title: Breast cancer: integrating the patient with her genome.
abstract: Increasingly, gene expression data are becoming the currency of the realm in assessing disease prognosis. This has been especially evident in cancer, particularly those malignancies for which tumor samples are fairly accessible and understanding prognostic factors has clear implications for treatment decisions. Recently, Pittman et al. demonstrated substantially increased accuracy of personalized disease outcome prediction in breast cancer by integrating gene-expression profile data with traditional clinical risk factors in a set of 158 breast cancer patients.
authors.affiliation: The Institute for Genome Sciences and Policy, Duke University, Durham, North Carolina 27710, USA. misha.angrist@duke.edu
authors.forename: Misha
authors.initials: M
authors.lastname: Angrist
mesh_terms: D001943:Breast Neoplasms / Q000235:genetics*; D005260:Female; D020869:Gene Expression Profiling; D006801:Humans; D011379:Prognosis; D012306:Risk