We sought to develop a multiple biomarker approach for prediction of incident major
adverse cardiac events (MACE; composite of cardiovascular death, myocardial infarction,
and stroke) in patients referred for coronary angiography. In a 649-participant training
cohort, predictors of MACE within 1 year were identified using least-angle regression;
over 50 clinical variables and 109 biomarkers were analyzed. Predictive models were
generated using least absolute shrinkage and selection operator with logistic regression.
A score derived from the final model was developed and evaluated with a 278-patient
validation set during a median of 3.6 years follow-up. The scoring system consisted
of N-terminal pro B-type natriuretic peptide (NT-proBNP), kidney injury molecule-1,
osteopontin, and tissue inhibitor of metalloproteinase-1; no clinical variables were
retained in the predictive model. In the validation cohort, each biomarker improved
model discrimination or calibration for MACE; the final model had an area under the
curve (AUC) of 0.79 (p <0.001), higher than AUC for clinical variables alone (0.75).
In net reclassification improvement analyses, addition of other markers to NT-proBNP
resulted in significant improvement (net reclassification improvement 0.45; p = 0.008).
At the optimal score cutoff, we found 64% sensitivity, 76% specificity, 28% positive
predictive value, and 93% negative predictive value for 1-year MACE. Time-to-first
MACE was shorter in those with an elevated score (p <0.001); such risk extended to
at least to 4 years. In conclusion, in a cohort of patients who underwent coronary
angiography, we describe a novel multiple biomarker score for incident MACE within
1 year (NCT00842868).
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Article Info
Publication History
Published online: April 13, 2017
Accepted:
March 31,
2017
Received in revised form:
March 31,
2017
Received:
February 14,
2017
Footnotes
This work was supported by a grant from Prevencio, Inc. (Kirkland, Washington).
See page 31 for disclosure information.
Identification
Copyright
© 2017 Elsevier Inc. All rights reserved.
