An Empirical Framework for Validating Artificial Intelligence–Derived PD-L1 Positivity Predictions Applied to Urothelial Carcinoma

Study Background

• Assessing programmed death ligand 1 (PD-L1) immunohistochemistry (IHC) expression plays an important role in identifying patients likely to benefit from anti–programmed death-1/PD-L1 therapies in advanced cancer, including urothelial carcinoma (UC)
• Studies have shown moderate-to-strong interobserver agreement for pathologist assessment of PD-L1 expression on tumor cells, with moderate-to-poor concordance for immune cell scoring 1–3
• Thus, conventional pathologist estimation of whole-slide image scores is a suboptimal approach to obtain reference data for the evaluation of the performance of image-analysis algorithms, especially for immune cell scoring