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C-reactive protein improves risk prediction in patients with acute coronary syndrome, or does it?

Juan Carlos Kaski
DOI: http://dx.doi.org/10.1093/eurheartj/ehp435 274-277 First published online: 23 October 2009
This editorial refers to ‘C-reactive protein improves risk prediction in patients with acute coronary syndromes’, by F. Schiele et al. on page 290

Patients with acute coronary syndrome (ACS) represent a heterogeneous population. Both the severity of coronary artery disease and the extent of myocardial damage can differ markedly among patients presenting with ACS and these differences—in addition to age, left ventricular dysfunction, and the presence of co-morbidities—are likely to be responsible for different clinical outcomes in different patients. Accurate risk stratification of ACS patients continues to represent a major challenge to the managing physician.1,2 Established cardiovascular risk factors have been incorporated into algorithms for risk assessment in ACS patients and several clinical risk scores have been proposed in the past decade, which are promoted by International guidelines for management of patients with ACS.1,3 The Platelet glycoprotein IIb/IIIa in Unstable Angina: Receptor suppression Using Integrilin Therapy (PURSUIT),4 the Thrombolysis in Myocardial Infartion (TIMI),5 and the Global Registry of Acute Cardiac Events (GRACE)6 risk scores appear to be efficient prognostic indicators. However, they have limitations and physicians do not appear to have fully embraced the use of these scores in clinical practice.7,8 There is interest in the use of newer biomarkers, particularly those that have been shown to have independent prognostic value in different patient subgroups with coronary artery disease.9,10 The advent of biomarkers of inflammation, in particular high-sensitivity C-reactive protein, raised new hopes regarding improved prognostic algorithms in ACS.11 It has been speculated that the addition of C-reactive protein to other clinical variables encompassed by different risk scores can increase the prognostic ability of these clinical risk scores. In the general population, the use of a multimarker approach in different studies resulted in better risk prediction compared with single markers (Figure 1).12 In the Wang et al. study12 in over 3000 people attending the sixth examination of Framingham Offspring Study, subjects with high multimarker scores had a risk of death four times greater than those with low multimarker scores. However, as assessed by the C-statistic, the use of multiple biomarkers added only moderately to the overall prediction of risk based on conventional cardiovascular risk factors. C-reactive protein, in particular, predicted the risk of death but not of non-fatal cardiovascular events, after adjusting for other biomarkers. Folsom et al.13 reported similar negative findings in patients taking part in the ARIC (Atherosclerosis Risk in Communities) study.

Figure 1

Prognostic role of clinical risk scores and biomarkers of cardiovascular risk. Biomarkers of inflammation, high-sensitivity C-reactive protein in particular, have been suggested to improve the prognostic accuracy of clinical and electrocardiographic variables in patients with ACS. It has also been speculated that the use of biomics (i.e. genomics, proteomics, transcriptomics and metabolomics) data can improve prognosis further but this remains to be proven objectively in the clinical setting. In the general population, the use of a multimarker approach in different studies resulted in better risk prediction compared with single markers.12

Schiele et al.14 report the results of a study in ACS patients aimed at assessing whether the addition of C-reactive protein measurements gives incremental predictive value to the GRACE risk score.6 The goal of the study is laudable as discriminating between the wide differences in event rates among patients with ACS may be important in deciding the type, intensity, and timing of treatment. The study by Schiele et al.14 is the first to investigate—in ACS patients—the potential contributory role of a marker of inflammation to the various conventional markers of risk that comprise the GRACE risk score.6 In slightly over 1500 ACS patients, the authors confirmed an independent predictive role for C-reactive protein in ACS, as patients in the highest quartile of C-reactive protein showed increased mortality rates at 30 days of follow-up. Moreover, the study showed that the addition of C-reactive protein measurements improved global fit, discriminatory capacity, and calibration of the GRACE risk score model. These are important variables that define the clinical value of risk scoring instruments. The finding by Schiele et al. that combined with the GRACE risk score, a high C-reactive protein concentration improves risk classification is important and could represent a useful contribution to clinical patient management.

Several questions emerge, however, on analysing the results of this important study.

Can the study results be extrapolated to other acute coronary syndrome populations?

The Schiele et al. study assessed individuals entered in the ‘Registre Franc Comtois des Syndromes Coronariens Aigus’, a prospective ACS registry that includes patients admitted for ACS in cardiology centres in the region of Franche-Comté, in Eastern France comprising ∼1.2 million people. The study involved 1501 patients in whom C-reactive protein was measured and also had complete follow-up data (baseline C-reactive protein values were available in 74% of all patients admitted). The high C-reactive protein group—defined as patients with a C-reactive protein level above the third-quartile of the C-reactive protein distribution—represents a relatively small group. No indication was given in the manuscript as to whether different ethnic groups were represented equally in the study but this is unlikely to be the case. Whether findings in this subgroup with high C-reactive protein levels can be extrapolated to other ACS patients in other regions of the World and subjects belonging to other ethnic groups require further investigation.

This was a subgroup with unusually high C-reactive protein concentrations, older age, a high prevalence of co-morbidities, and compromised haemodynamic status at admission, who received suboptimal treatment according to guidelines.

What was the cause of such high C-reactive protein levels in these patients?

