© The Author 2006. Published by Oxford University Press.
EDITORIAL |
Development and Evaluation of Therapeutically Relevant Predictive Classifiers Using Gene Expression Profiling
Correspondence to: Richard Simon, DSc, Biometric Research Branch, Division of Cancer Treatment and Diagnosis, National Cancer Institute, 9000 Rockville Pike, Bethesda, MD 20892-7434 (e-mail: rsimon@nih.gov).
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Gene expression profiles offer the possibility of improving risk predication and optimizing treatment selection for individual patients. Two articles in this issue of the Journal describe clinical studies of gene expression profiling—one a developmental study and the other a validation study. Asgharzadeh et al. (1) address the development of a prognostic classifier for patients with metastatic neuroblastoma lacking amplification of the MYCN gene. Buyse et al. (2) report the validation of a gene expression–based prognostic classifier for patients with early breast cancer.
Asgharzadeh et al. (1) developed their classifier based on the expression of 55 genes that appears to predict risk of disease progression more accurately than does patient age, histologic type, or other currently used risk features. The claims of improved risk prediction are based on an internal estimate of prediction accuracy computed by Asgharzadeh et al. The approach taken by the authors
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