Abstract
Background
Although brachial artery flow-mediated dilation (FMD) predicts recurrent cardiovascular events, its predictive value for incident cardiovascular disease (CVD) events in adults free of CVD is not well established. We assessed the predictive value of FMD for incident CVD events in the Multi Ethnic Study of Atherosclerosis (MESA).
Methods and Results
Brachial artery FMD was measured in a nested case- cohort sample of 3026 out of 6814 subjects (mean ± SD age 61.2 ± 9.9 years), in MESA, a population-based cohort study of adults free of clinical CV disease at baseline recruited at six clinic sites in the USA. The sample comprised 50.2% females, 34.3% Caucasian, 19.7% Chinese, 20.8% African Americans and 25.1% Hispanics. Probability-weighted Cox proportional hazard analysis was used to examine the association between FMD and five years of adjudicated incident CVD events, including incident myocardial infarction, definite angina, coronary revascularization (coronary artery bypass grafting, percutaneous transluminal coronary angioplasty or other revascularization), stroke, resuscitated cardiac arrest and CVD death.
Mean (SD) FMD of the cohort was 4.4 (2.8) %. In probability-weighted Cox models, FMD/unit SD was significantly associated with incident cardiovascular events in both the univariate(adjusted for age and gender) [hazard ratio; 0.79(95% CI, 0.65–0.97), p=0.01], after adjusting for the Framingham Risk Score (FRS) [hazard ratio; 0.80(95%CI, 0.62–0.97), p=0.025] and also in multivariable models [hazard ratio; 0.84(95%CI, 0.71–0.99), p=0.04] after adjusting for age, gender, diabetes mellitus, cigarette smoking status, systolic blood pressure, HDL, LDL, triglycerides, heart rate, statin use and blood pressure medication use. The c statistic (AUC) of FMD, FRS, FRS + FMD) were 0.65, 0.74 and 0.74 respectively. Compared with the FRS alone, the addition of FMD to the FRS net correctly re-classifies 52% of subjects with no incident CVD event, but net incorrectly reclassifies 23% of subjects with an incident CVD event; an overall net correct re-classification of 29% (p < 0.001).
Conclusions
Brachial FMD is a predictor of incident cardiovascular events in population based adults. Even though the addition of FMD to the FRS did not improve discrimination of subjects at risk of CVD events in ROC analysis, it did improve the classification of subjects as low, intermediate and high CVD risk compared to the FRS.
Keywords: Endothelial dysfunction, brachial flow-mediated dilation, incident cardiovascular event, healthy adults
Introduction
The vascular endothelium plays a major role in the control of vasomotor tone, platelet adhesion and thrombosis (1). These functions of the vascular endothelium are in part due to the release of nitric oxide, prostaglandins and other vasoactive compounds (2). Brachial flow-mediated dilation (FMD) is a measure of the release of nitric oxide by the endothelium due to a transient flow stimulus (3). Impaired brachial FMD is widely regarded as an early, and potentially reversible, manifestation of vascular disease and may represent an integrated measure of the impact of various insults to the endothelium. (4–6).
Despite the wealth of data linking impaired FMD to cardiovascular disease (CVD) risk factors and improvements in FMD to various therapies(7,8), the data linking impaired FMD to subsequent clinical events are more limited and largely focused on studies in subjects with or at high risk for CVD events (9–14). Only one study by Shimbo et al. has focused on subjects free of cardiovascular disease (15). In this small study, there was an inverse association between impaired FMD and incident clinical CVD events; however the association did not persist after adjustment for other risk factors. More data are needed to determine the extent to which FMD may be a useful predictor of CVD risk in subjects free of cardiovascular disease and to determine if it offers incremental predictive value over conventional risk factors.
To clarify the association between brachial FMD and incident cardiovascular events in subjects free of clinically evident cardiovascular disease, we examined brachial FMD and incident cardiovascular events in a nested case-cohort subset of the Multi-Ethnic Study of Atherosclerosis (MESA).
