{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,1]],"date-time":"2026-05-01T21:22:07Z","timestamp":1777670527074,"version":"3.51.4"},"reference-count":44,"publisher":"Oxford University Press (OUP)","issue":"2","license":[{"start":{"date-parts":[[2026,2,5]],"date-time":"2026-02-05T00:00:00Z","timestamp":1770249600000},"content-version":"vor","delay-in-days":1,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"funder":[{"name":"University of California San Francisco Helen Diller Family Comprehensive Cancer Center Diversity, Equity, Inclusion and Accessibility"},{"name":"American Society of Clinical Oncology Conquer Cancer Foundation Award"},{"name":"Radiation Oncology Institute Award"},{"name":"University of California San Francisco Computational Cancer Research Award"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2026,3,3]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>Radiation therapy (RT) plays a crucial role in managing cancer-related symptoms. This study characterized symptom documentation, especially pain, preceding bone metastasis diagnosis and initiation of RT for bone metastasis using natural language processing approaches.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>A deidentified cohort of patients who received RT for bone metastasis at a single tertiary-care institution (2013-2023) was created. Clinical data, notes, and metadata were computationally extracted. A previously validated natural language processing pipeline based on Apache clinical Text Analysis and Knowledge Extraction System was used to extract Common Terminology Criteria for Adverse Events\u2013encoded symptoms from all notes in the 30\u2009days preceding bone metastasis diagnosis and each course of RT for bone metastasis. Logistic regression analyses examined the association between clinical and demographic variables and pain documentation.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>In all, 1061 patients (median [IQR] age, 64 [54-72] years; 582 [54.9%] men) received 1718 courses of RT for bone metastases. The most common documented symptoms before bone metastasis diagnosis and first RT for bone metastasis, respectively, were bone metastasis\u2013related pain (52.5% vs 91.6%, P\u2009&amp;lt;\u2009.001), nausea (20.8% vs 48.9%, P\u2009&amp;lt;\u2009.001), and constipation (12.8% vs 34.2%, P\u2009&amp;lt;\u2009.001). Before bone metastasis diagnosis, multiracial or a race other than Asian, Black, or White (odds ratio\u2009=\u20090.61, 95% confidence interval\u2009=\u20090.38 to 0.99]; P\u2009=\u2009.045) was associated with decreased pain documentation compared with White race. Before RT for bone metastases, women (odds ratio\u2009=\u20091.48, 95% confidence interval\u2009=\u20091.02 to 2.15, P\u2009=\u2009.04) had increased pain documentation compared with men.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>Women and patients who identified as multiracial or a race other than Asian, Black, or White experienced a relative increase in pain documentation from bone metastasis diagnosis to RT for bone metastases. This finding may reflect differential decision-making for which patients are offered RT for bone metastases sooner in the symptom trajectory. Interventions are needed to increase equitable distribution of RT.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1093\/jncics\/pkag010","type":"journal-article","created":{"date-parts":[[2026,1,29]],"date-time":"2026-01-29T12:46:17Z","timestamp":1769690777000},"source":"Crossref","is-referenced-by-count":0,"title":["Natural language processing to identify documented pain preceding radiation therapy for bone metastases"],"prefix":"10.1093","volume":"10","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-5380-4825","authenticated-orcid":false,"given":"Jie Jane","family":"Chen","sequence":"first","affiliation":[{"name":"Department of Radiation Oncology, University of California San Francisco , San Francisco, CA,","place":["United States"]}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jean","family":"Feng","sequence":"additional","affiliation":[{"name":"Department of Epidemiology and Biostatistics, University of California San Francisco , San Francisco, 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Francisco , San Francisco, CA,","place":["United States"]}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0004-9204-2423","authenticated-orcid":false,"given":"Marianna V","family":"Elia","sequence":"additional","affiliation":[{"name":"UCSF UC Berkeley Joint Program in Computational Health , San Francisco, CA,","place":["United States"]}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9522-0900","authenticated-orcid":false,"given":"Lisa","family":"Ni","sequence":"additional","affiliation":[{"name":"Department of Radiation Oncology, University of California San Francisco , San Francisco, CA,","place":["United States"]}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9756-4037","authenticated-orcid":false,"given":"Felix Y","family":"Feng","sequence":"additional","affiliation":[{"name":"Department of Radiation Oncology, University of California San Francisco , San Francisco, CA,","place":["United States"]}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0095-8951","authenticated-orcid":false,"given":"Michael W","family":"Rabow","sequence":"additional","affiliation":[{"name":"Department of Internal Medicine, Division of Palliative Medicine, University of California San Francisco , San Francisco, CA,","place":["United States"]},{"name":"Department of Urology, University of California San Francisco , San Francisco, CA,","place":["United States"]}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9841-9357","authenticated-orcid":false,"given":"Steve E","family":"Braunstein","sequence":"additional","affiliation":[{"name":"Department of Radiation Oncology, University of California San Francisco , San Francisco, CA,","place":["United 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