Assessment of the multiple-biomarker approach for diagnosis of myocardial infarction in patients presenting with symptoms suggestive of acute coronary syndrome.
BACKGROUND
Cardiac troponin is the preferred biomarker for detecting acute myocardial injury and infarction (MI). We studied whether multiple biomarkers of numerous pathophysiological pathways would increase the diagnostic accuracy for detecting MI.


METHODS
Seven biomarkers [myeloperoxidase, soluble CD40 ligand, placental growth factor, matrix metalloproteinase 9 (MMP-9), high-sensitivity C-reactive protein (hsCRP), cardiac troponin I (cTnI), N-terminal pro-B-type natriuretic peptide] and estimated glomerular filtration rate were measured in 457 patients presenting on admission with symptoms suggestive of acute coronary syndrome. Twenty-five patients (5.4%) received MI diagnoses. Clinical sensitivities and specificities were evaluated from 99th-percentile reference values. Forward and backward stepwise logistic regression modeling techniques were used to identify biomarkers that were independently predictive of MI.


RESULTS
Biomarker sensitivities ranged from 20% to 96%, and specificities ranged from 19% to 89%. MMP-9 had the highest sensitivity, but its specificity was 19%. cTnI demonstrated a sensitivity of 72% (95% CI, 51%-88%) and a specificity of 89% (95% CI, 85%-92%). In multivariate models, cTnI (P < 0.001) and either hsCRP (P = 0.009) or MMP-9 (P = 0.03) were independently predictive of MI. Addition of hsCRP or MMP-9 increased the specificity to 95% (95% CI, 92%-97%) or 91% (95% CI, 88%-94%), respectively, but reduced the sensitivity to 56% (95% CI, 35%-76%) and 68% (95% CI, 47%-85%) relative to cTnI alone.


CONCLUSIONS
Our findings indicate that the most clinically accurate biomarker for the early diagnosis of MI is the use of cTnI alone, rather than a multiple-biomarker approach, when an analytically robust cardiac troponin assay based on the 99th percentile is used.
Apple
Fred S
FS
Department of Laboratory Medicine, Hennepin County Medical Center, University of Minnesota School of Medicine, Minneapolis, MN, USA. apple004@umn.edu
Smith
Stephen W
SW
Pearce
Lesly A
LA
Murakami
MaryAnn M
MM
D054058:Acute Coronary Syndrome / Q000097:blood* / Q000175:diagnosis*; D000368:Aged; D015415:Biomarkers / Q000097:blood*; D002097:C-Reactive Protein / Q000032:analysis; D023201:CD40 Ligand / Q000097:blood; D004797:Enzyme-Linked Immunosorbent Assay; D005260:Female; D005919:Glomerular Filtration Rate; D006801:Humans; D016015:Logistic Models; D008297:Male; D020780:Matrix Metalloproteinase 9 / Q000097:blood; D008875:Middle Aged; D009203:Myocardial Infarction / Q000097:blood* / Q000175:diagnosis*; D020097:Natriuretic Peptide, Brain / Q000097:blood; D010446:Peptide Fragments / Q000097:blood; D009195:Peroxidase / Q000097:blood; D000072483:Placenta Growth Factor; D011257:Pregnancy Proteins / Q000097:blood; D018570:Risk Assessment; D012680:Sensitivity and Specificity; D012995:Solubility; D019210:Troponin I / Q000097:blood
D015415:Biomarkers; C000608036:PGF protein, human; D010446:Peptide Fragments; D011257:Pregnancy Proteins; D019210:Troponin I; C109794:pro-brain natriuretic peptide (1-76); D020097:Natriuretic Peptide, Brain; D000072483:Placenta Growth Factor; D023201:CD40 Ligand; D002097:C-Reactive Protein; D009195:Peroxidase; D020780:Matrix Metalloproteinase 9