Methods
Study Population and Data Collection
The study design for MESA has been published elsewhere (16). In brief, MESA is a prospective cohort study that began in July 2000 to investigate the prevalence, correlates and progression of subclinical CVD in individuals without known CVD at baseline. The cohort includes 6814 women and men aged 45–84 years old recruited from 6 US communities (Baltimore, Md; Chicago, Ill.; Forsyth County, N.C.; Los Angeles County, Calif.; northern Manhattan, N.Y.; and St. Paul, Minn.). MESA cohort participants were 38% white (n=2624), 28% black (n=1895), 22% Hispanic (n=1492), and 12% Chinese (n=803). Individuals with a history of physician diagnosed myocardial infarction, angina, heart failure, stroke, or transient ischemic attack, or who had undergone an invasive procedure for CVD (coronary artery bypass graft, angioplasty, valve replacement, pacemaker placement or other vascular surgeries) were excluded from participation. This study was approved by the Institutional Review Boards of each study site and written informed consent was obtained from all participants.
Demographics, medical history, anthropometric and laboratory data for the present study were taken from the first examination of the MESA cohort (July 2000-August 2002). Current smoking was defined as having smoked a cigarette in the last 30 days. Diabetes mellitus was defined as fasting glucose ≥ 126 mg/dl or the use of hypoglycemic medications. Use of antihypertensive and other medications was based on review of prescribed medication containers. Resting blood pressure was measured 3 times in the seated position, and the average of the second and third readings was recorded. Hypertension was defined as a systolic blood pressure ≥ 140 mmHg, diastolic blood pressure ≥ 90 mmHg, or use of medication prescribed for hypertension. Body mass index was calculated as weight (kg)/height (m2). Total and high-density lipoprotein cholesterol were measured from blood samples obtained after a 12-hour fast. Low-density lipoprotein cholesterol was estimated by the Friedewald equation (17).
Brachial flow-mediated dilation measurement
Brachial FMD was documented using ultrasound in the MESA cohort during the first examination. Participants were excluded from the FMD examination if they had uncontrolled hypertension (n=158), blood pressures in the left and right arms that differed by more than 15 mmHg, a history of Raynaud’s phenomenon (n=55), a congenital abnormality of the arm or hand (n=12), or a radical mastectomy on either side (n=100), resulting in 6489 participants that underwent the brachial FMD examination. Participants were examined in the supine position after 15 minutes rest and after at least a six-hour fast. An automated sphygmomanometer (Dinamap® device) was used to monitor blood pressure and pulse in the left arm at five-minute intervals throughout the exam. A standard blood pressure cuff was positioned around the right arm, 2 inches below the antecubital fossa, and the artery was imaged 5 to 9 cm above the antecubital fossa. A linear-array multifrequency transducer operating at 9 MHz (GE Logiq 700 Device) was used to acquire images of the right brachial artery. After obtaining baseline images, the cuff was inflated to 50 mmHg above the participant’s systolic blood pressure for 5 minutes. Digitized images of the right brachial artery were captured continuously for 30 seconds before cuff inflation, and for two minutes beginning immediately before cuff deflation to document the vasodilator response. A detailed description of the scanning and reading protocol can be found at the MESA website (www.mesa-nhlbi.org).
Brachial ultrasound videotapes from the subset of the MESA participants included in the current nested case-cohort sample (see below) were analyzed at the Wake Forest University Cardiology Image Processing Laboratory using a previously validated semi-automated system (18). The semi-automated readings (media-adventitial interfaces to media-adventitial interfaces) of these digitized images generated the baseline and maximum diameters of the brachial artery from which % FMD was computed.
Intra-reader reproducibility for baseline diameter, maximum diameter and % FMD was evaluated by comparing an original and a blinded quality control re-read of ultrasounds from 40 MESA participants (32 males, 18 Caucasians, 2 Chinese, 10 African American and 10 Hispanics). The intra-class-correlation coefficients were 0.99, 0.99 and 0.93 respectively. Intra-subject variability was evaluated by comparing results from repeated examinations of 19 subjects on two days a week apart. The Intra-class correlation coefficients for baseline diameter, maximum diameter and % FMD were 0.90, 0.90, and 0.54 respectively. Percent technical error of measurement was 1.39% for baseline diameter measurement, 1.47% for maximum diameter measurement and 28.4% for %FMD measurement.
