Multimarker risk model containing troponin-T, interleukin 10, myeloperoxidase and placental growth factor predicts long-term cardiovascular risk after non-ST-segment elevation acute coronary syndrome

Objective: To evaluate the predictive value of seven biomarkers, which individually have been shown to be independent predictors, for use in a combined multimarker model for long-term cardiovascular outcome after non-ST-segment elevation acute coronary syndrome (NSTEACS). Design and Setting: Levels of high-sensitivity C-reactive protein (hsCRP), myeloperoxidase, pregnancy-associated plasma protein A, placental growth factor (PlGF), soluble CD40 ligand (sCD40L), interleukin 10 (IL-10) and troponin-T (TnT) were determined in patients enrolled in the CAPTURE trial. Cox proportional hazard regression analyses were applied to evaluate the relation between biomarkers and the occurrence of all-cause mortality or non-fatal myocardial infarction (MI). Patients: 1090 patients with NSTEACS. Main outcome measure: All-cause mortality and non-fatal MI during a median follow-up of 4 years. Results: The composite endpoint was reached by 15.3% of patients. Admission levels of TnT >0.01 μg/l (adjusted HR 1.8), IL-10 <3.5 ng/l (1.7), myeloperoxidase >350 μg/l (1.5) and PlGF >27 ng/l (1.9) remained significant predictors for the incidence of all-cause mortality or non-fatal MI after multivariable adjustment for other biomarkers and clinical characteristics, whereas hsCRP, pregnancy-associated plasma protein A and sCD40L were only associated with the endpoint in univariate analysis. A multimarker model consisting of TnT, IL-10, myeloperoxidase and PlGF predicted 4-year event rates that varied between 6.0% (all markers normal) and 35.8% (three or more biomarkers abnormal). Conclusion: In patients with NSTEACS, biomarkers characterising distinct aspects of the underlying atherosclerotic process and myocardial damage of the initial cardiac event can assist in predicting long-term adverse cardiac outcomes. The use of combinations of selected biomarkers adds incremental predictive value to further risk stratification in an otherwise seemingly homogeneous NSTEACS population.

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