{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,1]],"date-time":"2026-10-01T07:59:49Z","timestamp":1790841589931,"version":"4.1.0"},"reference-count":19,"publisher":"Oxford University Press (OUP)","issue":"2","license":[{"start":{"date-parts":[[2026,4,10]],"date-time":"2026-04-10T00:00:00Z","timestamp":1775779200000},"content-version":"vor","delay-in-days":38,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2026,3,3]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:p>The ArteraAI Prostate Test (ArteraAI Inc.) is the first predictive biomarker for the benefit of adding short-term androgen deprivation therapy (ADT) to radiotherapy for intermediate-risk prostate cancer. We evaluated the cost-effectiveness of ArteraAI to guide short-term ADT using a Markov model simulating 15-year outcomes for 71-year-old patients with intermediate-risk prostate cancer receiving radiotherapy using NRG\/RTOG 9408 data on which ArteraAI was validated. Three strategies were compared: (1) all patients receive ADT (ADT-for-all), (2) only patients with unfavorable intermediate-risk prostate cancer receive ADT (National Comprehensive Cancer Network [NCCN]), and (3) only ArteraAI-positive patients receive ADT (ArteraAI). Costs and utilities obtained from Medicare claims and published literature were used to calculate incremental cost-effectiveness ratios. A willingness-to-pay threshold of $100\u2009000\/quality-adjusted life year (QALY) was chosen. The ADT-for-all strategy was dominated by the NCCN strategy. Compared with the NCCN strategy, the ArteraAI strategy lowered costs by $12\u2009296 and improved effectiveness by 0.01 QALYs making it dominant.<\/jats:p>","DOI":"10.1093\/jncics\/pkag035","type":"journal-article","created":{"date-parts":[[2026,4,8]],"date-time":"2026-04-08T11:51:54Z","timestamp":1775649114000},"source":"Crossref","is-referenced-by-count":1,"title":["Cost-effectiveness of an artificial intelligence predictive model for guiding androgen deprivation therapy in intermediate-risk prostate cancer"],"prefix":"10.1093","volume":"10","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-7625-3678","authenticated-orcid":false,"given":"P Travis","family":"Courtney","sequence":"first","affiliation":[{"name":"Department of Radiation Oncology, University of California , Los Angeles, CA,","place":["United States"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ya-Chen Tina","family":"Shih","sequence":"additional","affiliation":[{"name":"Department of Radiation Oncology, University of California , Los Angeles, CA,","place":["United States"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Albert J","family":"Chang","sequence":"additional","affiliation":[{"name":"Department of Radiation Oncology, University of California , Los Angeles, CA,","place":["United States"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Alan","family":"Lee","sequence":"additional","affiliation":[{"name":"Department of Radiation Oncology, University of California , Los Angeles, CA,","place":["United States"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Michael L","family":"Steinberg","sequence":"additional","affiliation":[{"name":"Department of Radiation Oncology, University of California , Los Angeles, CA,","place":["United States"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5781-4174","authenticated-orcid":false,"given":"Luca 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