Ascertainment of Cardiovascular Events
At intervals of 9 to 12 months, an interviewer contacted each participant by telephone to inquire about all interim hospital admissions, cardiovascular outpatient diagnoses, and deaths. To verify self-reported diagnoses, study personnel requested copies of all death certificates and medical records for all hospitalizations and outpatient cardiovascular diagnoses. Next-of-kin interviews were done for out-of-hospital cardiovascular deaths. Hospital records were obtained for an estimated 98% of hospitalized cardiovascular events, and some information was available for 95% of outpatient diagnostic encounters.
Hospital records that suggested possible cardiovascular events were abstracted by study personnel. The MESA coordinating center collated the abstracted or original endpoint records and sent them to 2 paired cardiologists, cardiovascular epidemiologists or neurologists for independent endpoint classification and assignment of incidence dates. If, after review and adjudication, disagreements persisted, a full Mortality and Morbidity Review Committee made the final classification.
Reviewers assigned a diagnosis of myocardial infarction based on combinations of symptoms, electrocardiographic findings, and cardiac biomarker levels. Death from CHD was classified as definite, probable or absent based on hospital records, death certificates and conversations with families. Definite fatal CHD required a myocardial infarction within 28 days of death, chest pain within 72 hours before death, or history of CHD, and the absence of a known nonatherosclerotic or noncardiac cause of death. If the definite fatal CHD criteria were not met, probable fatal CHD could be assigned with an underlying cause of death consistent with fatal CHD; this required the absence of a known nonatherosclerotic or noncardiac cause of death. Stroke required a focal deficit of >24 hours and was most instances confirmed by neuro-imaging. Stroke included subarachnoid hemorrhages, intraparenchymal hemorrhages, and brain infarctions. The definition of angina was adapted from the Women’s Health Initiative criteria and was classified by reviewers as definite, probable or absent. Definite or probable angina required clinical symptoms to be considered a MESA event, with definite angina requiring objective evidence of coronary atherosclerosis.
Definition of the Primary Outcome
For the purposes of this study a CVD event was defined as an incident myocardial infarction, definite angina, coronary revascularization (coronary artery bypass grafting and percutaneous coronary intervention), resuscitated cardiac arrest, stroke, or CVD death as defined by the MESA protocol.
Statement of Responsibility
The authors had full access to and take full responsibility for the integrity of the data. All authors have read and agree to the manuscript as written.
Nested Case-Cohort Sample and Statistical Analysis
Nested case-cohort study design has been shown to be very efficient, economical and their findings have been shown to be representative of the whole cohort studies (19). Even though 6489 participants had FMD measured, for cost reason only a subset (current cohort) had their tapes read and were included in the MESA FMD ancillary study.
A nested case-cohort of MESA participants involving a random sample of MESA participants (sub cohort, n=2844) and all those who had an adjudicated cardiovascular event by October 10th 2005 (cases, n=182) were included in this analysis. A single subject with a sex-specific FMD greater than six standard deviations above the mean was excluded. Descriptive data are presented as mean ±SD for continuous variables or the frequencies of subjects for categorical variables. To account for the sampling probabilities for the case cohort design, weighted survival curves (Cox model) and log-rank tests were used to compare the event-free survival rates for incident cardiovascular events among those above or below the sex-specific median % FMD. Similar analyses comparing event free-survival among those above and below the best threshold based on ROC analysis produced similar results (data not shown). Probability-weighted Cox proportional hazard models (20) were also used to evaluate the association between FMD treated as a continuous variable and survival free of the primary and various secondary outcomes with and without adjustment for potential confounding variables. Potential confounders were selected based on prior evidence of an association with FMD or CVD events from previous studies or statistical evidence of a univariate (age and gender adjusted) association with the primary outcome in the current study (a priori p ≤ 0.20). A stepwise procedure was used to identify the subset of these covariates that remained significantly associated with the primary outcome in a multivariate probability-weighted Cox proportional hazards model (the full model). The covariates retained in the fully adjusted models included: age, gender, diabetes mellitus, smoking status, systolic BP, use of blood pressure medication, HDL, LDL cholesterol, triglycerides, heart rate and statin use. In a separate model the Framingham Risk Score (21) was used as a single adjusting covariate.
