Methods of creatine kinase-MB analysis to predict mortality in patients with myocardial infarction treated with reperfusion therapy.
Abstract
BACKGROUND: Larger infarct size measured by creatine kinase (CK)-MB release is associated
with higher mortality and has been used as an important surrogate endpoint in the
evaluation of new treatments for ST-segment elevation myocardial infarction (STEMI).
Traditional approaches to quantify infarct size include the observed CK-MB peak and
calculated CK-MB area under the curve (AUC). We evaluated alternative approaches to
quantifying infarct size using CK-MB values, and the relationship between infarct
size and clinical outcomes. METHODS: Of 1,850 STEMI patients treated with reperfusion
therapy in the COMplement inhibition in Myocardial infarction treated with Angioplasty
(COMMA) (percutaneous coronary intervention (PCI)-treated) and the COMPlement inhibition
in myocardial infarction treated with thromboLYtics (COMPLY) (fibrinolytic-treated)
trials, 1,718 (92.9%) (COMMA, n = 868; COMPLY, n = 850) had at least five of nine
protocol-required CK-MB measures. In addition to traditional methods, curve-fitting
techniques were used to determine CK-MB AUC and estimated peak CK-MB. Cox proportional
hazards modeling assessed the univariable associations between infarct size and mortality,
and the composite of death, heart failure, shock and stroke at 90 days. RESULTS: In
COMPLY, CK-MB measures by all methods were significantly associated with higher mortality
(hazard ratio range per 1,000 units increase: 1.09 to 1.13; hazard ratio range per
1 standard deviation increase: 1.41 to 1.62; P <0.01 for all analyses). In COMMA,
the associations were similar but did not reach statistical significance. For the
composite outcome of 90-day death, heart failure, shock and stroke, the associations
with all CK-MB measures were statistically significant in both the COMMA and COMPLY
trials. CONCLUSIONS: Sophisticated curve modeling is an alternative to infarct-size
quantification in STEMI patients, but it provides information similar to that of more
traditional methods. Future studies will determine whether the same conclusion applies
in circumstances other than STEMI, or to studies with different frequencies and patterns
of CK-MB data collection.
Type
Journal articleSubject
Area Under CurveBiomarkers
Clinical Enzyme Tests
Creatine Kinase, MB Form
Heart Failure
Humans
Myocardial Infarction
Myocardial Reperfusion
Percutaneous Coronary Intervention
Predictive Value of Tests
Proportional Hazards Models
Risk Assessment
Risk Factors
Shock
Stroke
Thrombolytic Therapy
Time Factors
Treatment Outcome
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https://hdl.handle.net/10161/12499Published Version (Please cite this version)
10.1186/1745-6215-14-123Publication Info
Lopes, Renato D; Lokhnygina, Yuliya; Hasselblad, Victor; Newby, Kristin L; Yow, Eric;
Granger, Christopher B; ... Mahaffey, Kenneth W (2013). Methods of creatine kinase-MB analysis to predict mortality in patients with myocardial
infarction treated with reperfusion therapy. Trials, 14. pp. 123. 10.1186/1745-6215-14-123. Retrieved from https://hdl.handle.net/10161/12499.This is constructed from limited available data and may be imprecise. To cite this
article, please review & use the official citation provided by the journal.
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Show full item recordScholars@Duke
Paul Wayne Armstrong
Adjunct Professor in the Department of Medicine
Christopher Bull Granger
Professor of Medicine
Research: My primary research interest is in conduct and methodology of large randomized
clinical trials in heart disease. I have led a number of large international clinical
studies in heart attacks, unstable angina, heart failure, and atrial fibrillation.
I have lead clinical studies of blood thinners and coronary intervention for heart
attacks, stroke prevention in atrial fibrillation, and prevention of heart attack
for patients with coronary artery disease. I have been co-directo
Victor Hasselblad
Professor Emeritus of Biostatistics & Bioinformatics
The research interests of Vic Hasselblad include distribution fitting, sample size
and power calculations, dose-response estimation, meta-analysis, and non-inferiority
designs.
Yuliya Vladimirovna Lokhnygina
Associate Professor of Biostatistics & Bioinformatics
Statistical methods in clinical trials, survival analysis, adaptive designs, adaptive
treatment strategies, causal inference in observational studies, semiparametric inference
Renato Delascio Lopes
Professor of Medicine
Atrial Fibrillation Antithrombotic Therapy in patients with Acute Coronary Syndromes
Elderly patients with Heart Disease Biomarkers in Acute Coronary Syndromes and Atrial
Fibrillation Thrombosis and Anticoagulation and novel antithrombotic agents Metabolomics
in Cardiovascular Medicine
James Steven Mills
Assistant Professor of Medicine
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