TY - JOUR
T1 - Multi-Biomarker Profiling and Recurrent Hospitalizations in Heart Failure
AU - Bayés-Genís, Antoni
AU - Núñez, Julio
AU - Núñez, Eduardo
AU - Martínez, Jaume Barallat
AU - Pastor Ferrer, Maria-Cruz
AU - de Antonio Ferrer, Marta
AU - Zamora, Elisabet
AU - Sanchis, Juan
AU - Rosés, Josep Lupón
PY - 2016
Y1 - 2016
N2 - Despite advances in pharmacologic therapy and devices, patients with heart failure (HF) continue to have significant rehospitalization rates and risk prediction remains challenging. We sought to explore the value of a multi-biomarker panel [including NT-proBNP, high-sensitivity cardiac troponin T (hs-TnT), and ST2] on top of clinical assessment for long-term prediction of recurrent hospitalizations in HF. NT-proBNP, hs-TnT, and ST2 (suppression of tumorigenicity-2) levels were measured in 891 consecutive ambulatory HF patients. The independent association between the multi-biomarker panel and recurrent hospitalizations was assessed through a multivariable negative binomial regression and expressed as incidence rates ratios. McFadden pseudo- R 2 and goodness-of-fit measures were also used. The total number of unplanned hospitalizations [all-cause, cardiovascular (CV)-, and HF-related] were selected as the primary endpoints. At a mean follow-up of 4.2 ± 2.1 years, 1623 all-cause hospitalizations in 498 patients (55.9%), 710 CV-related hospitalizations in 331 patients (37.2%), and 444 HF-related hospitalizations in 214 patients (24.1%) were registered. The crude incidence of all-cause, CV-, and HF-related recurrent hospitalizations was significantly higher for patients with the multi-biomarker panel above the cut-point (hs-TnT > 14 ng/L, NT-proBNP > 1000 ng/L, and ST2 > 35 ng/mL) (all P < 0.001). For all-cause, CV-, and HF-related recurrent hospitalizations, the McFadden R 2, Akaike information criterion, and Bayesian information criterion supported the superiority of incorporating the multi-biomarker panel into a clinical predictive model. A multi-biomarker approach based on NT-proBNP, hs-TnT, and ST2 better identifies HF patients at risk for recurrent hospitalizations as compared to approaches entailing just one or two of these biomarkers. Elucidation of new biophysiological predictors for recurrent hospitalizations may identify patient profiles for focused intervention.
AB - Despite advances in pharmacologic therapy and devices, patients with heart failure (HF) continue to have significant rehospitalization rates and risk prediction remains challenging. We sought to explore the value of a multi-biomarker panel [including NT-proBNP, high-sensitivity cardiac troponin T (hs-TnT), and ST2] on top of clinical assessment for long-term prediction of recurrent hospitalizations in HF. NT-proBNP, hs-TnT, and ST2 (suppression of tumorigenicity-2) levels were measured in 891 consecutive ambulatory HF patients. The independent association between the multi-biomarker panel and recurrent hospitalizations was assessed through a multivariable negative binomial regression and expressed as incidence rates ratios. McFadden pseudo- R 2 and goodness-of-fit measures were also used. The total number of unplanned hospitalizations [all-cause, cardiovascular (CV)-, and HF-related] were selected as the primary endpoints. At a mean follow-up of 4.2 ± 2.1 years, 1623 all-cause hospitalizations in 498 patients (55.9%), 710 CV-related hospitalizations in 331 patients (37.2%), and 444 HF-related hospitalizations in 214 patients (24.1%) were registered. The crude incidence of all-cause, CV-, and HF-related recurrent hospitalizations was significantly higher for patients with the multi-biomarker panel above the cut-point (hs-TnT > 14 ng/L, NT-proBNP > 1000 ng/L, and ST2 > 35 ng/mL) (all P < 0.001). For all-cause, CV-, and HF-related recurrent hospitalizations, the McFadden R 2, Akaike information criterion, and Bayesian information criterion supported the superiority of incorporating the multi-biomarker panel into a clinical predictive model. A multi-biomarker approach based on NT-proBNP, hs-TnT, and ST2 better identifies HF patients at risk for recurrent hospitalizations as compared to approaches entailing just one or two of these biomarkers. Elucidation of new biophysiological predictors for recurrent hospitalizations may identify patient profiles for focused intervention.
KW - Biomarkers
KW - Heart failure
KW - Hospitalizations
KW - Prediction
KW - NT-proBNP
KW - Hs-tnt
KW - ST2
U2 - 10.3389/fcvm.2016.00037
DO - 10.3389/fcvm.2016.00037
M3 - Article
C2 - 27777932
SN - 2297-055X
VL - 3
JO - Frontiers in Cardiovascular Medicine
JF - Frontiers in Cardiovascular Medicine
ER -