Abstract
565 Background: Population-wide screening mammography has contributed to a significant increase in the diagnosis of DCIS, raising questions about over-diagnosis and over-treatment. We aimed to determine whether adding genomic variables to standard clinico-pathologic factors may identify low-risk versus high-risk DCIS, with an ultimate goal of tailoring therapy. Methods: Patient-level clinical and pathologic data were extracted from the electronic medical records of Stanford Cancer Institute and linked to demographic data from the population-based California Cancer Registry; results were integrated with data from tissue microarrays of biopsies revealing DCIS only versus concurrent invasive breast cancer (IBC) with DCIS. We used fluorescence in situ hybridization to investigate the predictive values of CNAs of 1q, 8q24 and 11q13 (reported by The Cancer Genome Atlas to be among the most frequent CNAs in IBC) in the DCIS component of the biopsies. Multivariable logistic regression analysis was performed to de...
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