Resumen:
Purpose: This retrospective analysis of the largest available clinico-genomic database used de-identified patient-level electronic health record-derived real-world data (RWD) combined with FoundationOne comprehensive genomic profiling (CGP) to characterize patients with metastatic urothelial carcinoma (mUC) treated in the real-world setting, detect potential biomarkers, and develop a bladder immune performance index (BIPI).
Experimental design: Patients with mUC who started front-line single-agent immune checkpoint inhibitors (ICI) and an unmatched group treated with front-line platinum-based chemotherapy between January 1, 2011, and September 30, 2019, were selected. Clinical and genomic data were correlated with overall survival (OS). A novel BIPI predicting outcome with ICIs was developed using machine learning methods and validated using data from a phase II trial (NCT02951767).
Results: In ICI-treated patients (n = 118), high tumor mutational burden (¿10 mutations/megabase) was associated with improved OS (HR, 0.58; 95% CI, 0.35-0.95; P = 0.03). In chemotherapy-treated patients (n = 268), those with high APOBEC mutational signature had worse OS (HR, 1.43; 95% CI, 1.06-1.94; P = 0.02). Neither FGFR3 mutations nor DNA damage-repair pathway alterations were associated with OS. A novel BIPI combining clinical and genomic variables (nonmetastatic at initial diagnosis, normal or above normal albumin level at baseline, prior surgery for organ-confined disease, high tumor mutational burden) identified ICI-treated patients with longest OS and was validated in an independent dataset.
Conclusions: Contemporary RWD including FoundationOne CGP can be used to characterize outcomes in real-world patients according to biomarkers beyond PD-L1. A validated, novel clinico-genomic BIPI demonstrated satisfactory prognostic performance for OS in patients with mUC receiving front-line ICI therapy.
