TY - JOUR
T1 - Acute Coronary Syndrome Subphenotypes Based on Repeated Biomarker Measurements in Relation to Long-Term Mortality Risk
AU - de Bakker, Marie
AU - Scholte, Niels T. B.
AU - Oemrawsingh, Rohit M.
AU - Umans, Victor A.
AU - Kietselaer, Bas
AU - Schotborgh, Carl
AU - Ronner, Eelko
AU - Lenderink, Timo
AU - Aksoy, Ismail
AU - van der Harst, Pim
AU - Asselbergs, Folkert W.
AU - Maas, Arthur
AU - Oude Ophuis, Anton J.
AU - Krenning, Boudewijn
AU - de Winter, Robbert J.
AU - The, S. Hong Kie
AU - Wardeh, Alexander J.
AU - Hermans, Walter
AU - Cramer, G. Etienne
AU - BIOMArCS Investigators †
AU - van Schaik, Ron H.
AU - de Rijke, Yolanda B.
AU - Akkerhuis, K. Martijn
AU - Kardys, Isabella
AU - Boersma, Eric
N1 - Publisher Copyright: © 2024, American Heart Association Inc.. All rights reserved.
PY - 2024/1/16
Y1 - 2024/1/16
N2 - 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.
AB - 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.
KW - Acute coronary syndrome
KW - Cardiovascular biomarkers
KW - Death
KW - Phenotypes
KW - Repeated measurements
UR - http://www.scopus.com/inward/record.url?scp=85182594171&partnerID=8YFLogxK
U2 - https://doi.org/10.1161/JAHA.123.031646
DO - https://doi.org/10.1161/JAHA.123.031646
M3 - Article
C2 - 38214281
SN - 2047-9980
VL - 13
SP - e031646
JO - Journal of the American Heart Association
JF - Journal of the American Heart Association
IS - 2
M1 - e031646
ER -