Biomarkers to Predict Recurrent Cardiovascular Disease: The Heart and Soul Study
Article Outline
Abstract
Purpose
The study purpose was to evaluate the ability of 6 biomarkers to improve the prediction of cardiovascular events among persons with established coronary artery disease.
Background
Cardiovascular risk algorithms are designed to predict the initial onset of coronary artery disease but are less effective in persons with preexisting coronary artery disease.
Methods
We examined the association of N-terminal prohormone brain natriuretic peptide (Nt-proBNP), cystatin C, albuminuria, C-reactive protein (CRP), interleukin-6, and fibrinogen with cardiovascular events in 979 Heart and Soul Study participants with coronary artery disease after adjusting for demographic, lifestyle, and behavior variables; cardiovascular risk factors; cardiovascular disease severity; medication use; and left ventricular ejection fraction. The outcome was a composite of stroke, myocardial infarction, and coronary heart disease death during an average of 3.5 years of follow-up.
Results
During follow-up, 142 participants (15%) developed cardiovascular events. The highest quartiles (vs lower 3 quartiles) of 5 biomarkers were individually associated with cardiovascular risk after multivariate analysis: Nt-proBNP hazard ratio (HR)
=2.13 (95% confidence interval [CI], 1.43-3.18); cystatin C HR=1.72 (95% CI, 1.10-2.70); albuminuria HR=1.71 (95% CI, 1.15-2.54); CRP HR=2.00 (95% CI, 1.40-2.85); and interleukin-6 HR=1.76 (95% CI, 1.22-2.53). When all biomarkers were included in the multivariable analysis, only Nt-proBNP, albuminuria, and CRP remained significant predictors of events: HR=1.88 (95% CI, 1.23-2.85), HR=1.63 (95% CI, 1.09-2.43), and HR=1.82 (95% CI, 1.24-2.67), respectively. The area under the receiver operator curve for clinical predictors alone was 0.73 (95% CI, 0.68-0.78); adding Nt-proBNP, albuminuria, and CRP significantly increased the area under the receiver operator curve to 0.77 (95% CI, 0.73-0.82, P<.005).
Conclusion
Among persons with prevalent coronary artery disease, biomarkers reflecting hemodynamic stress, kidney damage, and inflammation added significant risk discrimination for cardiovascular events.
Keywords: Albuminuria, Biomarkers, Cardiovascular events, Coronary artery disease, C-reactive protein, Cystatin C, Fibrinogen, Interleukin-6, N-terminal prohormone brain natriuretic peptide
Cardiovascular biomarkers have been extensively studied for the prediction of incident development of cardiovascular disease. Among the most studied are the inflammatory biomarkers, C-reactive protein (CRP), measures of hemodynamic stress, such as brain natriuretic peptide and N-terminal prohormone brain natriuretic peptide (Nt-proBNP), and the markers of kidney disease, albuminuria, and cystatin C. However, the utility of these biomarkers in the secondary prevention setting has been less well studied. These biomarkers provide important prognostic information beyond that attainable with traditional cardiovascular risk factors in the setting of acute coronary syndrome.1, 2 Whether the use of multiple biomarkers improves cardiovascular risk stratification in the outpatient setting among persons with coronary artery disease is unknown.
Traditional risk factors, such as cholesterol, hypertension, and smoking, may have less prognostic value in the secondary prevention setting than for primary prevention; in part this may result from the more aggressive management of these risk factors and the relative importance of heart disease severity as a risk factor for recurrent events.2 In patients with established coronary artery disease, biomarkers may have the ability to capture dynamic pathophysiologic processes, such as the hemodynamic function, stability of atherosclerotic plaque, and microvascular damage to the kidney, which are not assessed with standard clinical measurements. On the other hand, whether these markers provide unique predictive ability beyond traditional risk factors and standard clinical information remains unknown.
In this study, we evaluated the ability of biomarkers to predict the risk of cardiovascular death, myocardial infarction, or stroke among a cohort of 979 ambulatory persons with coronary artery disease who were enrolled in the Heart and Soul Study. We estimated the association of Nt-proBNP, cystatin C, albuminuria, CRP, interleukin (IL)-6, and fibrinogen with cardiovascular events after multivariable adjustment for standard clinical information and traditional cardiovascular risk factors. Finally, we identified the biomarkers that added the greatest predictive value in this cohort and calculated their incremental contribution to risk discrimination by plotting receiver operating characteristic (ROC) curves.
