{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,28]],"date-time":"2026-08-28T07:25:49Z","timestamp":1787901949053,"version":"build-2784847793"},"reference-count":27,"publisher":"American Society of Clinical Oncology (ASCO)","issue":"1","content-domain":{"domain":["ascopubs.org"],"crossmark-restriction":true},"short-container-title":["JCO Clin Cancer Inform"],"published-print":{"date-parts":[[2026,1]]},"abstract":"<jats:sec>\n                    <jats:title>PURPOSE<\/jats:title>\n                    <jats:p>This study assessed the feasibility of developing the University of Maryland Marlene and Stewart Greenebaum Comprehensive Cancer Center (UMGCCC)-Medicare\u2013linked database infrastructure by integrating tumor registry, electronic health records (EHRs), and Medicare administrative claims data. The database was designed to support research identifying determinants of differences in cancer outcomes among patient populations commonly under-represented in clinical trials (based on the US population with the disease) including older adults.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>METHODS<\/jats:title>\n                    <jats:p>Patients 65 years and older who were diagnosed and\/or received their first course of treatment for a primary tumor at UMGCCC from 2018 to 2021 were included in the database. A two-stage data linkage process was used to merge cancer center tumor registry data with EHR and Medicare claims data. We performed data quality and linkage quality checks. Summary statistics were calculated for patient and tumor characteristics.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>RESULTS<\/jats:title>\n                    <jats:p>Of the 3,322 patients identified from the tumor registry, 3,119 patients (94%) were included in the UMGCCC-Medicare database (mean age 73.1 years, 56% male, 31% Black). Lung cancers were the most common (15%) followed by oral cancers (12%) and non-Hodgkin lymphoma (6%).<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>CONCLUSION<\/jats:title>\n                    <jats:p>The development of the UMGCCC-Medicare database serves as proof of concept for linking real-world data from different sources. The database is a valuable resource for research requiring detailed patient-level data and follow-up that may generate real-world evidence for older adults living in the United States and treated in routine oncology practice.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1200\/cci-25-00276","type":"journal-article","created":{"date-parts":[[2026,3,18]],"date-time":"2026-03-18T20:00:14Z","timestamp":1773864014000},"update-policy":"https:\/\/doi.org\/10.1200\/crossmark","source":"Crossref","is-referenced-by-count":1,"title":["Building Capacity for Research on Cancer, Older Adults, and Under-Represented Populations: Methods and Lessons Learned From the Development of the University of Maryland Marlene and Stewart Greenebaum Comprehensive Cancer Center-Medicare Database"],"prefix":"10.1200","volume":"10","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-0633-3140","authenticated-orcid":true,"given":"Tsung-Ying","family":"Lee","sequence":"first","affiliation":[{"name":"Department of 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