Carlson, R. W.

4565 Background: The efficient delivery of adjuvant therapy after radical prostatectomy (RP) in patients with prostate cancer is limited by the lack of biomarkers, beyond clinicopathologic factors, that are able to assess the risk of clinically significant disease progression. Previously, routine FFPE patient specimens from the Mayo Clinic Radical Prostatectomy Registry with long term follow-up were selected to develop a genomic classifier (GC) to predict clinical progression. Here, we present the validation of a GC in a cohort of patients at high risk of disease progression. Methods: A case-cohort study of high-risk RP patients from the Mayo Clinic (N=219) was used to validate the genomic classifier (GC) for predicting clinical progression (defined by positive bone or CT scan post-RP). Its performance was compared to a multivariable clinical classifier (CC) and a genomic-clinical classifier (GCC) which combines GC with established clinicopathologic variables. Concordance index, Cox modeling and decision curve analysis were used to compare the different models. Results: GC and GCC were predictive of clinical progression in the high-risk cohort with c-indices of 0.79 and 0.82, respectively, compared to the clinical classifier (0.70). Multivariable survival analysis showed that the majority of prognostic information of GCC came from the GC with a minor contribution from Gleason score. Decision curve analysis showed that GCC had a higher overall net benefit compared to CC over a wide range of ‘decision-to-treat’ thresholds for the risk of progression. Conclusions: In this high-risk cohort, GC and GCC classifiers showed improved performance over CC in prediction of clinical progression. GC is an independent prognostic factor in this cohort and captures the majority of prognostic information. GC and GCC’s prognostic performance and their usefulness in guiding decision-making in the adjuvant setting after RP need further testing in studies of additional prostate cancer risk groups.

576 Background: In node-negative, ER + breast cancer, gene expression profiling can identify level of risk and, in the case of ODX, may also identify pts with a higher chance of benefiting from adjuvant chemotherapy. Because the gene profile in ODX includes an assessment of ER, HER2, and proliferation, we hypothesized that clinicians using standardized criteria could discriminate risk (high versus low/intermediate) as specified by ODX. Methods: We identified Mayo Clinic patients with node-negative, ER + breast cancer, for whom ODX scores were available. Tumor slides were reviewed by an expert breast pathologist to confirm tumor size, histology, and tumor grade. Both ER and PR were quantitated; HER-2 was determined by IHC (FISH, if 2+). These clinical cases were presented to six academic oncologists, blinded to the ODX score, to predict ODX risk (low, intermediate, or high) and give their recommendation for chemotherapy (CTX) (yes/no). Afterwards, they were presented with the same cases with the actual ODX score, to give recommendations regarding CTX. Results: ODX scores in tumors from 31 patients were low in 18 pts, intermediate in 10 pts, and high in 3 pts. Concordance between predicted and actual ODX scores being low/intermediate vs high exceeded 87% for each oncologist. The most frequent discrepancies were actual low scores predicted as intermediate (31/80 discordant) and actual intermediate scores predicted as low (29/80 discordant). Overall agreement of predicted scores (high vs low/intermediate) among the oncologists was substantial (kappa=0.75, p<0.0001). CTX recommendations following provision of the ODX scores changed on average 18.2% (range 12.9%-25.8%) of the time, with slightly fewer changing for, versus against, a CTX recommendation. Conclusions: Our findings suggest that the proper evaluation and interpretation of traditional prognostic criteria will identify most node negative, ER + patients at high risk of recurrence (as predicted by ODX) but poorly discriminate low versus intermediate risk. The provision of ODX data changed the recommendation for CTX in approximately 20% of cases. No significant financial relationships to disclose.