Methods
Participants
The Heart and Soul Study is a prospective cohort study designed to investigate the influence of psychosocial factors on coronary artery disease progression.3, 4 Participants were recruited from several outpatient clinics in the San Francisco Bay Area without age restriction if they met 1 of the following inclusion criteria:
A total of 15,438 eligible patients were mailed an invitation, and 2495 responded with interest; 505 were unreachable; and 596 declined. An additional 370 patients were excluded on the basis of recent myocardial infarction, inability to walk 1 block, or plans to relocate.
Between September 2000 and December 2002, 1024 individuals enrolled, including 549 (54%) with a history of myocardial infarction, 237 (23%) with a history of revascularization, and 238 (23%) with a physician diagnosis of coronary disease (based on a positive angiogram or treadmill test in>98% of cases). The age range of participants was 36 to 97 years. Participants underwent a day-long baseline study appointment that included a medical history interview, physical examination, resting echocardiogram, and comprehensive health status questionnaire. Fasting (12-hour) venous samples were drawn, and plasma and sera were frozen at −70°C. Frozen serum (n=34) and urine samples (n=11) were excluded for 45 subjects, resulting in a sample size of 979 participants.
Measurements
Clinical CharacteristicsCandidate clinical predictors included demographic (age, sex, race) and lifestyle characteristics (physical activity, body mass index, alcohol use, and current smoking); cardiovascular risk factors (self-reported hypertension and diabetes, systolic and diastolic blood pressure, low-density lipoprotein and high-density lipoprotein cholesterol, triglycerides, and hemoglobin); cardiovascular disease history (prior myocardial infarction, stroke, heart failure, and revascularization; echocardiographic measures of ejection fraction); and medication use (aspirin, beta-blockers, renin-angiotensin-aldosterone inhibitors, and statins). Age, race, physical activity, smoking and alcohol use, and medical history were determined by questionnaire. Participants were instructed to bring their medication bottles to the study appointment, and study personnel recorded all current medications.
BiomarkersBlood samples were drawn in the fasting state; serum and plasma were aliquoted and stored at −70°C until January of 2005. Biomarkers evaluated in this study were Nt-proBNP, cystatin C, albumin/creatinine ratio, CRP, IL-6, and fibrinogen.
We used the Roche Elecsys electrochemiluminescence immunoassay (Roche Diagnostics, Indianapolis, Ind) to measure plasma levels of NT-proBNP. Serum cystatin C was measured from frozen serum samples collected at the baseline study visit using a BNII nephelometer (Dade Behring, Inc, Deerfield, Ill) with a particle-enhanced immunonephelometric assay.5 Albumin and creatinine from 24-hour urine samples were measured by nephelometry and the rate Jaffe method, respectively. Urine albumin to creatinine ratios (milligrams of albumin/grams of creatinine) were calculated as the index of albuminuria as recommended by the National Kidney Foundation. High-sensitivity CRP was measured from serum using the Roche Integra assay and the Beckman Extended Range assay as previously described.6, 7 We used the R&D Systems Quantikine HS IL-6 Immunoassay (Minneapolis, Minn) to measure the concentration of serum IL-6. Plasma fibrinogen concentrations were determined by the Clauss assay.
Outcomes
The cardiovascular events outcome was defined as the time to coronary artery disease death, nonfatal myocardial infarction, or stroke. Coronary artery disease death was defined as death during the hospitalization in which an myocardial infarction was documented or death not explained by other causes that occurred within 1 hour of the onset of terminal symptoms.8 Nonfatal myocardial infarction was defined using standard diagnostic criteria set by the American Heart Association Council on Epidemiology and Prevention.9 Stroke was defined as a new neurologic deficit not known to be secondary to brain trauma, tumor, infection, or other cause.10
Annual telephone interviews were conducted with participants or their proxy to ask about interval death or hospitalization. Trained research assistants carried out the telephone interviews using standardized scripts that were reviewed with the study team on an annual basis for quality control. Quality control for determining outcome events was maintained as follows: for any reported event, medical records, electrocardiograms, death certificates, and coroner’s reports were required and reviewed by 2 independent and blinded adjudicators. If the adjudicators agreed on the outcome classification, their classification was binding. In the event of disagreement, the adjudicators conferred, reconsidered their classification, and requested consultation from a third blinded adjudicator as necessary.
