{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,27]],"date-time":"2026-08-27T16:24:51Z","timestamp":1787847891285,"version":"build-2784847793"},"reference-count":27,"publisher":"Oxford University Press (OUP)","license":[{"start":{"date-parts":[[2026,7,10]],"date-time":"2026-07-10T00:00:00Z","timestamp":1783641600000},"content-version":"am","delay-in-days":0,"URL":"https:\/\/academic.oup.com\/pages\/standard-publication-reuse-rights"}],"funder":[{"DOI":"10.13039\/100000054","name":"National Cancer Institute","doi-asserted-by":"publisher","award":["R01 CA296792-01"],"award-info":[{"award-number":["R01 CA296792-01"]}],"id":[{"id":"10.13039\/100000054","id-type":"DOI","asserted-by":"publisher"}]},{"name":"UCSF Goldberg-Benioff Program in Translational Cancer Biology"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>A multimodal artificial intelligence (AI) model has been validated in prostate biopsy specimens to guide treatment intensification in men receiving radiation. The multimodal AI model has been explored to an extent for prostatectomy patients and has not yet been examined in relation to established genomic scores.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>We applied the multimodal AI biopsy model to a tissue microarray derived from of 424 prostatectomy patients with long-term follow-up. Multimodal AI scores were derived from digitized pathology images and clinical variables. Associations with biochemical recurrence and metastasis were tested using logistic and Cox regression, adjusting for the Cancer of the Prostate Risk Assessment (CAPRA) and genomic cell cycle progression scores.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>Multimodal AI scores were generated from a single tissue microarray spot for each of 414 (98%) patients. At 10\u2009years, recurrence-free and metastasis-free survival were 74% and 96%, respectively. In univariable models, the multimodal AI score was statistically significantly associated with biochemical recurrence (hazard ratio [HR] = 1.04, 95% CI = 1.02 to 1.06) and metastasis (HR = 1.05, 95% CI = 1.02 to 1.07). The multimodal AI score was not independently prognostic after adjustment for CAPRA but remained statistically significant when adjusted for cell cycle progression. Correlation between multimodal AI score and either CAPRA or CCP was modest (r\u2009&amp;lt;\u20090.35). The model combining multimodal AI score and cell cycle progression achieved the highest discrimination for metastasis (C index 0.76) comparable with CAPRA (C index 0.75).<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>The multimodal AI score, originally developed for whole slide biopsy specimens, was prognostic when applied to a tissue microarray of prostatectomy specimens despite not being designed for tissue microarrays. Although not outperforming established clinical tools, it provided complementary information when combined with genomic data. The multimodal AI platform merits further refinement and validation in diverse clinical settings.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1093\/jnci\/djag210","type":"journal-article","created":{"date-parts":[[2026,7,10]],"date-time":"2026-07-10T13:42:48Z","timestamp":1783690968000},"source":"Crossref","is-referenced-by-count":0,"title":["Combining pathology artificial intelligence and genomic biomarkers to refine long-term post-prostatectomy outcome prediction"],"prefix":"10.1093","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-4339-6685","authenticated-orcid":false,"given":"Matthew R","family":"Cooperberg","sequence":"first","affiliation":[{"name":"Department of Urology, University of California, San Francisco, Helen Diller Family Comprehensive Cancer Center , San Francisco, CA,","place":["United States"]},{"name":"Department of Epidemiology and Biostatistics, University of California , San Francisco, CA,","place":["United 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