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European Heart Journal Advance Access originally published online on November 28, 2006
European Heart Journal 2006 27(24):2962-2968; doi:10.1093/eurheartj/ehl362
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© The European Society of Cardiology 2006. All rights reserved. For Permissions, please e-mail: journals.permissions@oxfordjournals.org

Impact of C-reactive protein and fibrinogen on cardiovascular prognosis in patients with stable angina pectoris: the AtheroGene study

Jan-Malte Sinning1, Christoph Bickel1, Claudia-Martina Messow2, Renate Schnabel3, Edith Lubos3, Hans J. Rupprecht3, Christine Espinola-Klein3, Karl J. Lackner4, Laurence Tiret5, Thomas Münzel3, Stefan Blankenberg3,* for the Athero Gene Investigators

1 Department of Medicine, Bundeswehrzentralkrankenhaus Koblenz, Germany
2 Institute of Medical Biostatistics, Epidemiology and Informatics (IMBEI), Johannes Gutenberg-University Mainz, Germany
3 Department of Medicine II, Johannes Gutenberg-University Mainz, Langenbeckstrasse 1, 55131 Mainz, Germany
4 Institute of Clinical Chemistry and Laboratory Medicine, Johannes Gutenberg-University Mainz, Germany
5 INSERM U525, Faculté de Médicine Pitié-Salpétrière Paris, France

Received 17 May 2006; revised 14 October 2006; accepted 20 October 2006; online publish-ahead-of-print 28 November 2006.

* Corresponding author. Tel: +49 6131 175169; fax: +49 6131 175691. E-mail address: blankenberg{at}2-med.klinik.uni-mainz.de


   Abstract
Top
 Abstract
Introduction
 Methods
 Results
 Discussion
 Appendix
 Acknowledgements
 References
 
Aims C-reactive protein and fibrinogen have been extensively studied and shown to be predictive for a first cardiovascular event in healthy individuals. We evaluated the potential clinical use of C-reactive protein and fibrinogen in patients already suffering from coronary artery disease (CAD).

Methods and results In a substudy of the prospective AtheroGene registry, we assessed in 1806 patients with documented CAD and stable angina pectoris, the risk of cardiovascular death and non-fatal myocardial infarction (n=183) over a median follow-up of 3.5 (maximum 7.7) years according to baseline levels of C-reactive protein and fibrinogen.

C-reactive protein and fibrinogen were associated with future cardiovascular events, such as an increment in one standard deviation of C-reactive protein is associated with a 1.15-fold (95% CI 1.05–1.27, P=0.002) increase, an increment of one standard deviation of fibrinogen with a 1.27-fold (95% CI 1.12–1.43, P<0.0005) increase in hazard risk in the models adjusted for age and sex. Adjustment for traditional risk factors and clinical confounders did not significantly attenuate this relationship. In a comparison of a basic model (traditional risk factors; AUC=0.68) with models additionally including either C-reactive protein (AUC=0.69) or fibrinogen (AUC=0.70), only little additional predictive information over that obtained from assessment of traditional risk factors was obtained.

Conclusion In patients with documented CAD, C-reactive protein and fibrinogen were predictive for future cardiovascular risk, but did not provide further information on top of that obtained from models including traditional risk factors. Our data emphasize the clinical importance of traditional risk factors in patients with CAD.

Key Words: C-reactive protein • Fibrinogen • Coronary artery disease • Stable angina pectoris • Risk factors • Prognosis


   Introduction
Top
 Abstract
 Introduction
Methods
 Results
 Discussion
 Appendix
 Acknowledgements
 References
 
Atherosclerosis is considered to be an inflammatory disease.1,2 Inflammatory vessel wall processes are causally involved in the destabilization of the atherosclerotic plaque and the enhancement of thrombus formation. These processes are not restricted to one particular atherosclerotic region, but rather represent widespread vessel damage.3 These findings have prompted the search for circulating biochemical markers reflecting inflammatory activity within the vascular wall. In addition to fibrinogen, which was one of the first inflammatory biomarkers related to future cardiovascular risk,4 C-reactive protein has been extensively studied and shown to be predictive for a first cardiovascular event in apparently healthy men and women.5,6 Other studies have shown that elevated levels of C-reactive protein are associated with future cardiovascular events in patients with stable and unstable coronary artery disease (CAD).7,8 Its clinical usefulness, however, has recently been challenged and some authors suggest that clinical guidelines recommending C-reactive protein measurement as independent risk factor may need to be reviewed.9–11

The ‘stable angina substudy’ of the prospective AtheroGene registry evaluates the predictive power of the inflammatory markers, C-reactive protein and fibrinogen, for a future cardiovascular event. We investigated the predictive value of these markers in patients with stable angina pectoris and determined their additive predictive value in comparison to a basic model including traditional risk factors.