Statistical Analysis
To model the outcome, we began by constructing a parsimonious standard clinical model. We elected a priori to force demographic characteristics and cardiovascular disease history into all of the models. Each lifestyle cardiovascular risk factor and cardiovascular medication variable was included if it had an association with the outcome (P<.2) in unadjusted analyses. This adjusted “clinical” model was then used as the base model to test the added prognostic information from the biomarkers.
The potential for multiple biomarkers to have independent prognostic value depends on the unique information they provide. Therefore, we began our analysis by determining the intercorrelations of these 6 biomarkers. We categorized the biomarkers into quartiles based on the precedent of prior studies from Heart and Soul.11, 12, 13 In addition, we used clinically applicable cutpoints for the biomarkers currently in common use: Nt-proBNP greater than 500 pg/mL, CRP greater than 3.0 mg/L, and albuminuria greater than 30 mg/g. We constructed multivariate proportional hazard models with each biomarker added individually to the clinical model, both as log-transformed linear variables and dichotomous variables (high quartile vs lower 3 quartiles), and using the clinical cutpoints where applicable. We then combined the biomarkers as linear variables along with the clinical multivariate model to allow them to compete as predictors; backward stepwise deletion identified those significant at P less than .05. This procedure was repeated for the dichotomized biomarkers.
Finally, we evaluated the global predictive ability of the standard clinical model for the cardiovascular outcome by computing the area under the curve (AUC) for the ROC curve.14 We repeated the ROC analysis with the addition of the independently predictive biomarkers identified above and compared the resulting AUC to determine statistical significance.
Results
Baseline Characteristics
A total of 979 individuals were included in the analysis. The mean age was 67 years; 82% were men and 60% were white. During an average follow-up of 3.7 years, 142 individuals had a cardiovascular event during follow-up, of which there were 87 myocardial infarctions, 26 strokes, and 50 coronary heart disease deaths.
Participants who experienced a cardiovascular event were on average 5 years older and more likely to have diabetes and hypertension, but less likely to smoke compared with participants without cardiovascular events. High-density lipoprotein cholesterol levels were lower in persons with cardiovascular events, but systolic blood pressure, low-density lipoprotein cholesterol complex, triglycerides, and body mass index were similar in the 2 groups. In addition, the participants with recurrent events had a greater prevalence of heart failure and reduced ejection fraction, and greater use of renin-angiotensin inhibitors (Table 1).
Table 1. Characteristics of the Study Sample According to the Development of Recurrent Cardiovascular Disease
| Characteristics | Cardiovascular Event (N=142) | No Events (N=837) | P Value |
|---|---|---|---|
| Demographic | Mean (SD) or N (%) | ||
| Age | 71.0(12.0) | 66.1(10.7) | <.0001 |
| Male | 121(85.2%) | 677(80.9%) | .22 |
| Race | .60 | ||
| White or Caucasian | 91(64.1%) | 498(59.6%) | |
| Black or African American | 23(16.2%) | 136(16.3%) | |
| Asian or Pacific Islander | 13(9.2%) | 100(12.0%) | |
| Hispanic, Latino, or Latin American | 9(6.3%) | 76(9.1%) | |
| Other group not listed | 6(4.2%) | 26(3.1%) | |
| Cardiovascular risk factor | |||
| Diabetes mellitus | 57(40.1%) | 202(24.2%) | .0001 |
| Current smoking | 31(22.0%) | 252(30.4%) | .04 |
| Hypertension (self-report) | 112(79.4%) | 577(69.1%) | .01 |
| Systolic blood pressure | 133.6(21.5) | 132.9(21.0) | .71 |
| Low-density lipoprotein | 103.2(34.2) | 104.4(33.9) | .71 |
| High-density lipoprotein | 43.5(14.0) | 46.1(14.0) | .04 |
| Triglycerides | 155.1(168.0) | 138.4(121.1) | .26 |
| Body mass index (kg/m2) | .46 | ||
| <25 | 38(26.8%) | 221(26.4%) | |
| 25-30 | 58(40.9%) | 349(41.7%) | |
| >30 | 46(32.4) | 267(31.9) | |
| Cardiovascular disease status | |||
| Prior myocardial infarction | 85(59.9) | 437(52.7) | .11 |
| Prior cerebrovascular accident | 27(19.0) | 112(13.5) | .08 |
| Prior heart failure | 38(26.8) | 133(16.0) | .002 |
| Ejection fraction<50% | 32(22.5) | 78(9.3) | <.0001 |
| Medication use | |||
| Aspirin | 112(78.9) | 646(77.2) | .66 |
| Angiotensin-converting enzyme inhibitors/angiotensin receptor blockers | 90(63.4) | 416(49.7) | .003 |
| Statins | 88(62.0) | 542(64.8) | .52 |
| Beta-blockers | 90(63.4) | 474(56.6) | .13 |
The intercorrelations among the 6 candidate biomarkers are presented in Table 2. Strong correlations (all>.4) were observed among the 3 inflammatory biomarkers, CRP, IL-6, fibrinogen, and between Nt-proBNP and cystatin C.