We also examined the area under receiver operator curves (AUC) using probability-weighted Cox models to assess the individual and combined predictive accuracy of FMD and the Framingham Risk Score, for incident CVD events (22), and used probability-weighted Cox proportional hazards models to determine the potential for the addition of FMD to appropriately re-classify subjects into low, intermediate and high risk categories compared to the FRS (23). To compare the performance of the two different approaches (FRS vs. FRS+FMD) using a common strategy for assignment to risk category we first used a weighted logistic regression model of FRS alone to generate predicted probabilities for the primary outcome among those classified as low, intermediate and high risk by FRS. The absolute event rate cut points for the primary outcome between the three FRS risk categories were: low:< 4.0%, intermediate: 4.0–7.5%, high > 7.5%. We then used a similar model to generate predicted probability for the primary outcome using FRS and FMD and assigned subjects to low, intermediate or high risk using the same cut points obtained from the first model. This approach allowed us to use comparable absolute event rates for the primary outcome during the period of observation rather than extrapolating beyond what was actually observed.
All statistical analyses were performed using SAS version 9.1 or JMP version 7.0 (SAS Institute, Cary, N.C.).
Results
The demographic characteristics of the study sample are as shown in Table 1. Half (50.2%) of the cohort was female. There were 34.3% Caucasians, 19.7% Chinese, 20.8% African Americans and 25.1% Hispanics. A total of 182 (6.0%) subjects had an adjudicated CVD event over a maximum of five years [Incident rate of adjudicated CVD event in the entire MESA study (n=6814) was 2.6% over the five years of follow-up]. Traditional risk factors were higher in cases than the sub cohort (Table 1).
Table 1.
Demographic characteristics [mean ± SD or n (%)] of the subcohort (n=2843) and incident cases (n=182), MESA.
| Variables | Subcohort (n=2843) | Cases (n=182) |
|---|---|---|
| Age (years) | 60.8± 9.9 | 66.9± 9.2 |
| Female Gender (%) | 1451 (51.3) | 68(37.4) |
| Race (%) | ||
| Caucasians | 960(33.8) | 79(43.4) |
| Chinese | 579(20.4) | 18(9.9) |
| African Americans | 590(20.7) | 40(22.0) |
| Hispanics | 713(25.1) | 45(24.7) |
| BMI (Kg/M2) | 27.8 ±5.3 | 28.8± 5.3 |
| SBP (mmHg) | 124.1± 19.6 | 135.9± 21.2 |
| DBP (mmHg) | 71.8± 10.1 | 75.0 ±10.2 |
| Cholesterol (mmHg) | ||
| Total | 194.1± 34.9 | 197.0± 40.9 |
| HDL | 50.7± 14.5 | 48.1± 14.2 |
| LDL | 117.1± 30.2 | 119.5 ±35.6 |
| Triglycerides | 133.9± 96.4 | 147.3± 81.9 |
| Cigarette smoking (%) | ||
| Never | 1528(54.0) | 71(39.0) |
| Past | 978(34.6) | 80(44.0) |
| Current | 323(11.4) | 31(17.0) |
| Heart Rate (bpm) | 62.7± 9.1 | 64.2 ±11.7 |
| Diabetes mellitus (%) | 266(9.4) | 47 (25.8) |
| ACE Inhibitors Use (%) | 277(9.8) | 41(22.5) |
| HMG CoA use (%) | 381(13.5) | 48(26.4) |
| BP medication Use (%) | 845(29.7) | 95(52.2) |
| Brachial FMD (%) | 4.4± 2.8 | 3.4 ±2.5 |
| Brachial Diameter (mm) | 4.3± 0.8 | 4.7± 0.8 |
Subjects with sex-specific FMD responses higher than the median had fewer events than those with sex-specific FMD responses lower or equal to the median during 5 years of follow-up (log rank p-value <0.0001, Fig. 1). In univariate probability-weighted Cox proportional hazard analysis, FMD/unit SD was a significant predictor of CVD events [hazard ratio 0.61, 95% CI (0.51–0.72) p <0.0001]. In similar analyses FMD remained significantly associated with incident CVD events after adjusting for 1.) age [hazard ratio 0.70, 95%CI (0.60–0.85), p=0.001], 2) age and gender [hazard ratio 0.79, 95%CI(0.65–0.97), p=0.010] 3.) age, gender, diabetes, smoking status, LDL, HDL, triglycerides, systolic BP, use of hypertension medications, resting heart rate and statin use (the full model), and 3) the Framingham Risk Score [hazard ratio 0.80, 95%CI(0.63–0.97), p=0.025] (Fig. 2). Table 2 shows the hazard ratios of variables in the univariate (adjusted for age and gender) probability-weighted Cox model, the variables that made it into the multivariable model based on the a priori p value <0.20 and the hazard ratios of the variables in the multivariable probability-weighted Cox model.
