Background: CALGB 90206 was a phase III trial of 732 pts with RCC comparing B+I versus I alone demonstrating no difference in OS. To date, there are no validated predictive biomarkers for B in RCC. For this reason, baseline plasma samples from CALGB 90206 pts were analyzed to identify and test predictive markers for B+I in RCC pts. Methods: Baseline EDTA plasma samples from 424 consenting pts were analyzed using an optimized multiplex ELISA platform for 32 candidate factors related to tumor growth, angiogenesis, and inflammation. The data were randomly split into training (n=286) and validation (n=138) sets. The proportional hazards model was used to test for treatment-marker interactions of OS. The estimated coefficients from the training set were used to compute a risk score (RS) for each pt in the validation set. The RS classified pts by risk in the validation set. The model was assessed for its predictive accuracy using area under the curve (AUC). Results: A statistically significant 3-way interaction between interleukin-6 (IL-6), hepatocyte growth factor (HGF) and treatment was observed in the training set (p<0.0001). The median levels of IL-6 and HGF in the training set were 8.4 pg/ml and 89 pg/ml, respectively. In the validation set, the RS was predictive of OS (p<0.001) with the high and low risk groups having a median OS of 10 months and 32 months, respectively. The AUC in the validation set was 0.82 (95% CI=0.77-0.88). The median OS (in months) by median levels of IL-6 and HGF stratified by treatment arm in the validation set is presented in the table with associated 95% CI (NR=not reached). Conclusions: IL-6 and HGF are predictive for OS in RCC patients treated with B+I and a RS based on these factors identified patients who benefitted most from B. If independently validated, this novel RS could guide clinical decisions and pt selection in future RCC trials.