Table 2. Intercorrelations Among Six Biomarkers Measured in the Heart and Soul Cohort
| Nt-proBNP | Cystatin C | Albuminuria | CRP | IL-6 | Fibrinogen | |
|---|---|---|---|---|---|---|
| Nt-proBNP | 1.00 | 0.46 | 0.20 | 0.13 | 0.29 | 0.11 |
| <0.001 | <0.001 | <0.001 | <0.001 | <0.001 | ||
| Cystatin C | 1.00 | 0.30 | 0.15 | 0.28 | 0.26 | |
| <0.001 | <0.001 | <0.001 | <0.001 | |||
| Albuminuria | 1.00 | 0.06 | 0.11 | 0.17 | ||
| 0.07 | <0.002 | <0.001 | ||||
| CRP | 1.00 | 0.52 | 0.50 | |||
| <0.001 | <0.001 | |||||
| IL-6 | 1.00 | 0.41 | ||||
| <0.001 | ||||||
| Fibrinogen | 1.00 |
Greater risk differences from high to low quartiles were observed for Nt-proBNP (>459 pg/mL), cystatin C (>1.3 mg/L), albuminuria (>19.5 mg/g), CRP (>4.93 mg/L), and IL-6 (>4.2 mg/L) than fibrinogen (>443 mg/dL) (Figure 1). In unadjusted models, each biomarker had strong associations with the outcome either as a linear or a dichotomized variable (Table 3). In multivariate analyses, each biomarker was a linear predictor of the outcome. Nt-proBNP had the strongest association, and fibrinogen had the weakest association. When dichotomized at the high quartile (vs the lower 3 quartiles), each biomarker, except for fibrinogen, was an independent predictor of the outcome. When using clinical cutpoints, we found a similar association of Nt-proBNP with the outcome (hazard ratio: 2.25 [1.46-3.48]): a somewhat stronger association of albuminuria with the higher threshold (2.25 [1.45-3.50]) and a weaker association of CRP with the lower threshold (1.24 [0.85-1.80]).
Figure 1.
Cardiovascular event incidence rates per 1000 person-years across quartiles of Nt-proBNP, cystatin C, albuminuria, CRP, IL-6, and fibrinogen. Nt-proBNP
=N-terminal prohormone brain natriuretic peptide; CRP=C-reactive protein; IL=interleukin.
Table 3. Association of Individual Biomarkers with Recurrent Cardiovascular Events Among Persons with Coronary Artery Disease
| Linear Analysis (per SD)⁎ | High Quartile vs Lower Three Quartiles† | |||
|---|---|---|---|---|
| HR (95% CI) | P Value | HR (95% CI) | P Value | |
| Nt-proBNP | ||||
| Unadjusted | 2.13(1.82-2.51) | <.001 | 3.81(2.73-5.30) | <.001 |
| Adjusted‡ | 1.67(1.35-2.06) | <.001 | 2.13(1.43-3.18) | <.001 |
| Cystatin C | ||||
| Unadjusted | 1.59(1.42-1.78) | <.001 | 3.16(2.27-4.39) | <.001 |
| Adjusted‡ | 1.54(1.32-1.80) | <.001 | 1.72(1.10-2.70) | .02 |
| Albuminuria | ||||
| Unadjusted | 1.59(1.39-1.81) | <.001 | 2.87(1.90-4.34) | <.001 |
| Adjusted‡ | 1.39(1.18-1.63) | <.001 | 1.71(1.15-2.54) | .008 |
| CRP | ||||
| Unadjusted | 1.58(1.33-1.87) | <.001 | 2.58(1.80-3.69) | <.001 |
| Adjusted‡ | 1.52(1.26-1.82) | <.001 | 2.00(1.40-2.85) | <.001 |
| IL-6 | ||||
| Unadjusted | 1.77(1.50-2.10) | <.001 | 2.39(1.72-3.34) | <.001 |
| Adjusted‡ | 1.55(1.28-1.87) | <.001 | 1.76(1.22-2.53) | .003 |
| Fibrinogen | ||||
| Unadjusted | 1.44(1.21-1.71) | <.001 | 1.50(1.05-2.15) | .03 |
| Adjusted‡ | 1.26(1.04-1.52) | .02 | 1.15(0.78-1.69) | .48 |
⁎Linear analysis performed using log-transformed concentrations of biomarkers. |
†Cutpoints for high quartiles are as follows: Nt-proBNP |
‡Adjusted for age, sex, race, diabetes, body mass index, current smoking, prior myocardial infarction, cerebrovascular accident, chronic heart failure, ejection fraction |
