MP58-15 PREDICTING SURVIVAL AFTER RADICAL CYSTECTOMY: VALIDATION OF THE SPARC SCORE

INTRODUCTION AND OBJECTIVES: The Survival Prediction After Radical Cystectomy (SPARC) score incorporates clinical and pathologic features to predict cancer specific survival (CSS) for urothelial carcinoma of the bladder after radical cystectomy (RC). Validation of this model would improve its generalizability. METHODS: Using the IRB-approved bladder cancer database at the University of Southern California, we identified patients who underwent RC for urothelial carcinoma of the bladder for curative intent from 1971-2009. Clinical factors (Charlson comorbidity index, ECOG performance status, hydronephrosis, adjuvant chemotherapy, smoking status) and pathologic factors (pathologic T stage, nodal status, multifocality, and lymphovascular invasion) included in the SPARC score were obtained. Patients were excluded if there were missing variables or if they underwent neoadjuvant chemotherapy. Associations between clinicopathologic factors and CSS were evaluated using Cox proportional hazards. Calibration plots were generated comparing actuarial CSS with SPARC predicted CSS by deciles. A c-index was generated to determine accuracy of the prediction. Kaplan Meier curves estimated CSS stratified by SPARC score and were compared with the log rank test. RESULTS: A total of 2045 patients underwent RC and 1123 (55%) met inclusion criteria with a median follow-up of 4.7 years (IQR 2.0-8.9 years). Of the 1123 patients, 332 (30%) died of bladder cancer. All the clinical and pathologic variables used in the SPARC scoring model were associated with CSS except for smoking status and tumor multifocality. Calibration plots demonstrated concordance between the SPARC-predicted and actuarial CSS with a c-index of 0.75. Kaplan Meier curves demonstrated significant differences in CSS based upon SPARC score, p<0.001 (Figure). CONCLUSIONS: The SPARC score represents a valid instrument for predicting CSS after RC for urothelial carcinoma of the bladder. The model can be utilized to better tailor adjuvant therapy and surveillance. Source of Funding: none