{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,29]],"date-time":"2026-07-29T16:02:31Z","timestamp":1785340951424,"version":"3.55.0"},"reference-count":20,"publisher":"American Medical Association (AMA)","issue":"7","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["JAMA Netw Open"],"abstract":"\n Importance<\/jats:title>\n Genomic testing plays a central role in precision oncology by guiding targeted therapies. Medicare established national coverage determinations (NCDs) for next-generation sequencing (NGS) in 2018 and 2020, yet population-level adoption patterns remain underexamined.<\/jats:p>\n <\/jats:sec>\n \n Objective<\/jats:title>\n To examine trends and variation in uptake of NGS and non-NGS genomic testing among Medicare beneficiaries with common cancers.<\/jats:p>\n <\/jats:sec>\n \n Design, Setting, and Participants<\/jats:title>\n This retrospective cohort study used Medicare fee-for-service beneficiaries aged 66 years or older with claims from January 1, 2016, to December 31, 2023. Beneficiaries with incident lung, breast, colorectal, prostate, or endometrial cancer were identified using the Chronic Conditions Data Warehouse. The data analysis was performed from July 1 to December 31, 2025.<\/jats:p>\n <\/jats:sec>\n \n Exposures<\/jats:title>\n Cancer types, time periods defined by implementation of Medicare NCDs for somatic NGS (March 16, 2018) and germline NGS (January 27, 2020), and patient characteristics (age, race and ethnicity, and geographic location).<\/jats:p>\n <\/jats:sec>\n \n Main Outcomes and Measures<\/jats:title>\n Outcomes were receipt of NGS testing (primary) and receipt of any genomic testing and shift to NGS testing among tested beneficiaries (secondary), within 180 days after the first cancer diagnosis claim. Testing rates were described by cancer type and over time. Multivariable logistic regression was used to estimate adjusted probabilities of receiving NGS testing.<\/jats:p>\n <\/jats:sec>\n \n Results<\/jats:title>\n \n Of 391\u202f151 Medicare beneficiaries with cancer (50.6% were female; 31.8% were older than 75 years), 7.0% received non-NGS testing only, 1.2% NGS only, 0.5% both, and 91.4% no genomic testing. NGS adoption increased modestly, whereas overall genomic testing nearly tripled from 6.0% in 2016 to 16.7% in 2023. Uptake varied across cancers; beneficiaries with lung cancer had the highest NGS uptake (1.6% in 2016 vs 9.2% in 2023;\n P<\/jats:italic>\n \u2009&amp;lt;\u2009.001), whereas beneficiaries with breast cancer showed the sharpest increase in non-NGS testing without a parallel increase in NGS. Beneficiaries with colorectal or endometrial cancer showed a moderate increase, whereas beneficiaries with prostate cancer had the lowest uptake for any genomic testing. In adjusted analyses, the largest increase was observed among beneficiaries with lung cancer (5.16 percentage points [95% CI, 4.75-5.56 percentage points];\n P<\/jats:italic>\n \u2009&amp;lt;\u2009.001) during the post-germline NCD phase.\n <\/jats:p>\n <\/jats:sec>\n \n Conclusions and Relevance<\/jats:title>\n In this cohort study of Medicare beneficiaries with cancer, genomic testing increased after NCD implementation, with increases driven by NGS among beneficiaries with lung cancer and non-NGS among beneficiaries with breast cancer. Overall, NGS uptake remained modest, highlighting persistent gaps in access to precision oncology testing.<\/jats:p>\n <\/jats:sec>","DOI":"10.1001\/jamanetworkopen.2026.26078","type":"journal-article","created":{"date-parts":[[2026,7,29]],"date-time":"2026-07-29T15:30:34Z","timestamp":1785339034000},"page":"e2626078","source":"Crossref","is-referenced-by-count":0,"title":["Genomic Testing Uptake Among Medicare Beneficiaries With Cancer"],"prefix":"10.1001","volume":"9","author":[{"given":"So-Yeon","family":"Kang","sequence":"first","affiliation":[{"name":"Department of Health Management and Policy, Georgetown University School of Health, Washington, DC"},{"name":"Cancer Prevention and Control Program, Lombardi Comprehensive Cancer Center, Georgetown University Medical Center, Washington, DC"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Rui","family":"Zhang","sequence":"additional","affiliation":[{"name":"Department of Biostatistics, Bioinformatics, and Biomathematics, Georgetown University, Washington, DC"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Chul","family":"Kim","sequence":"additional","affiliation":[{"name":"Cancer Prevention and Control Program, Lombardi Comprehensive Cancer Center, Georgetown University Medical Center, Washington, DC"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Marc