Dataset Information

Multicenter validation of the diagnostic accuracy of a blood-based gene expression test for assessing obstructive coronary artery disease in nondiabetic patients.

ABSTRACT:

Background

Diagnosing obstructive coronary artery disease (CAD) in at-risk patients can be challenging and typically requires both noninvasive imaging methods and coronary angiography, the gold standard. Previous studies have suggested that peripheral blood gene expression can indicate the presence of CAD.

Objective

To validate a previously developed 23-gene, expression-based classification test for diagnosis of obstructive CAD in nondiabetic patients.

Design

Multicenter prospective trial with blood samples obtained before coronary angiography. (ClinicalTrials.gov registration number: NCT00500617) SETTING: 39 centers in the United States.

Patients

An independent validation cohort of 526 nondiabetic patients with a clinical indication for coronary angiography.

Measurements

Receiver-operating characteristic (ROC) analysis of classifier score measured by real-time polymerase chain reaction, additivity to clinical factors, and reclassification of patient disease likelihood versus disease status defined by quantitative coronary angiography. Obstructive CAD was defined as 50% or greater stenosis in 1 or more major coronary arteries by quantitative coronary angiography.

Results

The area under the ROC curve (AUC) was 0.70 ± 0.02 (P < 0.001); the test added to clinical variables (Diamond-Forrester method) (AUC, 0.72 with the test vs. 0.66 without; P = 0.003) and added somewhat to an expanded clinical model (AUC, 0.745 with the test vs. 0.732 without; P = 0.089). The test improved net reclassification over both the Diamond-Forrester method and the expanded clinical model (P < 0.001). At a score threshold that corresponded to a 20% likelihood of obstructive CAD (14.75), the sensitivity and specificity were 85% and 43% (yielding a negative predictive value of 83% and a positive predictive value of 46%), with 33% of patient scores below this threshold.

Limitation

Patients with chronic inflammatory disorders, elevated levels of leukocytes or cardiac protein markers, or diabetes were excluded.

Conclusion

A noninvasive whole-blood test based on gene expression and demographic characteristics may be useful for assessing obstructive CAD in nondiabetic patients without known CAD.

Primary funding source

CardioDx.

SUBMITTER: Rosenberg S

PROVIDER: S-EPMC3786733 | biostudies-literature | 2010 Oct

REPOSITORIES: biostudies-literature

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Publications

Multicenter validation of the diagnostic accuracy of a blood-based gene expression test for assessing obstructive coronary artery disease in nondiabetic patients.

Rosenberg Steven S Elashoff Michael R MR Beineke Philip P Daniels Susan E SE Wingrove James A JA Tingley Whittemore G WG Sager Philip T PT Sehnert Amy J AJ Yau May M Kraus William E WE Newby L Kristin LK Schwartz Robert S RS Voros Szilard S Ellis Stephen G SG Tahirkheli Naeem N Waksman Ron R McPherson John J Lansky Alexandra A Winn Mary E ME Schork Nicholas J NJ Topol Eric J EJ

Annals of internal medicine 20101001 7

<h4>Background</h4>Diagnosing obstructive coronary artery disease (CAD) in at-risk patients can be challenging and typically requires both noninvasive imaging methods and coronary angiography, the gold standard. Previous studies have suggested that peripheral blood gene expression can indicate the presence of CAD.<h4>Objective</h4>To validate a previously developed 23-gene, expression-based classification test for diagnosis of obstructive CAD in nondiabetic patients.<h4>Design</h4>Multicenter pr ...[more]

PMID: 20921541

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Dataset Information

Multicenter validation of the diagnostic accuracy of a blood-based gene expression test for assessing obstructive coronary artery disease in nondiabetic patients.

Background

Objective

Design

Patients

Measurements

Results

Limitation

Conclusion

Primary funding source

Publications

Multicenter validation of the diagnostic accuracy of a blood-based gene expression test for assessing obstructive coronary artery disease in nondiabetic patients.

Similar Datasets

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