In a backward selection model, Nt-proBNP, albuminuria, and CRP emerged as independent predictors of the outcome (Table 4). Because of the overlap between albuminuria and cystatin C, and between CRP and IL-6, we interchanged these pairs in the final model. When albuminuria was replaced, cystatin C had slightly weaker associations than albuminuria: 1.21 (95% confidence interval [CI], 1.01-1.45, P<.04) per standard deviation and 1.48 (95% CI, 1.00-2.19, P<.05) for the high quartile. IL-6, replacing CRP, had similar associations with CRP: 1.34 (95% CI, 1.09-1.63, P<.05) per standard deviation and 1.53 (95% CI, 1.05-2.23, P<.03) for the high quartile.
Table 4. Biomarkers Independently Associated with Recurrent Cardiovascular Events (N=786)
| Linear Analysis (per SD)⁎ | High Quartile | |||
|---|---|---|---|---|
| Adjusted HR†(95% CI) | P Value | Adjusted HR†(95% CI) | P Value | |
| Nt-proBNP | 1.44(1.15-1.80) | .002 | 1.88(1.23-2.85) | .003 |
| Albuminuria | 1.26(1.06-1.49) | .008 | 1.63(1.09-2.43) | .02 |
| CRP | 1.37(1.13-1.67) | .002 | 1.82(1.24-2.67) | .002 |
⁎Linear analysis performed using log-transformed concentrations of biomarkers. |
†Adjusted for age, sex, race, diabetes, body mass index, current smoking, prior myocardial infarction, cerebrovascular accident, chronic heart failure, ejection fraction |
To evaluate the incremental effect of the 3 significant biomarkers (Nt-proBNP, albuminuria, and CRP) on discrimination of risk for recurrent cardiovascular events, we compared the ROC curves for the standard clinical model with the same model including the 3 biomarkers (Figure 2). The AUC increased significantly from 0.73 (95% CI, 0.68-0.78) for the standard clinical model to 0.77 (95% CI, 0.73-0.82) for the biomarkers (P<.005).
Figure 2.
Receiver operator characteristic curves for the standard clinical model (dashed line) and the standard clinical model plus Nt-proBNP, albuminuria, and CRP (solid line). Nt-proBNP
=N-terminal prohormone brain natriuretic peptide; ACR = albuminuria; CRP=C-reactive protein; AUC=area under the curve.
Discussion
In this study among persons with prevalent coronary artery disease, we found that 5 biomarkers were significant predictors of cardiovascular events beyond standard clinical information: Nt-proBNP, cystatin C, albuminuria, CRP, and IL-6. After simultaneous adjustment for all 5 of these biomarkers, Nt-proBNP, albuminuria, and CRP emerged as independent predictors of cardiovascular events. Collectively, these biomarkers added a moderate but statistically significant improvement in discrimination of cardiovascular risk, as evidenced by the AUC of the ROC curve increasing from 0.73 to 0.77. These results suggest that markers of hemodynamic stress, kidney damage, and inflammation can augment risk prediction in persons with coronary artery disease.
Our findings complement and extend the previous literature on risk prediction among persons with coronary artery disease. In a study among 2763 women with stable coronary artery disease enrolled in the Heart and Estrogen Protection Study, Vittinghoff et al2 determined the most important predictors of myocardial infarction and coronary heart disease death during 7 years of follow-up. They found coronary artery disease severity (angina symptoms, number of myocardial infarctions, and heart failure history) and kidney dysfunction (estimated creatinine clearance<40 mL/min) to be as important predictors of recurrent events as the traditional cardiovascular risk factors, diabetes, hypertension, and abnormal lipoprotein levels.