   Methods
Top
 Abstract
 Introduction
 Methods
Results
 Discussion
 Appendix
 Acknowledgements
 References
 
Study population
A detailed description of the design of the AtheroGene study has been outlined previously.7 Between November 1996 and January 2004, 3173 patients who had undergone coronary angiography at the Department of Medicine II of the Johannes Gutenberg-University Mainz or the Bundeswehrzentralkrankenhaus Koblenz were enrolled in the AtheroGene registry. 150 patients without any evidence of angiographically visible stenosis as well as 282 patients with a subacute myocardial infarction were excluded. From the remaining 2741 patients who had at least one stenosis≥30% diagnosed in a major coronary artery, 1806 presented with stable angina pectoris and 935 with an acute coronary syndrome. In the latter group, 652 patients had unstable angina pectoris classified by Braunwald classification (Class B or C) and 283 had an acute myocardial infarction within the previous 48 h.

The 1806 remaining patients with stable angina pectoris were considered in these analyses. Of these 1806 patients, 1790 were followed up during a median period of 3.5 (maximum 7.7) years. Patients either presented themselves at our clinic (78.2%) or were interviewed over the phone by trained medical staff. Follow-up information including death from cardiovascular causes (n=131), death from causes not related to CAD (n=48), and non-fatal myocardial infarction (n=52) were obtained from hospital or general practitioners' charts.

Exclusion criteria were evidence of haemodynamically significant valvular disease, surgery or trauma within the previous month, known cardiomyopathy, known malignant diseases, febrile conditions, or use of oral anticoagulant therapy within the previous four weeks.

We considered that patients receiving medication for diabetes or whose current fasting blood glucose level was above 125 mg/dL suffer from diabetes mellitus. Patients receiving anti-hypertensive treatment or having already confirmed a diagnosis of hypertension (blood pressure above 160/90 mmHg) were considered to suffer from hypertension. Hyperlipoproteinaemia was diagnosed in patients under lipid-lowering medication or with a history of cholesterol levels≥240 mg/dL. Patients were classified as currently smoking, as having smoked in the past (if they had stopped more than 4 weeks and less than 40 years earlier), or as having never smoked or having stopped 40 or more years earlier.

Study participants had German nationality and, particularly, were inhabitants of the Rhein-Main Area. The study was approved by the local Ethics Committee. Participation was voluntary and each subject gave written informed consent.

Laboratory methods
Blood samples were taken under standardized conditions before coronary angiography was performed. Samples were centrifuged at 4000g for 10 min, divided into aliquots, and stored at –80°C until analysis. C-reactive protein was determined by a highly sensitive, latex particle-enhanced immunoassay (Roche Diagnostics; range of detection 0.1–20 mg/L; interassay coefficient of variation, 1.0% for values of 15 mg/L and 6.5% for values below 4 mg/L). Fibrinogen was determined by the derived method. Serum lipid levels were measured immediately. Lipid levels were measured using routine methods [total cholesterol and triglycerides, Roche Diagnostics GmbH, Mannheim, Germany; high-density lipoprotein cholesterol (HDL), Rolf Greiner Biochemica, Flacht, Germany; and low-density lipoprotein cholesterol (LDL) calculated according to the Friedewald formula7,12]. The LDL/HDL-ratio was computed by dividing LDL by HDL levels.

Statistical analysis
Due to skewed distribution (skewness>1) of the inflammatory markers, C-reactive protein and fibrinogen, differences of the baseline characteristics were assessed by log-normalized variables and the Mann–Whitney U test. Differences in proportions were evaluated by the {chi}2 test.

The cumulative survival plot in relation to the variables divided according to their quartiles was estimated by the Kaplan–Meier method, survival in groups was compared with the log-rank test. In all survival analyses, the combined endpoint was death from cardiovascular causes and non-fatal myocardial infarction (n=183), and data from patients who died of other causes were censored at the time of death.

