Predicting response to intravesical BCG in high-risk non-muscle invasive bladder cancer using an artificial intelligence-powered pathology assay: development and validation in an international 12 center cohort.

There are few markers to identify those likely to recur or progress after treatment with intravesical BCG. We developed and validated artificial intelligence-based histologic assays that extract interpretable features from transurethral resection of bladder tumor digitized pathology images to predict risk of recurrence, progression, development of BCG unresponsive disease, and cystectomy. Pre-BCG resection-derived whole-slide images and clinical data were obtained for high-risk non-muscle invasive bladder cancer cases treated with BCG from 12 centers and were analyzed through a segmentation and feature extraction pipeline. Features associated with clinical outcomes were defined and tested on independent development and validation cohorts. Cases were classified into high or low risk for recurrence, progression, BCG unresponsive disease, and cystectomy. 944 cases (development:303, validation:641, median follow-up:36 months) representative of the intended use population were included (high-grade Ta:34.1%, high-grade T1:54.8%; carcinoma-in-situ only:11.1%, any carcinoma-in-situ:31.4%). In the validation cohort, "High recurrence risk" cases had inferior high-grade recurrence-free survival versus "Low recurrence risk" cases (HR 2.08, p<0.0001). "High progression risk" patients had poorer progression-free survival (HR 3.87, p<0.001) and higher risk of cystectomy (HR 3.35, p<0.001) than "Low progression risk". Cases harboring the BCG unresponsive disease signature had a shorter time to development of BCG unresponsive disease than cases without the signature (HR 2.31, p<0.0001). AI assays provided predictive information beyond clinicopathologic factors. We developed and validated AI-based histologic assays that identify high-risk non-muscle invasive bladder cancer cases at higher risk of recurrence, progression, BCG unresponsive disease, and cystectomy, potentially aiding clinical decision-making.