Prognostic utility of a multibiomarker panel in patients with suspected myocardial infarction. (3rd October 2022)

• Record Type: Journal Article
• Authors: Toprak, B; Weimann, J; Lehmacher, J; Soerensen, N A; Hartikainen, T S; Haller, P M; Schock, A; Karakas, M; Renne, T; Zeller, T; Blankenberg, S; Westermann, D; Twerenbold, R; Neumann, J T
• Is Part Of: European heart journal. Volume 43(2022)Supplement 2
• Publication Date: 2022-10-03
• Subjects: Cardiology -- Periodicals; Heart -- Diseases -- Periodicals; 616.12005
• DOI: 10.1093/eurheartj/ehac544.1318
• Languages: English
• ISSNs: 0195-668X

Abstract

Abstract: Introduction: Rapid and accurate evaluation of patients presenting with suspected myocardial infarction (MI) to the emergency department (ED) is crucial due to strongly varying outcomes in these patients. Despite the routine use of circulating biomarkers, among which high-sensitivity cardiac troponin currently dictates diagnostic protocols in chest pain patients, it still remains unclear which biomarkers are of highest utility for prognostic purposes in this patient collective. Purpose: We sought to investigate the prognostic utility of a multibiomarker panel with 29 different biomarkers in a contemporary cohort of patients with suspected MI by applying a dual analytical approach. Methods: The multibiomarker panel was measured in stored blood samples that were collected directly at admission from 748 prospectively enrolled patients who presented with symptoms suggestive of MI to the ED of a German tertiary center between 2013 and 2017. The final diagnosis of all patients was adjudicated according to the 4th Universal Definition of MI. The investigated endpoint comprised incident major cardiovascular events (MACE) within 1 year after admission. MACE was defined as the composite of cardiovascular death, non-fatal MI (excluding index events), revascularization and cardiac rehospitalization. Log-transformed biomarkers were entered individually into an age-and sex-adjusted Cox regression model to explore the hazard ratio (HR) per one standard deviation increase (SD) for 1-year MACE in the overall cohort. The selection of optimal multimarker models, adjusted for age and sex, was performed using 1) stepwise backward selection via Akaike information criterion as the stopping rule, and 2) Least Absolute Shrinkage and Selection Operator (LASSO) with 5-fold cross-validation. Results: Out of 748 patients with available multibiomarker panel, 138 (18.4%) were diagnosed with MI. Median age at admission was 64 (interquartile range [IQR] 50–75) years in the overall cohort, 63.1% were male. At 1 year of follow-up, 160 cases of incident MACE were documented. 16 of the investigated 29 biomarkers were significantly associated with 1-year MACE, amongst which NT-proBNP was the strongest predictor (HR per SD 1.74, 95% confidence interval [CI] 1.44–2.09, p<0.0001; Table 1). Using stepwise backward selection, three biomarkers including NT-proBNP, Apo A-I and Apo C-III remained in the final multivariable model (Figure 1). The LASSO approach confirmed NT-proBNP (HR per SD 1.24) and Apo A-I (HR per SD 0.98) as strong and independent predictors of 1-year MACE while Apo C-III was replaced with KIM-1 (HR per SD 1.06). Conclusions: Among 29 biomarkers, numerous provide prognostic utility while NT-proBNP and Apo A-I emerged as the strongest independent predictors of 1-year MACE. Their routine assessment and integration into risk prediction models may improve personalized risk stratification in patients with symptoms suggestive of MI. Funding Acknowledgement: Type of funding sources: Foundation. Main funding source(s): The BACC study was supported by the German Center for Cardiovascular Research, an unrestricted grant by Abbott Diagnostics, and Prevencio, which also partly covered the biomarker measurements.