The association of the inflammatory markers with outcome was also evaluated in different models by Cox regression, one model adjusting for age and sex and another one adjusting for the classical risk factors [age, sex, body mass index (BMI), hypertension, diabetes mellitus, smoking status, HDL-cholesterol, number of diseased vessels, lipid-lowering therapy, beta-blocker therapy]. Further the hazard ratio (HR) per one standard deviation increment was calculated. For further illustration, HRs estimated for the fourths of C-reactive protein and fibrinogen using the same models are presented. HR and 95% confidence interval (95% CI) are reported with two-tailed probability values. Proportional hazards assumption was checked using standard methods based on testing for significant slope of the smooth curve through the scatter of the rescaled Schoenfeld residuals vs. time.

To assess the predictive ability of the models, we considered the cardiovascular endpoint at 2 years as a binary variable, and logistic regression was performed. Associated receiver operating characteristic (ROC) curves for predicted probabilities were drawn for a basic model including classical risk factors and models additionally containing C-reactive protein and fibrinogen. The corresponding areas under the curve along with their 95% CIs were calculated. To obtain the best model fit in the regression analyses, C-reactive protein was log-transformed, age was entered as age3, BMI as 1/(BMI2), and HDL-cholesterol as 1/(HDL-cholesterol2).

As P-values are not adjusted for multiple testing they have to be considered as descriptive. All analyses were performed with the SPSS software, version 12.0.1 (SPSS Inc., Chicago, IL, USA), or R 2.1.0 (R Development Core Team, 2005).


   Results
Top
 Abstract
 Introduction
 Methods
 Results
Discussion
 Appendix
 Acknowledgements
 References
 
Baseline characteristics according to cardiovascular outcome
Table 1 outlines the baseline characteristics of the overall study population. 183 study participants subsequently died from cardiovascular causes or had a non-fatal myocardial infarction, 1623 patients did not have a cardiovascular event.


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  		Table 1 Baseline characteristics of the study population

 
As expected, patients who experienced a subsequent cardiovascular event were older, had a higher prevalence of traditional risk factors like hypertension, diabetes, smoking, elevated LDL and total cholesterol levels, as well as lower HDL cholesterol concentration. In addition, prevalence of patients taking lipid-lowering (890 patients under statin medication, 96 under fibrates, and two subjects taking both drugs) or beta-blocker medication was higher among those without cardiovascular event.

Baseline concentration of the inflammatory biomarkers, C-reactive protein (3.98 vs. 2.69 mg/L; P<0.0005) and fibrinogen (3.44 vs. 3.12 g/L; P<0.0005) was higher among those patients who experienced a cardiovascular event during follow-up compared with those who did not.

Prospective evaluation of C-reactive protein and fibrinogen on cardiovascular outcome
C-reactive protein and fibrinogen showed a moderate to strong interdependence (r=0.521). Both inflammatory markers were associated with future cardiovascular events if considered in univariate analysis. Highest event rates were observed in the upper quartiles with a 1.66-fold (95% CI 1.08–2.53) increase for the combined endpoint for C-reactive protein and a 1.92-fold (95% CI 1.22–3.03) risk for fibrinogen compared with the lowest quartile. After adjustment for potential confounders, C-reactive protein lost its independent predictive value, whereas fibrinogen still provided relevant risk information. In the fully adjusted model, the HRs across quartiles for C-reactive protein were 1, 1.09, 1.01, and 1.41 (P=0.25) and for fibrinogen 1, 0.99, 1.69, and 1.66 (P=0.02).

Subanalyses were carried out to evaluate the relationship between C-reactive protein and fibrinogen and future cardiovascular death as well as non-fatal myocardial infarction as separate endpoints. C-reactive protein and fibrinogen were associated with fatal events, but not significantly with non-fatal myocardial infarction. Detailed analyses are presented in Table 2.


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  		Table 2 HRs for follow-up events across quartiles of C-reactive protein and fibrinogen and HRs as well as P-value per increment of one standard deviation. Provided are age-/sex- and risk factor-adjusted HRs. Optimal transformations: age,3 1/(BMI2), 1/(HDL2)

 
Figure 1 displays the effect of C-reactive protein and fibrinogen on future cardiovascular events over time in Kaplan–Meier analyses.


Figure 3621
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  		Figure 1 Event-free survival according to quartiles of (A) C-reactive protein and (B) fibrinogen.

