Raichlen JS, O’Leary DH, et al; METEOR Study Group. Algorithms to measure carotid intima-media thickness in trials: a comparison of reproducibility, rate of progression and treatment effect.J Hypertens. 2011; 29:2181–2193.CrossrefMedlineGoogle Scholar
  • 18. Wang JG, Staessen JA, Li Y, Van Bortel LM, Nawrot T, Fagard R, et al. Carotid intima-media thickness and antihypertensive treatment: a meta-analysis of randomized controlled trials.Stroke. 2006; 37:1933–1940.LinkGoogle Scholar
  • 19. Tropeano AI, Saleh N, Hawajri N, Macquin-Mavier I, Maison P. Do all antihypertensive drugs improve carotid intima-media thickness? A network meta-analysis of randomized controlled trials.Fundam Clin Pharmacol. 2011; 25:395–404.CrossrefMedlineGoogle Scholar
  • 20. Gardener H, Della Morte D, Elkind MS, Sacco RL, Rundek T. Lipids and carotid plaque in the Northern Manhattan Study (NOMAS).BMC Cardiovasc Disord. 2009; 9:55.CrossrefMedlineGoogle Scholar
  • 21. Herder M, Johnsen SH, Arntzen KA, Mathiesen EB. Risk factors for progression of carotid intima-media thickness and total plaque area: a 13-year follow-up study: the Tromsø Study.Stroke. 2012; 43:1818–1823.LinkGoogle Scholar
  • 22. van der Meer IM, Iglesias del Sol A, Hak AE, Bots ML, Hofman A, Witteman JC. Risk factors for progression of atherosclerosis measured at multiple sites in the arterial tree: the Rotterdam Study.Stroke. 2003; 34:2374–2379.LinkGoogle Scholar
  • 23. Kronmal RA, McClelland RL, Detrano R, Shea S, Lima JA, Cushman M, et al. Risk factors for the progression of coronary artery calcification in asymptomatic subjects: results from the Multi-Ethnic Study of Atherosclerosis (MESA).Circulation. 2007; 115:2722–2730.LinkGoogle Scholar
  • 24. Bild DE, Detrano R, Peterson D, Guerci A, Liu K, Shahar E, et al. Ethnic differences in coronary calcification: the Multi-Ethnic Study of Atherosclerosis (MESA).Circulation. 2005; 111:1313–1320.LinkGoogle Scholar

eLetters(0)

eLetters should relate to an article recently published in the journal and are not a forum for providing unpublished data. Comments are reviewed for appropriate use of tone and language. Comments are not peer-reviewed. Acceptable comments are posted to the journal website only. Comments are not published in an issue and are not indexed in PubMed. Comments should be no longer than 500 words and will only be posted online. References are limited to 10. Authors of the article cited in the comment will be invited to reply, as appropriate.

Comments and feedback on AHA/ASA Scientific Statements and Guidelines should be directed to the AHA/ASA Manuscript Oversight Committee via its Correspondence page.