Patients with inflammatory conditions were not excluded from the study and it is therefore difficult to ascertain the cause of the very high C-reactive protein concentrations in these patients. The high-C-reactive protein group was defined by a C-reactive protein level >22 mg/L and the median value of C-reactive protein was 66 mg/L. As mentioned above, this group had more co-morbidities and worse haemodynamic condition compared with patients with lower C-reactive protein concentrations, which could have contributed to the surprisingly high C-reactive protein levels. Whether this increased inflammatory status is the expression of more aggressive coronary artery disease or the result of systemic inflammation associated with the various co-morbidities presented by these patients is difficult to ascertain. Irrespective of the cause of the increased C-reactive protein, however, the study showed that despite the presence of several confounding factors, high C-reactive protein levels were an independent marker for increased mortality. This perhaps indicates an additional contribution of inflammation—whether systemic of associated with vascular disease—to the pathogenesis and pathophysiology of the ACS, in this particular group of patients.

Incremental predictive value of GRACE risk score with the addition of C-reactive protein: would the assessment of other biomarkers have changed the study results?

The study showed that combined with the GRACE risk score, the assessment and inclusion of C-reactive protein in the risk model improves patient risk stratification. The risk reclassification after the introduction of high C-reactive protein levels showed that a proportion of patients were better categorized. This is an important finding in the study that may have clinical implications. However, the question emerges as to whether the addition of other serum biomarkers, B-type brain natriuretic peptide (BNP) measurements, for example, could have improved the model further. B-type brain natriuretic peptide has been shown in different studies to be an important predictor of cardiovascular risk in diverse clinical settings, including the ACS.12,15,16

It should be of clinical relevance to know if the modest additional predictive role of C-reactive protein found in the Schiele et al. study14 would be negated by the incorporation of BNP as an additional variable, particularly in the context of the GRACE risk score. One of the reasons why the additional contribution of C-reactive protein measurements to clinical risk scores and multimarker risk scoring algorithms has been shown to be modest in the present study14 and others12,13 is that C-reactive protein concentrations overlap markedly in individuals with stable and unstable cardiovascular disease. Moreover, risk factors and clinical biomarkers of cardiovascular risk exert their deleterious actions via increased oxidative stress and inflammation, thus sharing inflammatory pathways that lead to atherosclerotic heart disease. Consequently, C-reactive protein and many other inflammatory biomarkers give information that duplicates or overlaps that provided by other clinical variables usually assessed during patient characterization. Thus, although raised concentrations of inflammatory markers can be independent markers of cardiovascular risk, thus highlighting the importance of inflammation in the atherogenic process and disease progression, they will not necessary provide substantial incremental information over and above that supplied by conventional markers of risk. Perhaps, the selection of multiple biomarkers, reflecting unrelated pathogenic mechanisms, may provide better risk prediction.12 The SIESTA (Systemic Inflammation Evaluation in Patients with Non-ST Elevation ACS) study, which has adopted such an approach and is expected to fully report its findings in 2009, may shed some light on this issue.

Will these findings help improving effectiveness of treatment?

Although statistically significant, the improvement of risk classification allowed by the addition of C-reactive protein was modest in the Schiele study14 and achieved at the cost of an increase in the complexity of the score, as indicated by the authors. This is an important consideration and it remains to be seen if the practicing physicians will embrace this modified risk score. In my view, this will occur only if well-designed prospective studies show that the prompt initiation of high-dose statin treatment results in better clinical outcome in patients with high C-reactive protein levels otherwise receiving optimal conventional treatment. However, the prompt administration of high dose of statins should be part of the routine treatment of ACS, irrespective of both cholesterol and C-reactive protein levels. Hence, no major changes in treatment should be expected from the results in the Schiele et al. study,14 even in patients who are found to have very high levels of C-reactive protein. It is conceivable, however, that if specific anti-inflammatory interventions are identified in future trials and proven to be of clinical value, this would probably increase the role of markers of inflammation in the selection of patients who might benefit from such therapies, and the evaluation of their effects.

Conclusion

The important study by Schiele et al.14 has identified a possible role for C-reactive protein measurements in patients presenting with ACS, as it showed that the addition of C-reactive protein improves the predictive ability of the GRACE risk score in a subset of patients with markedly increased C-reactive protein concentrations. There are, however, several questions that remain unanswered by this interesting study and which need to be resolved before the approach proposed in the Schiele et al. trial can find a clinical application. Markers of inflammation have an independent value in risk stratification but their incremental contribution to current risk scoring algorithms seems to be very modest indeed. Perhaps, our search for better markers of risk in ACS should move away from inflammatory markers alone and include biomarkers that reflect different, unrelated, pathogenic pathways leading to the development and recurrence of the condition. Hopes are now placed on genetic markers, transcriptomics, proteomics, and metabolomics, which are expected to represent tools that may help us overcome the limitations we face at present. However, the challenge for these new markers will be to provide true, sizeable, incremental information over and above that provided by existing clinical markers of risk and help clinicians to improve patient management.

Footnotes

  • The opinions expressed in this article are not necessarily those of the Editors of the European Heart Journal or of the European Society of Cardiology.

  • doi:10.1093/eurheartj/ehp273

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