 
C-reactive protein and fibrinogen compared with traditional risk factors
To place the predictive value of C-reactive protein and fibrinogen into the context of traditional risk factors, we evaluated all variables in univariate and multivariate models. To directly compare the predictive power, the HRs associated with continuous variables are presented per increment standard deviation. As expected, the traditional risk factors such as age (HR 1.00; 95% CI 1.00–1.00; P=0.003), current smoking (HR 1.50; 95% CI 1.02–2.20; P=0.04), insulin-dependent diabetes mellitus (HR 1.82; 95% CI 1.17–2.83; P=0.001), and 1/(HDL-cholesterol levels2) (HR 1.12; 95% CI 1.01–1.25; P=0.04) were the strongest predictors of future cardiovascular events. C-reactive protein (HR 1.07; 95% CI 1.01–1.24; P=0.04) and fibrinogen (HR 1.16; 95% CI 0.99–1.35; P=0.06) remained moderately related to future cardiovascular events after adjustment for most potential confounders as outlined in Table 3.


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  		Table 3 HRs with 95% CI for traditional risk factors, C-reactive protein, and fibrinogen

 
Incremental effects of C-reactive protein and fibrinogen in addition to traditional risk factors
To explore whether C-reactive protein or fibrinogen added to traditional risk factor screening, we computed the area under the ROC curve (AUC) associated with prediction of different logistic regression models additionally including fibrinogen, C-reactive protein, or both considering the cardiovascular endpoints at 2 years as a binary variable. As there were patients with a follow-up of less than 2 years, only 1393 patients were available for this analysis; 89 of them experienced a cardiovascular event and had measurements of fibrinogen and C-reactive protein. A basic model including traditional risk factors such as age, sex, BMI, hypertension, diabetes mellitus, smoking status, HDL-cholesterol, number of diseased vessels, lipid-lowering and beta-blocker therapy revealed an AUC of 0.68. Figure 2 presents analyses comparing this basic model with models additionally including either C-reactive protein or fibrinogen, or both. Inclusion of either C-reactive protein or fibrinogen only modestly improved the predictive value of the basic model such as the AUC increase from 0.68 (95% CI 0.62–0.74) for the basic model to 0.69 (95% CI 0.63–0.75) for basic model plus C-reactive protein respective to 0.70 (95% CI 0.64–0.76) for basic model plus fibrinogen. Results were similar during a 1-year and 3-year follow-up (data not shown).


Figure 3622
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  		Figure 2 Incremental effects of C-reactive protein and fibrinogen in addition to the traditional risk factors.

 

   Discussion
Top
 Abstract
 Introduction
 Methods
 Results
 Discussion
Appendix
 Acknowledgements
 References
 
Our data indicate that traditional risk factors, which are simple and readily available, are the strongest risk predictors for future cardiovascular events. Although C-reactive protein and fibrinogen were individually related to future cardiovascular risk, they add little additional prognostic information to the traditional risk factors of CAD.

From a clinical perspective, recent data suggest the potential utility of C-reactive protein determination for risk stratification in healthy individuals. However, it is still a matter of ongoing controversy whether or not determination of C-reactive protein adds to the predictive value of traditional risk factors.13–16 Whereas initial data suggested that determination of C-reactive protein adds prognostic information at all levels of LDL-cholesterol and across the entire Framingham Risk Score,6,17,18 several more recent studies (including an updated meta-analysis) provided evidence that C-reactive protein is only a moderately strong predictor of coronary heart disease and does not add substantial, independent predictive information on future cardiovascular risk.9,11,19–21

The intensively discussed meta-analysis of Danesh et al.9 showed that the adjustment for traditional risk factors is very inhomogeneous and that there are many possibilities of confounding. After adjustment, levels of C-reactive protein did not add significant information to the traditional risk factors. In addition, a recent meta-analysis adds evidence for a moderately strong association between plasma fibrinogen levels and the risk of CHD, even after adjustment.22 In our study, which followed up patients with angiographically proven CAD, C-reactive protein and fibrinogen provided only little incremental predictive value in addition to the basic model. Although P-values were statistically significant a clinical relevance cannot be assumed from the slight increase in AUC analysis. The point of criticism that patients of the Reykjavik study had higher cholesterol and lower C-reactive protein levels than the current population does not hold true in our study of a contemporary western population.14 Whereas the Reykjavik study, the Women's Health Study, the Physicians' Health Study, and many others6,9,17,23–25 were investigating a population in times when the use of lipid-lowering agents was uncommon, our study analysed a group of patients, 55% (988/1790) of whom were taking statin medication at the time of blood sampling. Thus, the observational AtheroGene study mirrors a contemporary CAD population. However, our data suggest that statin medication does not considerably influence the relationship between C-reactive protein and outcome since adjustment for statin medication and stratified subanalyses (data not shown) does not affect the predictive value of C-reactive protein and fibrinogen. In extension to this observation, a recent study reports a persistent significance of C-reactive protein levels in predicting recurrent coronary events even after statin therapy, regardless of the resulting level of LDL-cholesterol.26 This would mean that it becomes difficult to derive therapeutic options with regard to an individual's C-reactive protein value.