Figure 1.
Weighted curves showing cumulative event-free survival stratified by FMD > or =/ < the sex-specific median value for the cohort (follow-up truncated at 1700 days due to small numbers of subjects at risk for follow-up > 1700 days).*indicates number at risk.
FMD: Brachial flow mediated dilation
CVD: Cardiovascular disease
Figure 2.
Probability-weighted Cox Proportional Hazard Ratios for nested models of FMD vs CVD events with and without cardiovascular risk factors and the Framingham Risk Score (FRS). * of change in FMD/ unit SD. ** adjusted for age, gender, diabetes mellitus, cigarette smoking, systolic blood pressure, blood pressure medication use,HDL, LDL cholesterol, triglycerides, heart rate and Statin use
FMD: Brachial flow-mediated dilation
FRS: Framingham Risk Score
Table 2.
Univariate (age and gender adjusted) and multivariable hazard ratios (probability weighted) and 95%CI for cardiovascular event incidence in relation to FMD and risk factors.
| Variable/ increment of hazard ratio. | Univariate Hazard Ratio (95%CI) | P value | Multivariable Hazard Ratio (95%CI) | P value |
|---|---|---|---|---|
| FMD/ unit SD | 0.79(0.65–0.97) | 0.010 | 0.84(0.71–0.99) | 0.04 |
| Age/ unit SD | 1.94(1.67–2.24) | <0.0001 | 1.87(1.41–2.46) | <0.0001 |
| Male Gender | 2.42(1.78–3.28) | <0.0001 | 2.19(0.83–5.39) | 0.12 |
| Caucasian | 1.05(0.92–1.20) | 0.46 | - | - |
| Diabetes mellitus | 1.30(1.20–1.40) | <0.0001 | 1.27(1.17–1.35) | <0.0001 |
| Systolic BP / unit SD | 1.40(1.19–1.65) | <0.001 | 1.31(1.05–1.64) | 0.02 |
| Total Cholesterol/unit SD | 1.24(1.07–1.45) | 0.040 | - | - |
| LDL Cholesterol/unit SD | 1.21(1.02–1.42) | 0.020 | 1.29(1.12–1.48) | 0.004 |
| HDL/unit SD | 0.78(0.64–0.96) | 0.020 | 0.93(0.54–1.59) | 0.78 |
| Triglycerides / unit SD | 1.10(1.04–1.18) | 0.001 | 0.94(0.84–1.05) | 0.36 |
| BMI/ unit SD | 1.12(0.94–1.42) | 0.40 | - | - |
| Heart Rate/unit SD | 1.30(1.11–1.52) | 0.001 | 1.22(1.06–1.42) | 0.007 |
| Cigarette Smoking | 1.45(1.16–1.81) | 0.001 | 1.41(1.09–1.83) | 0.009 |
| HMG CoA Use | 1.59(1.13–2.28) | 0.010 | 1.61(0.55–4.68) | 0.38 |
| ACE inhibitor Use | 1.81(1.25–2.64) | 0.001 | - | - |
| BP medication use | 2.30(1.74–3.05) | <0.0001 | 1.49(1.01–2.20) | 0.04 |
Footnote: - Indicates variables not included in the multivariable model. ACE inhibitor use is captured by BP medication use and total cholesterol also not included in full model because LDL was in the model. Replacing LDL by total cholesterol in the multivariable model resulted in similar risk estimates.
In stratified analyses, the inverse association between FMD and CVD events was similar across gender, smoking, hypertension and diabetes strata and there were no significant interactions between any of these predictors of CVD events and FMD in determining prognosis (data not shown). In a similar fashion, FMD was similarly associated with CVD events in all four ethnic groups; however, the confidence limits all included unity in fully adjusted models (Figure 3).
Figure 3.
Univariate* and multivariable**(full model) probability- weighted Cox proportional hazard ratios of change in FMD/unit SD vs CVD events stratified by ethnicity. Full model was adjusted for age, gender, diabetes mellitus, cigarette smoking, systolic blood pressure, blood pressure medication use,HDL, LDL cholesterol, triglycerides, heart rate and Statin use.
