TY  - JOUR
ID  - enlighten128378
UR  - https://eprints.gla.ac.uk/128378/
IS  - 3
A1  - Demissei, Biniyam G.
A1  - Valente, Mattia A.E.
A1  - Cleland, John G.F.
A1  - O'Connor, Christopher M.
A1  - Metra, Marco
A1  - Ponikowski, Piotr
A1  - Teerlink, John R.
A1  - Cotter, Gad
A1  - Davison, Beth
A1  - Givertz, Michael M.
A1  - Bloomfield, Daniel M.
A1  - Dittrich, Howard
A1  - van der Meer, Peter
A1  - van Veldhuisen, Dirk J.
A1  - Hillege, Hans L.
A1  - Voors, Adriaan A.
Y1  - 2016/03//
N2  - Aim: 

The clinical value of single biomarkers at single time-points to predict outcomes in patients with acute heart failure (AHF) is limited. We performed a multimarker, multi-time-point analysis of biomarkers for the prediction of post-discharge clinical outcomes in high-risk AHF patients.
Methods and results: 

A set of 48 circulating biomarkers were measured in the PROTECT trial which enrolled 2033 patients with AHF. Associations between baseline levels of biomarkers and outcomes (30-day all-cause mortality, 30-day death or rehospitalization for renal/cardiovascular causes and 180-day all-cause mortality) were evaluated. Prognostic accuracies of baseline, days 2 or 3, 7, and 14 biomarker measurements were estimated and compared utilizing a time-dependent area under the curve (AUC) analysis. Forty-four biomarkers were significantly associated with outcomes, but 42 had limited prognostic value (C-index?<?0.70). However, multimarker models combining best-performing biomarkers from different clusters had a much stronger prognostic value. Combining blood urea nitrogen (BUN), chloride, interleukin (IL)-6, cTnI, sST-2 and VEGFR-1 into a clinical model yielded a 11% increase in C-index to 0.84 and 0.78 for 30-day and 180-day all-cause mortality, respectively, and cNRI of 0.86 95% CI [0.55?1.11] and 0.76 95% CI [0.57?0.87]. Prognostic gain was modest for the 30-day death/rehospitalization for cardiovascular or renal causes endpoint. Comparative time-dependent AUC analysis indicated that late measurements provided superior accuracy for the prediction of all-cause mortality over 180?days, with few exceptions including BUN and galectin-3. However, the predictive value of most biomarkers showed a diminishing pattern over time irrespective of moment of measurement.
Conclusions: 

Multimarker models significantly improve risk prediction. Subsequent measurements, beyond admission, are needed for majority of biomarkers to maximize prognostic value over time, particularly in the long term.
PB  - Wiley
JF  - European Journal of Heart Failure
VL  - 18
SN  - 1388-9842
TI  - Optimizing clinical use of biomarkers in high-risk acute heart failure patients
SP  - 269
AV  - none
EP  - 280
ER  -