News

Genetic-Test Algorithm Is Validated for CAD Assessment


 

Major Finding: The Corus genetic test bested two standard risk factor assessments for predicting obstructive coronary artery disease.

Source of Data: Prospective comparison of three screening tests in 525 patients.

Disclosures: The study was sponsored by, and Dr. Kraus received research support from, CardioDx, the maker of Corus.

ORLANDO — A genetic test surpassed conventional risk-factor assessment for predicting the presence of an obstructive coronary lesion, based on results from a prospective study of 525 patients with suspected coronary artery disease.

The results performed better than either the Diamond-Forrester method or the Framingham Risk Score for predicting obstructive coronary artery disease, Dr. William E. Kraus said at the annual scientific sessions of the American Heart Association.

The genetic test examines RNA expression for 23 genes in a peripheral blood sample. The test is marketed in the United States under the name Corus by CardioDx.

The risk algorithm used to interpret the genetic-test results factors the person's age and gender. The genes primarily control immune responses, including neutrophil activation, natural killer cell activation by T cells, and adaptive immunity. The functions of other genes that are part of the test remain unknown, but prior results identified their expression as tracking with coronary disease risk, said Dr. Kraus, a cardiologist at Duke University in Durham, N.C.

The Personalized Risk Evaluation and Diagnosis in the Coronary Tree (PREDICT) study enrolled patients at 43 U.S. sites with suspected coronary disease who were scheduled for coronary catheterization and angiography. The subjects included both symptomatic and asymptomatic individuals. Researchers collected clinical data and a blood specimen from each person prior to their angiography.

Angiography identified a coronary stenosis that obstructed at least 50% of at least one major coronary artery (diameter of at least 1.5 mm) in 192 of the 525 patients (37%).

The risk algorithm prospectively divided participants into a low-risk group of 174, a medium-risk group of 177, and a high-risk group of 174. Angiography found a coronary disease prevalence of 17% in the low-risk group, 33% in the medium-risk group, and 60% in the high-risk group.

The gene-test algorithm results accounted for 72% of the coronary artery disease found in the study. In contrast, applying the Diamond-Forrester method for determining coronary disease risk accounted for 66% of the coronary disease (N. Engl. J. Med. 1979;300:1350–8).

A more detailed comparison of the genetic-test algorithm to the Diamond-Forrester method showed that in the study group of 525, Diamond-Forrester identified 150 of the patients (29%) at medium risk for coronary disease, and the overall rate of actual disease in these people was 39%.

Running the genetic-test algorithm on these 150 people identified 32 as actually having a low risk, 65 as having a high risk, and 53 with a medium risk. The actual coronary disease rate found within each of these stratified subgroups confirmed the validity of the gene-test reclassification: In the 32 people categorized as low risk by the genetic test but medium risk by Diamond-Forrester the actual rate of coronary disease was 25%. Among the 53 people rated with a medium risk by the genetic tests the prevalence of actual coronary disease was 30%. And in the 65 patients that the genetic test flagged as having a high disease risk the actual prevalence was 52%.

The genetic-test algorithm has similar success reclassifying the coronary disease risk when the first determinant used was the Framingham Risk Score.

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