{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,27]],"date-time":"2026-10-27T18:39:04Z","timestamp":1793126344743,"version":"4.5.0"},"reference-count":30,"publisher":"American Society of Clinical Oncology (ASCO)","issue":"8","content-domain":{"domain":["ascopubs.org"],"crossmark-restriction":true},"short-container-title":["JCO Precis Oncol"],"published-print":{"date-parts":[[2024,10]]},"abstract":"<jats:sec>\n            <jats:title>PURPOSE<\/jats:title>\n            <jats:p>Current clinical risk stratification methods for localized prostate cancer are suboptimal, leading to over- and undertreatment. Recently, machine learning approaches using digital histopathology have shown superior prognostic ability in phase III trials. This study aims to develop a clinically usable risk grouping system using multimodal artificial intelligence (MMAI) models that outperform current National Comprehensive Cancer Network (NCCN) risk groups.<\/jats:p>\n          <\/jats:sec>\n          <jats:sec>\n            <jats:title>MATERIALS AND METHODS<\/jats:title>\n            <jats:p>The cohort comprised 9,787 patients with localized prostate cancer from eight NRG Oncology randomized phase III trials, treated with radiation therapy, androgen deprivation therapy, and\/or chemotherapy. Locked MMAI models, which used digital histopathology images and clinical data, were applied to each patient. Expert consensus on cut points defined low-, intermediate-, and high-risk groups on the basis of 10-year distant metastasis rates of 3% and 10%, respectively. The MMAI's reclassification and prognostic performance were compared with the three-tier NCCN risk groups.<\/jats:p>\n          <\/jats:sec>\n          <jats:sec>\n            <jats:title>RESULTS<\/jats:title>\n            <jats:p>The median follow-up for censored patients was 7.9 years. According to NCCN risk categories, 30.4% of patients were low-risk, 25.5% intermediate-risk, and 44.1% high-risk. The MMAI risk classification identified 43.5% of patients as low-risk, 34.6% as intermediate-risk, and 21.8% as high-risk. MMAI reclassified 1,039 (42.0%) patients initially categorized by NCCN. Despite the MMAI low-risk group being larger than the NCCN low-risk group, the 10-year metastasis risks were comparable: 1.7% (95% CI, 0.2 to 3.2) for NCCN and 3.2% (95% CI, 1.7 to 4.7) for MMAI. The overall 10-year metastasis risk for NCCN high-risk patients was 16.6%, with MMAI further stratifying this group into low-, intermediate-, and high-risk, showing metastasis rates of 3.4%, 8.2%, and 26.3%, respectively.<\/jats:p>\n          <\/jats:sec>\n          <jats:sec>\n            <jats:title>CONCLUSION<\/jats:title>\n            <jats:p>The MMAI risk grouping system expands the population of men identified as having low metastatic risk and accurately pinpoints a high-risk subset with elevated metastasis rates. This approach aims to prevent both overtreatment and undertreatment in localized prostate cancer, facilitating shared decision making.<\/jats:p>\n          <\/jats:sec>","DOI":"10.1200\/po.24.00145","type":"journal-article","created":{"date-parts":[[2024,10,24]],"date-time":"2024-10-24T19:59:09Z","timestamp":1729799949000},"update-policy":"https:\/\/doi.org\/10.1200\/crossmark","source":"Crossref","is-referenced-by-count":23,"title":["Prostate Cancer Risk Stratification in NRG Oncology Phase III Randomized Trials Using Multimodal Deep Learning With Digital Histopathology"],"prefix":"10.1200","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-7765-4473","authenticated-orcid":true,"given":"Jonathan David","family":"Tward","sequence":"first","affiliation":[{"name":"Department of Radiation Oncology, University of Utah, Salt Lake City, UT"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Huei-Chung","family":"Huang","sequence":"additional","affiliation":[{"name":"Artera, Inc, 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Evanston, IL"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1140-0603","authenticated-orcid":true,"given":"Todd M.","family":"Morgan","sequence":"additional","affiliation":[{"name":"Division of Urologic Oncology, University of Michigan Comprehensive Cancer Center, Ann Arbor, MI"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jedidiah M.","family":"Monson","sequence":"additional","affiliation":[{"name":"Department of Radiation Oncology, Saint Agnes Medical Center, Fresno, CA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"James A.","family":"Wallace","sequence":"additional","affiliation":[{"name":"Ingalls Memorial Hospital, Harvey, IL"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jean-Paul","family":"Bahary","sequence":"additional","affiliation":[{"name":"Department of Radiation Oncology, CHUM\u2014Centre Hospitalier de l\u2019Universite de Montreal, Montreal, QC, 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