CVD: cardiovascular disease
FMD: flow mediated dilation
Significant associations were also observed between FMD/unit SD and the major elements of the primary outcome in univariate probability-weighted Cox proportional hazard analyses; and, despite reduced sample size, FMD remained significantly associated with both MI and CVD death in fully adjusted models (Table 3).
Table 3.
Hazard ratio (95%CI) of FMD/unit SD for the primary outcome (CVD events) and its major constituents* in probability-weighted univariate (adjusted for age and gender) and multivariable models**.
| Outcome | # Events | Univariate Hazard Ratio (95%CI) | P value | Multivariable Hazard Ratio (95%CI) | P value |
|---|---|---|---|---|---|
| Composite | 182 | 0.79(0.65–0.97) | 0.01 | 0.84(0.71–0.99) | 0.04 |
| Hard CHD | 75 | 0.65(0.44–0.96) | 0.01 | 0.74(0.56–0.97) | 0.02 |
| Myocardial Infarction | 64 | 0.72(0.41–0.97) | 0.04 | 0.74(0.55–1.00) | 0.05 |
| Coronary Revascularization | 103 | 0.81(0.52–0.94) | 0.03 | 0.85(0.63–1.06) | 0.15 |
| Definite Angina | 67 | 0.84(0.61–1.05) | 0.15 | 1.09(0.84–1.43) | 0.56 |
| Stroke | 36 | 0.81(0.42–1.23) | 0.23 | 0.87(0.56–1.42) | 0.58 |
| CVD Death | 20 | 0.42(0.18–0.95) | 0.04 | 0.51(0.22–0.98) | 0.05 |
Hard CHD: myocardial Infarction, Resuscitated cardiac arrest or CHD death
Resuscitated cardiac arrest not included (n=5)
adjusted for age, gender, diabetes, smoking status, systolic BP, use of blood pressure medication, HDL, LDL cholesterol, triglycerides, heart rate and Statin use
In ROC analyses, the c statistic (AUC) for a univariate model of FMD was 0.65 while the c statistic for a model containing the Framingham risk score was 0.74. Addition of FMD to the Framingham risk score or to our full model did not increase the c statistic 0.74 (Figure 4). Examination of the re-classification properties of FMD indicate that a risk model that adds FMD to the FRS net correctly re-classifies 52% of subjects with no incident CVD event, but net incorrectly reclassifies 23% of subjects with an incident CVD event. The overall net correct re-classification is 29% (p < 0.001 Table 4). In the FRS intermediate risk subgroup the net correct re-classification was similar (28%, p < 0.001)
Figure 4.
Receiver Operator Curves for the Framingham risk score (AUC=0.74), brachial FMD (AUC=0.65) and Framingham risk score + FMD (AUC=0.74) to predict incident CVD events.
FMD: Flow mediated dilation
AUC: area under the curve
Table 4.
Reclassification of subjects based on FRS+ FMD vs FRS alone
| FRS+FMD Risk Category | |||||||||
|---|---|---|---|---|---|---|---|---|---|
| Subjects with no incident CVD event | re- classified to higher risk | re-classified to lower risk | Net correct re- classification | ||||||
| low | intermediate | high | total | p-value | |||||
| low | 567 | 24 | 7 | 598 | 161 | 1644 | 52% | ||
| FRS risk category | intermediate | 1210 | 351 | 130 | 1691 | ||||
| high | 175 | 259 | 110 | 544 | |||||
| total | 1952 | 634 | 247 | 2833 | |||||
| FRS+FMD Risk Category | |||||||||
| Subjects with an incident CVD event | |||||||||
| low | intermediate | high | total | ||||||
| low | 16 | 5 | 1 | 22 | 32 | 74 | −23% | ||
| FRS risk category | intermediate | 44 | 32 | 26 | 102 | ||||
| high | 3 | 27 | 28 | 58 | |||||
| total | 63 | 64 | 55 | 182 | |||||
| Net re-classification improvement | 29% | < 0.001 | |||||||
| Net re-classification improvement (intermediate risk only) | 28% | < 0.001 | |||||||
FMD denotes brachial flow mediated dilation
FRS denotes Framingham Risk Score
Brachial artery diameter (height adjusted), was a significant predictor of CVD event is the univariate probability weighted Cox analysis [hazard ratio 1.52(95%CI, 1.34–1.72), p<0.0001], after adjusting for FRS [hazard ratio 1.307(1.14–1.50), p=0.029] but was not an independent predictor of events in our final model [hazard ratio 1.13(95%CI, 0.75–1.63), p=0.59) (Figure 5).
