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Preliminary evidence showed that incorporation of gene-expression signatures into standard clinical risk factor measures can improve accuracy of prognoses in patients with breast cancer. To evaluate further the usefulness of gene signatures, Duke University investigators analyzed breast-tumor samples that they categorized into three prognostic groups (high, intermediate, or low risk for recurrence) based on clinicopathologic characteristics.
The initial dataset included 573 patients from the three clinicopathologic risk groups. Microarray analysis of tumor samples showed that these patients could be assigned to risk clusters according to their gene signatures. A multivariate model, which included clinicopathologic factors, identified gene si…