{"database":"biostudies-literature","file_versions":[],"scores":null,"additional":{"omics_type":["Unknown"],"submitter":["Morgan TM"],"funding":["NCI NIH HHS"],"pubmed_abstract":["Background and objective
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.Methods
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 with"],"journal":["European urology"],"pagination":["S0302-2838(25)04859-6"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/S-EPMC12774449"],"repository":["biostudies-literature"],"pubmed_title":["Development 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."],"pmcid":["PMC12774449"],"funding_grant_id":["UG1 CA189867","U24 CA196067","U10 CA180868","U10 CA180822"],"pubmed_authors":["Zwerink W","Efstathiou JA","Ren Y","Pugh SL","Michalski JM","Greenberg MJ","Feng FY","Martin AG","Ross AE","Hoffman KE","Tang S","Pollack A","Esteva A","Nguyen PL","Mitani A","Spratt DE","Tran PT","Bahary JP","Simko JP","Sandler HM","Chen E","DeVries S","Wilke D","Royce TJ","Morgan TM","Huang HC","Balogh AG"],"additional_accession":[]},"is_claimable":false,"name":"Development 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.","description":"Background and objective
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.Methods
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 with","dates":{"release":"2025-01-01T00:00:00Z","publication":"2025 Dec","modification":"2026-06-06T10:52:52.817Z","creation":"2026-05-29T03:12:38.999Z"},"accession":"S-EPMC12774449","cross_references":{"pubmed":["41436315"],"doi":["10.1016/j.eururo.2025.12.007"]}}