Figure 5.
Hazard Ratio (95%CI)for cardiovascular event for brachial diameter/ unit SD (height adjusted) in univariate and four multivariable models.
* FRS represents the Framingham risk score
**Full model was adjusted for age, gender, diabetes mellitus, cigarette smoking, systolic blood pressure, blood pressure medication use, HDL, LDL cholesterol, triglycerides, heart rate and Statin use
BD: brachial artery diameter (height adjusted)
The c statistic of brachial artery diameter was 0.64 and addition of brachial artery diameter also failed to increase the c statistic of the FRS (c statistics=0.74).
Discussion
The goal of this nested case-cohort study was to assess the predictive value of brachial FMD for incident cardiovascular events in population-based adults free of cardiovascular disease at baseline. Our study, which is the largest so far that has attempted to address this important topic, found that brachial FMD was significantly and inversely associated with incident cardiovascular events independent of other major cardiovascular risk factors. Brachial FMD was not better than, nor did it provide incremental discrimination to the FRS alone as a predictor of CVD events based on ROC analysis. However, it did provide a net improvement in the classification of subjects into low, intermediate or high risk categories compared with the FRS alone. These data provide additional evidence supporting the potential role of endothelial dysfunction in the pathogenesis of cardiovascular disease. However, until the findings of the present study are replicated in other cohorts and the variability of FMD is improved/eliminated, the authors of this paper will not recommend FMD as a clinical risk stratification tool.
The predictive value of brachial FMD for incident cardiovascular events in either high-risk subjects or subjects with recurrent cardiovascular events has been well explored, and findings are mixed. Some studies have shown an independent inverse association between brachial FMD and CVD events (9–12), but others have not (13, 14). A recent large meta-analysis suggested that the association between FMD and the estimated 10-year risk of coronary heart disease, assessed using the Framingham risk score, was strongest in the low risk populations compared with medium or high risk populations (24). There is, however, a paucity of data on the predictive value of brachial FMD for incident cardiovascular events in low-risk populations or subjects free of CVD at baseline. The study by Shimbo et al (15) attempted to address this question, but their findings were inconclusive due to small sample size and less ethnically diverse cohort compared with the USA population. In contrast, in the current study an inverse association between FMD and clinical CVD events remained significant after adjustment for multiple cardiovascular disease risk factors or for the FRS.
The consistency of the inverse association across risk factor and ethnicity strata (univariate) and across the various elements of the composite outcome provides additional reassurance of the internal validity of the observed association. However, the provocative observation of a nominal p-value of 0.05 for both MI and CVD death should be interpreted with caution given the small numbers of events and the post-hoc nature of these additional analyses.
The predictive accuracy of the Framingham risk score for incident CV events in the present study was good (AUC = 0.74), while the predictive accuracy of brachial FMD alone for incident CV event in the present study was fair at best (AUC = 0.65). Furthermore the addition of brachial FMD to the Framingham risk score model did not increase the model discrimination (AUC= 0.74) for incident CV events. However, despite that lack of discrimination value when considered across the full range of FMD values, when used to produce a categorical assignment to low, intermediate or high risk, FRS + FMD did offer an improvement over FRS alone - principally by identifying intermediate risk subjects that are less likely to have an incident CVD event in the subsequent 5 years of follow-up. Based on these data, it is tempting to conclude that FMD could therefore be used to screen intermediate risk subjects in order to clarify whether or not to initiate more aggressive preventive interventions. However, before such a clinical strategy could be generally recommended, several other things are required including 1. Confirmation that modifying clinical decisions based on FMD indeed results in a more favorable outcome than treatment decisions based solely on the FRS alone, 2. Assessment of the cost of the additional FMD testing required to produce the potential net improvement in outcomes, and 3. A determination of the feasibility of implementing FMD on a wide scale in clinical practice. Given the technical nature of the current FMD image acquisition and analysis techniques it seems implausible that it could be successfully deployed on a wide scale and in a cost-effective fashion. However, these data do provide additional incentives to search for other simple, reproducible and inexpensive strategies to evaluate endothelial function, or other biomarkers, that could be considered as an adjunct to conventional cardiovascular disease screening. Recently, similar improvements in risk classification have been observed with the use of CRP and parental history of heart disease (25, 26).
