TY - JOUR
T1 - Heart failure subphenotypes based on repeated biomarker measurements are associated with clinical characteristics and adverse events (Bio-SHiFT study)
AU - de Lange, Iris
AU - Petersen, Teun B.
AU - de Bakker, Marie
AU - Akkerhuis, K. Martijn
AU - Brugts, Jasper J.
AU - Caliskan, Kadir
AU - Manintveld, Olivier C.
AU - Constantinescu, Alina A.
AU - Germans, Tjeerd
AU - van Ramshorst, Jan
AU - Umans, Victor A. W. M.
AU - Boersma, Eric
AU - Rizopoulos, Dimitris
AU - Kardys, Isabella
N1 - Funding Information: This work was supported by the Jaap Schouten Foundation and the Noordwest Academie . The funding sources had no role in the study design; in the collection, analysis and interpretation of data; in the writing of the report; and in the decision to submit the article for publication. Publisher Copyright: © 2022 The Authors
PY - 2022/10/1
Y1 - 2022/10/1
N2 - Background: This study aimed to identify heart failure (HF) subphenotypes using 92 repeatedly measured circulating proteins in 250 patients with heart failure with reduced ejection fraction, and to investigate their clinical characteristics and prognosis. Methods: Clinical data and blood samples were collected tri-monthly until the primary endpoint (PEP) or censoring occurred, with a maximum of 11 visits. The Olink Cardiovascular III panel was measured in baseline samples and the last two samples before the PEP (in 66 PEP cases), or the last sample before censoring (in 184 PEP-free patients). The PEP comprised cardiovascular death, heart transplantation, Left Ventricular Assist Device implantation, and hospitalization for HF. Cluster analysis was performed on individual biomarker trajectories to identify subphenotypes. Then biomarker profiles and clinical characteristics were investigated, and survival analysis was conducted. Results: Clustering revealed three clinically diverse subphenotypes. Cluster 3 was older, with a longer duration of, and more advanced HF, and most comorbidities. Cluster 2 showed increasing levels over time of most biomarkers. In cluster 3, there were elevated baseline levels and increasing levels over time of 16 remaining biomarkers. Median follow-up was 2.2 (1.4–2.5) years. Cluster 3 had a significantly poorer prognosis compared to cluster 1 (adjusted event-free survival time ratio 0.25 (95%CI:0.12–0.50), p < 0.001). Repeated measurements clusters showed incremental prognostic value compared to clusters using single measurements, or clinical characteristics only. Conclusions: Clustering based on repeated biomarker measurements revealed three clinically diverse subphenotypes, of which one has a significantly worse prognosis, therefore contributing to improved (individualized) prognostication.
AB - Background: This study aimed to identify heart failure (HF) subphenotypes using 92 repeatedly measured circulating proteins in 250 patients with heart failure with reduced ejection fraction, and to investigate their clinical characteristics and prognosis. Methods: Clinical data and blood samples were collected tri-monthly until the primary endpoint (PEP) or censoring occurred, with a maximum of 11 visits. The Olink Cardiovascular III panel was measured in baseline samples and the last two samples before the PEP (in 66 PEP cases), or the last sample before censoring (in 184 PEP-free patients). The PEP comprised cardiovascular death, heart transplantation, Left Ventricular Assist Device implantation, and hospitalization for HF. Cluster analysis was performed on individual biomarker trajectories to identify subphenotypes. Then biomarker profiles and clinical characteristics were investigated, and survival analysis was conducted. Results: Clustering revealed three clinically diverse subphenotypes. Cluster 3 was older, with a longer duration of, and more advanced HF, and most comorbidities. Cluster 2 showed increasing levels over time of most biomarkers. In cluster 3, there were elevated baseline levels and increasing levels over time of 16 remaining biomarkers. Median follow-up was 2.2 (1.4–2.5) years. Cluster 3 had a significantly poorer prognosis compared to cluster 1 (adjusted event-free survival time ratio 0.25 (95%CI:0.12–0.50), p < 0.001). Repeated measurements clusters showed incremental prognostic value compared to clusters using single measurements, or clinical characteristics only. Conclusions: Clustering based on repeated biomarker measurements revealed three clinically diverse subphenotypes, of which one has a significantly worse prognosis, therefore contributing to improved (individualized) prognostication.
KW - Biomarkers
KW - Cluster analysis
KW - Heart failure
KW - Phenotype
KW - Prognosis
KW - Repeated measurements
UR - http://www.scopus.com/inward/record.url?scp=85132523725&partnerID=8YFLogxK
U2 - https://doi.org/10.1016/j.ijcard.2022.06.020
DO - https://doi.org/10.1016/j.ijcard.2022.06.020
M3 - Article
C2 - 35714717
SN - 0167-5273
VL - 364
SP - 77
EP - 84
JO - International journal of cardiology
JF - International journal of cardiology
ER -