Multiple marker approach to risk stratification in patients with stable coronary artery disease: to have or have not.

Individual biomarkers have expanding roles in risk assessment, diagnosis, and prognosis, and the list of up-and-coming markers is growing. Nonetheless, individual biomarkers have notable shortcomings, including day-to-day intra-individual variation and poor predictive values at the level of the individual patient, which limit their prognostic value. Combining multiple biomarkers from distinct pathophysiological pathways has the potential to overcome many of these pitfalls and to further improve risk stratification, and there has been a natural evolution towards studies evaluating such a multimarker approach. However, to date, a mixed picture has emerged on the clinical value of using multiple biomarkers for cardiovascular risk stratification. A number of studies have evaluated combinations of biomarkers for predicting cardiovascular disease in the community. Several have found statistically significant yet clinically modest improvements in prediction with a multimarker panel compared with a model with traditional risk factors alone. 3 A few, however, have found substantial improvements in risk prediction with a multimarker approach. –6 Secondary prevention populations have been the focus of even fewer studies evaluating a multimarker risk stratification approach. Blankenberg et al. studied 11 biomarkers [including nine inflammatory markers plus N-terminal pro-B-type natriuretic peptide (Nt-proBNP), and microalbuminuria] in 3199 patients with a history of coronary heart disease, peripheral vascular disease, diabetes, or stroke. After a mean 4.5 year follow-up, only Nt-proBNP provided incremental prognostic information for prediction of cardiovascular events compared with a traditional risk factor model, based on an increase in the area under the receiver-operating characteristic curve, or c-statistic. Although several inflammatory markers were significantly related to future cardiovascular risk, they added little additional prognostic information to the traditional markers. In this issue of the European Heart Journal, Schnabel et al. present findings of multimarker risk stratification from an additional secondary prevention population, based on 1781 consecutive patients with stable coronary artery disease from the AtheroGene cohort. For entrance into the study, patients had to be admitted with symptoms of possible coronary artery disease and have at least one major coronary artery with a stenosis of ≥30% at angiography; those with acute coronary syndrome were excluded. Patients were predominately male (78%) with a median age of 63 years. Twelve biomarkers of inflammation, lipid metabolism, renal function, vascular function, and haemodynamics/remodelling were evaluated individually for prediction of the combination of non-fatal myocardial infarction and cardiovascular death, an outcome that occurred in 137 subjects over a median follow-up of 3.6 years. The five markers that showed the strongest associations with cardiovascular events on Cox proportional hazards models, and that also had a significant integrated discrimination index (IDI), were Nt-proBNP, growth differentiation factor-15 (GDF-15), midregional pro-atrial natriuretic peptide (MR-proANP), cystatin C, and midregional pro-adrenomedullin (MR-proADM). Of the markers assessed, Nt-proBNP and GDF-15 were the strongest independent predictors of the combined outcome, and were the only two markers to show significant improvement in the net reclassification index (NRI). The authors found that the c-statistic increased with the addition of any of these five strongest markers to the established risk factors model, though the increases do not appear statistically significant, since the lower limit of the 95% confidence interval overlaps with the c-statistic of the baseline model in each case. The