Optimal PD-L1-high cutoff for association with overall survival in patients with urothelial cancer treated with durvalumab monotherapy.
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ABSTRACT: BACKGROUND:Studies have indicated that programmed death ligand 1 (PD-L1) expression may have utility as a predictive biomarker in patients with advanced/metastatic urothelial carcinoma (UC). Different immunohistochemical (IHC) assays are in development to assess PD-L1 expression on tumor cells (TCs) and tumor-infiltrating immune cells (ICs). METHODS:In this post hoc analysis of the single-arm, phase 1/2 Study 1108 (NCT01693562), PD-L1 expression was evaluated from tumor samples obtained prior to second-line treatment with durvalumab in patients with advanced/metastatic UC using the VENTANA (SP263) IHC Assay. The primary objective was to determine whether the TC ? 25%/IC ? 25% algorithm (i.e., cutoff of ? 25% TC or ? 25% IC with PD-L1 staining at any intensity above background) was optimal for predicting response to durvalumab. PD-L1 expression data were available from 188 patients. RESULTS:After a median follow-up of 15.8 and 14.6 months, higher PD-L1 expression was associated with longer overall survival (OS) and progression-free survival (PFS), respectively, with significant separation in survival curves for PD-L1-high and-low expressing patients for the TC ? 25%/IC ? 25% cutoff (median OS: 19.8 vs 4.8 months; hazard ratio: 0.46; 90% confidence interval: 0.33, 0.639). OS was also prolonged for PD-L1-high compared with-low patients when samples were categorized using TC/IC combined positive score ? 10 and IC? 5% cutoffs. In multivariate analysis, IC but not TC PD-L1 expression was significantly associated with OS, PFS, and objective response rate (P < 0.001 for each), although interaction analysis showed similar directionality of benefit for ICs and TCs. CONCLUSIONS:These findings support the utility of a combined TC/IC algorithm for predicting response to durvalumab in patients with UC, with the TC? 25%/IC? 25% cutoff optimal when used with the VENTANA (SP263) IHC Assay.
SUBMITTER: Zajac M
PROVIDER: S-EPMC7185603 | biostudies-literature | 2020
REPOSITORIES: biostudies-literature
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