NHLBI Workshop on C-Reactive Protein: Basic and Clinical Research Needs
July 10-11, 2006
Epidemiology of Markers of Inflammation and Cardiovascular Diseases —
Why C-Reactive Protein?
Traditional risk factors are a useful first step in determining who could be at risk for a coronary event. In the era of “global risk assessment” this should be done using one of the available scores, e.g. the Framingham score, the PROCAM score, or the SCORE score of the European Society of Cardiology, derived from multivariable statistical models. However, it has been noted that a considerable number of those at risk cannot be correctly identified on the basis of traditional risk factors. This has prompted the search for novel biomarkers to improve prediction of cardiovascular risk. Such markers could either be blood biomarkers relevant to the pathophysiology of atherosclerosis, e.g. representing inflammatory pathways, coagulation, platelet aggregation, lipoproteins or lipid-related variables, or genetic markers. On the other hand, markers of subclinical disease have emerged, that also could aid in improved risk prediction. The logical work-up of a subject therefore would consist in determining global risk based on traditional risk factors first. This would allow categorization into high (10 year risk >20%), low risk (10 year risk <10%) or intermediate risk (10-year risk of 10-20%). Those at intermediate risk would represent candidates for additional testing, to increase or decrease their estimated risk. Various blood biomarkers are available, but most of them are not yet suitable for the clinical routine for several reasons.
Atherosclerosis is characterized by a non-specific local inflammatory process which is accompanied by a systemic response. A large number of prospective studies in initially healthy subjects and in patients with manifest atherosclerosis have convincingly demonstrated a strong and independent association between even slightly elevated concentrations of various systemic markers of inflammation and several cardiovascular disease (CVD) endpoints. Presently, for C-reactive protein (CRP), the classical acute phase protein the largest data base is available. Prospective data have been reported in diverse populations including several ten-thousands of subjects from various ethnic groups. The measurement procedure is well standardised and automated, and high-sensitivity assays with sufficient precision are commercially available and have been approved by the FDA. Based on substantial evidence of a contribution of inflammation to atherothrombogenesis, the recent AHA/CDC consensus report from 2003 has recommended the measurement of CRP in asymptomatic subjects at intermediate risk for future coronary events (10-year risk of 10-20%) and in selected patients after an acute coronary syndrome. Furthermore, evidence suggests that measurement of CRP adds to global risk assessment based on the Framingham risk score. However, there is still a controversy regarding the clinical utility of CRP. This is based on several issues. First, a few epidemiological studies, like the Reykjavik Study have reported less strong associations with CVD with no incremental information of CRP above and beyond traditional risk factors. Second, the potential of incomplete adjustment still exists. Third, short-term variability and the lack of specificity may limit its use in clinical practice.
In conclusion, CRP is a strong, consistent and independent marker of future cardiovascular events. However, despite 10 years of intensive research, demonstration of the improvement of long-term risk prediction by CRP in those at intermediate risk has not been unequivocally established by current statistical approaches. Also, one has to consider the suboptimal use of scores and the incompleteness of included risk factors in these algorithms. Thus, we still need further data in diverse populations. Yet, most importantly, among all inflammatory biomarkers measured, CRP is the first to show some evidence of clinical utility. The CRP Collaboration Study Group may be able to resolve several of the remaining issues on the basis of individual patient data meta-analysis. Ultimately, studies are needed to demonstrate that changes in diagnostic classifications based on the additional measurement of CRP lead to changes in treatment that improve prognosis.
Back to Agenda
- Greenland P, Smith SC Jr, Grundy SM. Improving coronary heart disease risk assessment in asymptomatic people: role of traditional risk factors and noninvasive cardiovascular tests. Circulation. 2001;104:1863-7.
- Ridker PM. Clinical application of C-reactive protein for cardiovascular disease detection and prevention. Circulation. 2003;107:363-9.
- Koenig W, Lowel H, Baumert J, Meisinger C. C-reactive protein modulates risk prediction based on the Framingham Score: implications for future risk assessment: results from a large cohort study in southern Germany. Circulation. 2004;109:1349-53.
- Danesh J, Wheeler JG, Hirschfield GM, Eda S, Eiriksdottir G, Rumley A, Lowe GD, Pepys MB, Gudnason V. C-reactive protein and other circulating markers of inflammation in the prediction of coronary heart disease. N Engl J Med. 2004;350:1387-97.
- Boekholdt SM, Hack CE, Sandhu MS, Luben R, Bingham SA, Wareham NJ, Peters RJ, Jukema JW, Day NE, Kastelein JJ, Khaw KT. C-reactive protein levels and coronary artery disease incidence and mortality in apparently healthy men and women: The EPIC-Norfolk prospective population study 1993-2003. Atherosclerosis. 2005 Oct 27; [Epub ahead of print]
- Laaksonen DE, Niskanen L, Nyyssonen K, Punnonen K, Tuomainen TP, Salonen JT. C-reactive protein in the prediction of cardiovascular and overall mortality in middle-aged men: a population-based cohort study. Eur Heart J. 2005;26:1783-9.
- Malik S, Wong ND, Franklin S, Pio J, Fairchild C, Chen R. Cardiovascular disease in U.S. patients with metabolic syndrome, diabetes, and elevated C-reactive protein. Diabetes Care. 2005;28:690.
- Koenig W, Sund M, Frohlich M, Lowel H, Hutchinson WL, Pepys MB. Refinement of the association of serum C-reactive protein concentration and coronary heart disease risk by correction for within-subject variation over time: the MONICA Augsburg studies, 1984 and 1987. Am J Epidemiol. 2003;158: 357-64.