biostudies-literatureUnknownMorgan TMNCI NIH HHS<h4>Background and objective</h4>Biochemical recurrence (BCR) after radical prostatectomy (RP) is a heterogeneous disease state in prostate cancer with multiple treatment options. Improved risk stratification could enable more personalized decision-making. We developed and validated a digital pathology-based multimodal artificial intelligence (MMAI) model to predict outcomes in post-RP BCR patients undergoing salvage therapy.<h4>Methods</h4>An MMAI model was trained to predict distant metastasis (DM) using prostate histopathology image features and clinical variables (pathologic grade group, pathologic T stage, prostate-specific antigen level before salvage radiotherapy [SRT], age, and surgical margin). The locked model was validated in 533 patients from NRG/RTOG 9601 and 0534 treated withEuropean urologyS0302-2838(25)04859-6https://www.ebi.ac.uk/biostudies/studies/S-EPMC12774449biostudies-literatureDevelopment and Validation of a Multimodal Artificial Intelligence-derived Digital Pathology-based Biomarker Predicting Metastasis Among Patients with Biochemical Recurrence After Radical Prostatectomy in NRG/RTOG Trials.PMC12774449UG1 CA189867U24 CA196067U10 CA180868U10 CA180822Zwerink WEfstathiou JARen YPugh SLMichalski JMGreenberg MJFeng FYMartin AGRoss AEHoffman KETang SPollack AEsteva ANguyen PLMitani ASpratt DETran PTBahary JPSimko JPSandler HMChen EDeVries SWilke DRoyce TJMorgan TMHuang HCBalogh AGfalseDevelopment and Validation of a Multimodal Artificial Intelligence-derived Digital Pathology-based Biomarker Predicting Metastasis Among Patients with Biochemical Recurrence After Radical Prostatectomy in NRG/RTOG Trials.<h4>Background and objective</h4>Biochemical recurrence (BCR) after radical prostatectomy (RP) is a heterogeneous disease state in prostate cancer with multiple treatment options. Improved risk stratification could enable more personalized decision-making. We developed and validated a digital pathology-based multimodal artificial intelligence (MMAI) model to predict outcomes in post-RP BCR patients undergoing salvage therapy.<h4>Methods</h4>An MMAI model was trained to predict distant metastasis (DM) using prostate histopathology image features and clinical variables (pathologic grade group, pathologic T stage, prostate-specific antigen level before salvage radiotherapy [SRT], age, and surgical margin). The locked model was validated in 533 patients from NRG/RTOG 9601 and 0534 treated with2025-01-01T00:00:00Z2025 Dec2026-06-06T10:52:52.817Z2026-05-29T03:12:38.999ZS-EPMC127744494143631510.1016/j.eururo.2025.12.007