Development and internal validation of a prognostic nomogram for overall survival in patients with advanced renal cell carcinoma (aRCC) treated with pazopanib (PAZ).

380 Background: PAZ, an oral multikinase inhibitor, demonstrated significant improvement in PFS over placebo in patients with aRCC in a randomized, phase III trial (J Clin Oncol 2009:29; 475). The purpose of this study was to develop and internally validate a prognostic nomogram based on the outcome data from phase III trial for predicting the probability of 12-month OS for treatment-naïve and cytokine-pretreated aRCC patients who received PAZ. Methods: Statistical modeling was performed on a dataset consisting of 281 patients from the PAZ arm of the phase III trial. Missing values were first imputed using multiple imputation with chained equations. A Cox proportional hazards regression model was fit using routinely available predictors thought to be prognostic based on clinical judgment. These predictors included the neutrophil count relative to ULN, platelet count relative to ULN, LDH relative to ULN, alkaline phosphatase relative to ULN, corrected calcium, albumin, hemoglobin, ECOG performance status, months from diagnosis to treatment, number of metastatic sites, and presence of lung, liver and bone metastases. Bootstrap-corrected estimates of discrimination and calibration in the small were calculated following 1,000 resamples. The Cox model was plotted as a nomogram. Results: A prognostic nomogram was developed and internally validated for predicting the probability of 12-month OS in aRCC patients based on a Cox regression model using 13 predictor variables. Calibration plots suggested reasonable correspondence between predicted probabilities and actual proportions of OS. The bootstrap-corrected concordance index, a measure of discrimination, was 0.70. When examining the nomogram, albumin appeared to have the greatest potential influence on predicted OS. Months from diagnosis to treatment and corrected calcium level seemed to be the next most potentially influential predictors. Conclusions: The nomogram predicts with reasonable accuracy and should facilitate treatment decision making for patients with advanced renal cell carcinoma. Validation in a separate dataset is planned.