Blankenberg et al15 evaluated 9 inflammatory biomarkers (CRP, fibrinogen, and IL-6, soluble tumor necrosis factor receptors 1 and 2, soluble IL-1 receptor antagonist, IL-18, soluble vascular adhesion molecule-1, soluble intercellular adhesion molecule-1, plus microalbuminuria and Nt-proBNP) in an analysis from the Heart Outcomes Prevention Evaluation trial. The analysis included 3199 persons (77% men) with either prevalent cardiovascular disease or diabetes, and used the same composite outcome as our study with a follow-up interval of 4.5 years. Although soluble IL receptor antagonist, fibrinogen, soluble intracellular adhesion molecule-1, and Nt-proBNP were independent predictors in the final model, only Nt-proBNP significantly improved the AUC of the ROC curve (0.65-0.69). Although the AUC of the clinical model was lower in Blankenberg and colleagues’ study than in our analysis, perhaps because the model did not include coronary heart disease severity or ejection fraction, both ROC curves improved by 0.04 (4% of the AUC) with the addition of biomarkers. Similarly, Rothenbacher and colleagues16 evaluated a cohort of 1051 patients with recent acute coronary syndrome (85% men) during a 4-year follow-up for the same outcome; the authors found that Nt-proBNP, CRP, and creatinine predicted the outcome, but that only Nt-proBNP improved the AUC of the ROC curve (0.69-0.71).
The 3 predominant biomarkers in this study represent unique pathologic mechanisms: hemodynamic stress, kidney damage, and inflammation. Incorporating these disparate biomarkers into a “multimarker strategy” has been discussed in the setting of acute coronary syndrome, for which clinical management is predominately determined by prognosis.17 Morrow and Braunwald17 suggested that an ideal scheme for risk stratification in patients with acute coronary syndrome might combine the traditional risk factors known to promote atherosclerosis (eg, hyperglycemia, dyslipidemia) with measures of inflammation (eg, CRP, IL-6), myocyte necrosis (troponins), hemodynamic stress (brain natriuretic peptide or Nt-pro-BNP), and renal dysfunction/vascular damage (creatinine, microalbuminuria). Our study suggests that a similar paradigm may be appropriate to represent risk for recurrent cardiovascular disease in the outpatient setting.
Although these biomarkers provided moderate improvement in the global risk prediction in the secondary prevention setting, the clinical importance of this increased discriminatory capacity is unknown, and its effect on patient management requires further study. Greater prognostic information among persons with coronary artery disease could be useful in evaluating the risk/benefit tradeoff of possible intervention strategies, in counseling patients about their prognosis, and in making decisions about noncardiovascular prevention strategies, such as cancer screening. The presence of elevated Nt-proBNP levels might lead to earlier initiation of angiotensin-converting enzyme inhibitors and beta-blockers, but the potential benefits of screening with Nt-proBNP have not been studied. Kidney damage detected by either increased albuminuria or cystatin C might trigger the use of renin-angiotensin-aldosterone inhibitors or more aggressive systolic blood pressure control, but such a strategy has not been evaluated. Inflammatory biomarkers such as CRP and IL-6 have been consistently predictive of cardiovascular outcomes, but they may not be modifiable in either primary or secondary prevention settings.
This study should be interpreted in the context of certain limitations. The cohort is predominately male, so our findings cannot necessarily be generalized to women. We measured 6 biomarkers in this study, but there may be others with greater predictive value for recurrent cardiovascular events. Because these biomarkers were only measured on entry into the Heart and Soul cohort, we do not know their levels at the time of their recurrent event.
Conclusions
We found that biomarkers reflective of hemodynamic stress, kidney disease, and inflammation added moderate but significant discrimination for recurrent cardiovascular events beyond readily available clinical information. Future studies should evaluate whether these or other biomarkers will have clinical utility for the management of patients with established coronary artery disease.
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The Heart and Soul Study was supported by grants from the Department of Veterans Affairs, the Robert Wood Johnson Foundation, the American Federation for Aging Research, the Ischemia Research and Education Foundation, and the Nancy Kirwan Heart Research Fund. Dade Behring, Inc, paid for the cystatin C measurements. Roche Diagnostics paid for the Nt-proBNP assays.
PII: S0002-9343(07)00844-3
doi:10.1016/j.amjmed.2007.06.030
© 2008 Elsevier Inc. All rights reserved.
