424 Background: Reliable biomarkers to predict response of urothelial cancer to PD-1/PD-L1 inhibitors are still being investigated. Texture analysis represents underlying tumor heterogeneity and may serve as a predictor of response in urothelial cancer. The purpose of this study was to assess predictive ability of CT texture analysis for disease progression in patients with metastatic urothelial cancer treated with PD-1/PD-L1 inhibitor. Methods: In this IRB-approved HIPAA-compliant retrospective study, from total 93 consecutive patients with metastatic urothelial cancer treated with PD-1/PD-L1 inhibitors from 2013-2018, 43 patients with measurable disease per RECIST 1.1 criteria who had contrast-enhanced CT performed within three months after starting treatment were included. Progression-free survival was calculated based on serial follow-up CTs, and 11 patients without progression who did not reach 1 year follow-up were excluded. Texture features of measurable lesions on first follow-up CT were extracted (TexRAD Ltd, Feedback Plc, Cambridge, UK). Stepwise logistic regression analysis to identify patients who had progressive disease (PD) at 12 months was performed and performance assessed using receiver operator curves. Results: Of 32 included patients (24 men, 8 women; median age: 65 years) who had total 80 measurable lesions, 22 progressed by 12 months. On first follow-up CT, the entropy and mean of the lesions were higher (p = 0.04, p = 0.02) for patients with PD by 12 months. Calculated specificity and sensitivity of entropy (AUC = 0.79) were 90%, and 63%; of mean (AUC = 0.81) were 90%, and 50%. A predictive model including mean and entropy yielded 95% sensitivity, 80% specificity, 91% PPV, 89% NPV and 91% accuracy (AUC = 0.863) to identify patients with PD at 12 months. Conclusions: Texture analysis of CT performed within three months after starting PD-1/PD-L1 can help predict patients who progress by 12 months with high accuracy. Further studies investigating the correlation of texture analysis with survival endpoints may help validate the role of texture analysis as a biomarker to predict response to PD1/PD-L1 inhibitors.