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Acute Coronary Syndrome Subphenotypes Based on Repeated Biomarker Measurements in Relation to Long-Term Mortality
Marie de Bakker1, Niels T B Scholte1, Rohit M Oemrawsingh2
1Department of Cardiology Erasmus MC, University Medical Center Rotterdam Rotterdam The Netherlands.
Insights
Identifying post-acute coronary syndrome (ACS) subphenotypes using repeated biomarker measurements reveals distinct long-term mortality risks. Persistently elevated biomarkers indicate the worst outcomes, regardless of recurrent ACS.
Area of Science:
- Cardiology
- Biomarker Research
- Clinical Trials
Background:
- Post-acute coronary syndrome (ACS) patient outcomes vary.
- Identifying distinct patient subphenotypes is crucial for risk stratification.
- Repeated biomarker measurements may offer insights into these subphenotypes.
Purpose of the Study:
- To identify subphenotypes of patients post-ACS using longitudinal biomarker data.
- To investigate the association between these subphenotypes and long-term mortality risk.
Main Methods:
- Observational study (BIOMArCS) with high-frequency blood sampling for 1 year in ACS patients.
- Cluster analysis of repeated measurements of cardiac troponin T, NT-proBNP, hs-CRP, and GDF-15.
- Accelerated failure time models used to evaluate all-cause mortality over a median of 9.1 years.
Main Results:
- Three distinct biomarker-based subphenotypes were identified: low/stable, decreasing, and persistently elevated concentrations.
- Persistently elevated biomarker concentrations (cluster 3) were associated with the highest long-term mortality risk.
- Patients with persistently elevated biomarkers had similar poor outcomes to those with recurrent ACS in the first year.
Conclusions:
- Subphenotypes of post-ACS patients with varying long-term mortality risks can be identified using repeated cardiovascular biomarker measurements.
- Persistently elevated biomarker levels are a strong indicator of adverse long-term outcomes, irrespective of early recurrent ACS.
Background:
We aimed to identify patients with subphenotypes of postacute coronary syndrome (ACS) using repeated measurements of high-sensitivity cardiac troponin T, N-terminal pro-B-type natriuretic peptide, high-sensitivity C-reactive protein, and growth differentiation factor 15 in the year after the index admission, and to investigate their association with long-term mortality risk.
Methods And Results:
BIOMArCS (BIOMarker Study to Identify the Acute Risk of a Coronary Syndrome) was an observational study of patients with ACS, who underwent high-frequency blood sampling for 1 year. Biomarkers were measured in a median of 16 repeated samples per individual. Cluster analysis was performed to identify biomarker-based subphenotypes in 723 patients without a repeat ACS in the first year. Patients with a repeat ACS (N=36) were considered a separate cluster. Differences in all-cause death were evaluated using accelerated failure time models (median follow-up, 9.1 years; 141 deaths). Three biomarker-based clusters were identified: cluster 1 showed low and stable biomarker concentrations, cluster 2 had elevated concentrations that subsequently decreased, and cluster 3 showed persistently elevated concentrations. The temporal biomarker patterns of patients in cluster 3 were similar to those with a repeat ACS during the first year. Clusters 1 and 2 had a similar and favorable long-term mortality risk. Cluster 3 had the highest mortality risk. The adjusted survival time ratio was 0.64 (95% CI, 0.44-0.93; P=0.018) compared with cluster 1, and 0.71 (95% CI, 0.39-1.32; P=0.281) compared with patients with a repeat ACS.
Conclusions:
Patients with subphenotypes of post-ACS with different all-cause mortality risks during long-term follow-up can be identified on the basis of repeatedly measured cardiovascular biomarkers. Patients with persistently elevated biomarkers have the worst outcomes, regardless of whether they experienced a repeat ACS in the first year.
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