In the more recent PRIME study, not only C-reactive protein but also fibrinogen lost its significance as predictor for myocardial infarction and coronary death, when it was adjusted for traditional risk factors, level of the correspondent inflammatory marker, and additionally for Interleukin-6.20 This observation is confirmed and extended in a recent substudy of the Framingham Heart Study, demonstrating that elevated C-reactive protein levels do not provide further prognostic information beyond traditional risk factor assessment for the prediction of major coronary heart disease.11 Similar were the findings from a population-based prospective study of elderly people that revealed a much stronger predictive effect for Nt-proBNP and negligible additional information gained from C-reactive protein.27 In our prospective population of secondary prevention, we can now contribute to this discussion and question the clinical importance of C-reactive protein measurement in the setting of CAD. Although C-reactive protein and fibrinogen are significantly related to future cardiovascular events in the present study, both variables did not provide a gain of information about future cardiovascular risk compared with a basic model including traditional cardiovascular risk factors. This is in accordance with recent data indicating that simple and, importantly, modifiable risk factors including the traditional risk factors and abnormal apolipoprotein concentrations account for about 90% of the risk of myocardial infarction.28–30

Several limitations of our study should be considered. First, we only performed baseline measurements and therefore cannot clarify the variability of the inflammatory markers during the course of the study. However, this limitation is likely to affect both traditional risk factors as well as the new biomarkers. Thus, it is possible that after correction for regression/dilution or other biases introduced due to measurement errors, the traditional markers may predict an even greater proportion of events. Second, we did not measure apolipoproteins that have been recently shown to be very powerful predictors of myocardial infarction.30,31 Thus, the traditional risk factors including apolipoproteins may be the preferred predictors of future CAD risk. Third, measurement of all inflammatory markers was performed on samples that were initially kept frozen. However, this should not affect the validity of our results, since cases and controls were handled identically, being measured in one batch.

The number of variables in the fully adjusted model is relatively high compared with the number of events and therefore should be interpreted carefully.

In the analyses of 2-year survival, the number of patients available is smaller than in the proportional hazards regression as there are patients with a follow-up of less than 2 years. As in this analysis, the actual survival time is not considered, results might be biased and should be interpreted as tendencies. We performed the same analyses for 1-year and 3-year survivals and the results are almost the same.

In conclusion, our data indicate that traditional risk factors provide the most powerful predictive information for cardiovascular events in patients already suffering from CAD. Although markers of overall inflammatory burden like C-reactive protein and fibrinogen are related to the future risk of CAD patients, they add only little information above that obtained from traditional risk factors. At present, modifying the traditional risk factors will have the greatest documented benefit in patients with cardiovascular disease.


   Appendix
Top
 Abstract
 Introduction
 Methods
 Results
 Discussion
 Appendix
Acknowledgements
 References
 
The AtheroGene Group: S.B., H.-J.R., C.B., C.E.-K., R.S., E.L., J.-M.S., Jürgen Meyer, Department of Medicine II, Johannes Gutenberg-University Mainz, Germany; L.T., Odette Poirier, Viviane Nicaud, David Tregouet, Jean-Louis Georges, Claire Perret, Tiphaine Godefroy, Francois Cambien, INSERM U525, Paris, France.

AtheroGene recruitment centres: Department of Medicine II, Johannes Gutenberg-University, Mainz, Germany, and Department of Medicine, Bundeswehrzentralkrankenhaus, Koblenz, Germany.


   Acknowledgements
Top
 Abstract
 Introduction
 Methods
 Results
 Discussion
 Appendix
 Acknowledgements
References
 
The authors thank Margot Neuser for drawing the diagrams. The AtheroGene study is supported by a grant of the ‘Stiftung Rheinland-Pfalz für Innovation’, Ministry of Science and Education (AZ 15202-386261/545), Mainz, Germany, and by a grant from the Fondation de France (no. 2002004994). S.B. was supported by a grant of the Institut National de la Santé et de la Recherche Médicale (INSERM), Paris, France.