We showed in the Cardiovascular Health Study (12) that brachial artery diameter (height adjusted) was similar in predictive value and accuracy to brachial FMD for cardiovascular events in older adults. We hypothesized that brachial artery diameter may also be a measure of endothelial function and questioned the utility of whole brachial FMD measurement if brachial artery diameter (which is less variable and easy to measure) provides comparable information to brachial FMD. In the current study, brachial artery diameter (height adjusted) also showed a similar but inverse association with incident CV events in the univariate model but failed to achieve statistical significance in the multivariable model unlike FMD. The exact nature of the relationship between brachial artery diameter and cardiovascular risk warrants further investigation.
The current study has the following limitations. Endothelial-independent vasodilation following nitroglycerin administration was not examined due to the risk-benefit considerations of nitroglycerin administration in a population-based cohort study. Thus, we cannot determine whether impaired flow-mediated responses were the result of abnormal endothelial production, release and delivery of nitric oxide to the vascular smooth muscle or the result of impaired ability of the vascular smooth muscle to respond to nitric oxide (a non-endothelial dependant effect). However, other studies have consistently documented the specificity of FMD to the endothelium (27) and, regardless, the associations with CVD events and the effect on reclassification remain valid. The current study consists of population based adults free of clinical cardiovascular events at baseline. The findings of the present study should not be extrapolated to other dissimilar samples. Lastly, even though sonographers were centrally trained and standardized FMD measuring protocols were employed at all study sites, the re-test and re-read performance measures indicate considerable within-subject variability. In addition, FMD was also measured once in this population based study, even though multiple measurements have been shown to improve its variability. This variability limits the resolution possible for estimating effect sizes and likely obscures other important relationships between FMD, conventional CVD risk factors and cardiovascular risk.
Conclusion
Brachial FMD is a predictor of incident cardiovascular events in population-based adults free of clinical CVD at baseline. FMD in isolation or in addition to FRS did not improve overall discrimination of subjects at risk for a future events based on ROC analysis. However, FMD did provide significant improvement in classification of subjects as low, intermediate or high risk compared to FRS alone. These data provide justification for additional research on the utility of FMD and other measures to enhance the management of subjects at risk for cardiovascular disease.
Clinical Perspective
Since Celermajer et al introduced brachial flow-mediated dilation (FMD) testing as a measure of endothelial function; numerous studies have associated FMD with cardiovascular risk factors. Some authors have even hypothesized that FMD is a “barometer” of cumulative cardiovascular insult to the vascular endothelium; implying that accurate measurement of FMD will in fact be an important way of assessing global cardiovascular risk. Current methods of FMD measurement coupled with unknown biologic factors that influences the acquisition has contributed to the variability of FMD. Despite the variability, FMD has been shown to be predictive of cardiovascular events in elderly and high risk cohorts. Data on the predictive value of FMD in subjects free of cardiovascular events and low cardiovascular risk cohorts are limited. The present study uses the largest cohort so far studied and showed that FMD predicts incident cardiovascular events in population based adults free of clinical cardiovascular disease. Like other new biomarkers, the addition of FMD to the Framingham risk score (FRS) did not improve the discriminative ability of the FRS for cardiovascular events in this population in ROC analysis. However, re-classification analysis showed that the addition of FMD to FRS net re -classified 29% of subjects in this cohort correctly as low, intermediate and high risk compared with FRS alone. The addition of FMD to FRS mainly improved the net re -classification of the intermediate risk group (28%); a group that the FRS has been less accurate in classifying. Standardization and studies addressing the variability of FMD are needed.
Acknowledgments
Funding/ Support: This research was supported by contracts N01-HC-95159 through N01-HC-95166, and N01-HC-95169, and grants NHLBI T32 HL076132, all from the National Heart, Lung and Blood Institute, Bethesda, MD.
Footnotes
Conflict of Interest Disclosure: None of the authors has any conflict of interest
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