D.","family":"Schwartz","sequence":"additional","affiliation":[{"name":"Cancer Prevention and Control Program, Lombardi Comprehensive Cancer Center, Georgetown University Medical Center, Washington, DC"},{"name":"Jess and Mildred Fisher Center for Hereditary Cancer and Clinical Genomics Research, Washington, DC"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jaeil","family":"Ahn","sequence":"additional","affiliation":[{"name":"Cancer Prevention and Control Program, Lombardi Comprehensive Cancer Center, Georgetown University Medical Center, Washington, DC"},{"name":"Department of Biostatistics, Bioinformatics, and Biomathematics, Georgetown University, Washington, DC"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Arnold L.","family":"Potosky","sequence":"additional","affiliation":[{"name":"Cancer Prevention and Control Program, Lombardi Comprehensive Cancer Center, Georgetown University Medical Center, Washington, DC"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Carole Roan","family":"Gresenz","sequence":"additional","affiliation":[{"name":"McCourt School of Public Policy, Georgetown University, Washington, DC"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"10","published-online":{"date-parts":[[2026,7,29]]},"reference":[{"issue":"1","key":"zoi260721r2","first-page":"36","article-title":"Targeted therapy for non-small cell lung cancer: current standards and the promise of the future.","volume":"4","author":"Chan","year":"2015","journal-title":"Transl Lung Cancer 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Oncol"},{"issue":"2","key":"zoi260721r14","doi-asserted-by":"publisher","first-page":"349","DOI":"10.1377\/hlthaff.2020.01786","article-title":"Variation in telemedicine use and outpatient care during the COVID-19 pandemic in the United States: study examines variation in total US outpatient visits and telemedicine use across patient demographics, specialties, and conditions during the COVID-19 pandemic.","volume":"40","author":"Patel","year":"2021","journal-title":"Health Aff"},{"key":"zoi260721r15","doi-asserted-by":"publisher","DOI":"10.1093\/jnci\/djz183","article-title":"The association between Medicare low-income subsidy and anticancer treatment uptake in advanced lung cancer.","author":"Chou","year":"2020","journal-title":"J Natl Cancer Inst"},{"issue":"27","key":"zoi260721r17","doi-asserted-by":"publisher","first-page":"3205","DOI":"10.1200\/JCO.22.01063","article-title":"Biomarkers for systemic therapy in metastatic breast cancer: ASCO guideline update.","volume":"40","author":"Henry","year":"2022","journal-title":"J Clin Oncol"},{"issue":"7","key":"zoi260721r18","doi-asserted-by":"publisher","DOI":"10.1200\/PO.22.00715","article-title":"Comprehensive review on the clinical impact of next-generation sequencing tests for the management of advanced cancer.","volume":"7","author":"Gibbs","year":"2023","journal-title":"JCO Precis Oncol"},{"issue":"1","key":"zoi260721r19","doi-asserted-by":"publisher","first-page":"43","DOI":"10.1001\/jama.2023.9526","article-title":"Germline genetic testing after cancer diagnosis.","volume":"330","author":"Kurian","year":"2023","journal-title":"JAMA"},{"issue":"3","key":"zoi260721r20","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1200\/PO.18.00356","article-title":"Economic impact of next-generation sequencing versus single-gene testing to detect genomic alterations in metastatic non-small-cell lung cancer using a decision analytic model.","volume":"3","author":"Pennell","year":"2019","journal-title":"JCO Precis Oncol"},{"key":"zoi260721r1","unstructured":"Focus Area FDA. Individualized therapeutics and precision medicine. U.S. Food and Drug Administration. Published September 6, 2022. Accessed June 18, 2026. https:\/\/www.fda.gov\/science-research\/focus-areas-regulatory-science-report\/focus-area-individualized-therapeutics-and-precision-medicine"},{"key":"zoi260721r7","unstructured":"Next Generation Sequencing (NGS) for Medicare Beneficiaries with Advanced Cancer. Center for Medicare and Medicaid. Accessed June 18, 2026. https:\/\/www.cms.gov\/medicare-coverage-database\/view\/ncacal-tracking-sheet.aspx?NCAId=296"},{"key":"zoi260721r8","unstructured":"National coverage determination (NCD). Next generation sequencing (NGS). Centers for Medicare & Medicaid Services. January 27, 2020. Accessed June 18, 2026. https:\/\/www.cms.gov\/medicare-coverage-database\/details\/ncd-details.aspx?NCDId=372"},{"key":"zoi260721r16","unstructured":"2024 NCCN Clinical Practice Guidelines in Oncology (NCCN Guidelines) update: impact on NSCLC landscape. Journal of Clinical Pathways. November 15, 2024. 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