Conflict of interest: none declared.


   References
Top
 Abstract
 Introduction
 Methods
 Results
 Discussion
 Appendix
 Acknowledgements
 References
 

  1. Libby P. (2002) Inflammation in atherosclerosis. Nature 420:868–874.[CrossRef][Medline]
  2. Lusis AJ. (2000) Atherosclerosis. Nature 407:233–241.[CrossRef][Medline]
  3. Buffon A, Biasucci LM, Liuzzo G, D'Onofrio G, Crea F, Maseri A. (2002) Widespread coronary inflammation in unstable angina. N Engl J Med 347:5–12.[Abstract/Free Full Text]
  4. Kannel WB, Wolf PA, Castelli WP, D'Agostino RB. (1987) Fibrinogen and risk of cardiovascular disease. The Framingham Study. JAMA 258:1183–1186.[Abstract]
  5. Pearson TA, Mensah GA, Alexander RW, Anderson JL, Cannon RO 3rd, Criqui M, Fadl YY, Fortmann SP, Hong Y, Myers GL, Rifai N, Smith SC Jr, Taubert K, Tracy RP, Vinicor F. (2003) Markers of inflammation and cardiovascular disease: application to clinical and public health practice: A statement for healthcare professionals from the Centers for Disease Control and Prevention and the American Heart Association. Circulation 107:499–511.
  6. Ridker PM and Cook N. (2004) Clinical usefulness of very high and very low levels of C-reactive protein across the full range of Framingham Risk Scores. Circulation 109:1955–1959.
  7. Bickel C, Rupprecht HJ, Blankenberg S, Espiniola-Klein C, Schlitt A, Rippin G, Hafner G, Treude R, Othman H, Hofmann KP, Meyer J. (2002) Relation of markers of inflammation (C-reactive protein, fibrinogen, von Willebrand factor, and leukocyte count) and statin therapy to long-term mortality in patients with angiographically proven coronary artery disease. Am J Cardiol 89:901–908.[CrossRef][ISI][Medline]
  8. Haverkate F, Thompson SG, Pyke SD, Gallimore JR, Pepys MB. (1997) Production of C-reactive protein and risk of coronary events in stable and unstable angina. European Concerted Action on Thrombosis and Disabilities Angina Pectoris Study Group. Lancet 349:462–466.[CrossRef][ISI][Medline]
  9. Danesh J, Wheeler JG, Hirschfield GM, Eda S, Eiriksdottir G, Rumley A, Lowe GD, Pepys MB, Gudnason V. (2004) C-reactive protein and other circulating markers of inflammation in the prediction of coronary heart disease. N Engl J Med 350:1387–1397.[Abstract/Free Full Text]
  10. Tall AR. (2004) C-reactive protein reassessed. N Engl J Med 350:1450–1452.[Free Full Text]
  11. Wilson PW, Nam BH, Pencina M, D'Agostino RB Sr, Benjamin EJ, O'Donnell CJ. (2005) C-reactive protein and risk of cardiovascular disease in men and women from the Framingham Heart Study. Arch Intern Med 165:2473–2478.[Abstract/Free Full Text]
  12. Bickel C, Rupprecht HJ, Blankenberg S, Espinola-Klein C, Rippin G, Hafner G, Lotz J, Prellwitz W, Meyer J. (2002) Influence of HMG-CoA reductase inhibitors on markers of coagulation, systemic inflammation and soluble cell adhesion. Int J Cardiol 82:25–31.[CrossRef][ISI][Medline]
  13. Foody JM, Gotto AM, Wenger N. (2004) C-reactive protein and coronary heart disease. N Engl J Med 351:295–298 (Author reply 295–298).[CrossRef][Medline]
  14. Glynn RJ and Cook NR. (2004) C-reactive protein and coronary heart disease. N Engl J Med 351:295–298 (Author reply 295–298).[CrossRef][Medline]
  15. Libby P, Willerson JT, Braunwald E. (2004) C-reactive protein and coronary heart disease. N Engl J Med 351:295–298 (Author reply 295–298).[CrossRef][Medline]
  16. Ridker PM, Koenig W, Fuster V. (2004) C-reactive protein and coronary heart disease. N Engl J Med 351:295–298 (Author reply 295–298).[CrossRef][Medline]
