Gene expression score increases classification accuracy for patients without diabetes
TUESDAY, Oct. 5 (HealthDay News) -- A new blood test measuring gene expression can modestly increase the accuracy of predicting obstructive coronary artery disease (CAD) in patients without diabetes or known CAD, according to research published in the Oct. 5 issue of the Annals of Internal Medicine.
Steven Rosenberg, Ph.D., of CardioDx in Palo Alto, Calif., and colleagues conducted a multicenter prospective trial with blood samples obtained before coronary angiography to validate a previously developed 23-gene, expression-based classification test for diagnosis of obstructive CAD in individuals without diabetes. The study included a validation cohort composed of 526 patients who did not have diabetes but had a clinical indication for coronary angiography. The new gene-based test was compared to the Diamond-Forrester clinical risk method and an expanded clinical model for predicting the likelihood of obstructive CAD.
The researchers found that the gene-based test was significantly better at reclassification of patients compared to the other two methods. For a threshold score equivalent to a 20 percent likelihood of obstructive CAD, the gene expression test had a sensitivity and specificity of 85 and 43 percent, respectively, with a negative predictive value of 83 percent and a positive predictive value of 46 percent.
"Our test provides a statistically significant but modest improvement in classification of patient CAD status compared with clinical factors or noninvasive imaging. Further studies are needed to define the performance characteristics and clinical utility in populations with a lower pretest probability," the authors write.
The study was primarily funded by CardioDx, which employs several study authors.
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