  17. Ridker PM, Buring JE, Shih J, Matias M, Hennekens CH. (1998) Prospective study of C-reactive protein and the risk of future cardiovascular events among apparently healthy women. Circulation 98:731–733.
  18. Pai JK, Pischon T, Ma J, Manson JE, Hankinson SE, Joshipura K, Curhan GC, Rifai N, Cannuscio CC, Stampfer MJ, Rimm EB. (2004) Inflammatory markers and the risk of coronary heart disease in men and women. N Engl J Med 351:2599–2610.[Abstract/Free Full Text]
  19. Folsom AR, Aleksic N, Catellier D, Juneja HS, Wu KK. (2002) C-reactive protein and incident coronary heart disease in the Atherosclerosis Risk In Communities (ARIC) Study. Am Heart J 144:233–238.[CrossRef][ISI][Medline]
  20. Luc G, Bard JM, Juhan-Vague I, Ferrieres J, Evans A, Amouyel P, Arveiler D, Fruchart JC, Ducimetiere P. (2003) C-reactive protein, interleukin-6, and fibrinogen as predictors of coronary heart disease: the PRIME Study. Arterioscler Thromb Vasc Biol 23:1255–1261.[Abstract/Free Full Text]
  21. Mendall MA, Strachan DP, Butland BK, Ballam L, Morris J, Sweetnam PM, Elwood PC. (2000) C-reactive protein: relation to total mortality, cardiovascular mortality and cardiovascular risk factors in men. Eur Heart J 21:1584–1590.[Abstract/Free Full Text]
  22. Danesh J. for Fibrinogen Studies Collaboration. (2005) Plasma fibrinogen level and the risk of major cardiovascular diseases and nonvascular mortality: an individual participant meta-analysis. JAMA 294:1799–1809.[Abstract/Free Full Text]
  23. Rosenson RS and Koenig W. (2002) High-sensitivity C-reactive protein and cardiovascular risk in patients with coronary heart disease. Curr Opin Cardiol 17:325–331.[CrossRef][ISI][Medline]
  24. Kuller LH, Tracy RP, Shaten J, Meilahn EN. (1996) Relation of C-reactive protein and coronary heart disease in the MRFIT nested case–control study. Multiple Risk Factor Intervention Trial. Am J Epidemiol 144:537–547.[Abstract/Free Full Text]
  25. Ridker PM, Hennekens CH, Buring JE, Rifai N. (2000) C-reactive protein and other markers of inflammation in the prediction of cardiovascular disease in women. N Engl J Med 342:836–843.[Abstract/Free Full Text]
  26. Ridker PM, Cannon CP, Morrow D, Rifai N, Rose LM, McCabe CH, Pfeffer MA, Braunwald E. (2005) C-reactive protein levels and outcomes after statin therapy. N Engl J Med 352:20–28.[Abstract/Free Full Text]
  27. Kistorp C, Raymond I, Pedersen F, Gustafsson F, Faber J, Hildebrandt P. (2005) N-terminal pro-brain natriuretic peptide, C-reactive protein, and urinary albumin levels as predictors of mortality and cardiovascular events in older adults. JAMA 293:1609–1616.[Abstract/Free Full Text]
  28. Doll R, Peto R, Boreham J, Sutherland I. (2004) Mortality in relation to smoking: 50 years' observations on male British doctors. BMJ 328:1519.[Abstract/Free Full Text]
  29. Turnbull F. (2003) Effects of different blood-pressure-lowering regimens on major cardiovascular events: results of prospectively-designed overviews of randomised trials. Lancet 362:1527–1535.[CrossRef][ISI][Medline]
  30. Yusuf S, Hawken S, Ounpuu S, Dans T, Avezum A, Lanas F, McQueen M, Budaj A, Pais P, Varigos J, Lisheng L. (2004) Effect of potentially modifiable risk factors associated with myocardial infarction in 52 countries (the INTERHEART study): case–control study. Lancet 364:937–952.[CrossRef][ISI][Medline]
  31. Pischon T, Girman CJ, Sacks FM, Rifai N, Stampfer MJ, Rimm EB. (2005) Non-high-density lipoprotein cholesterol and apolipoprotein B in the prediction of coronary heart disease in men. Circulation 112:3375–3383.

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