{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"institution":[{"name":"medRxiv"}],"indexed":{"date-parts":[[2026,5,23]],"date-time":"2026-05-23T15:05:52Z","timestamp":1779548752029,"version":"3.53.1"},"posted":{"date-parts":[[2026,5,21]]},"group-title":"Genetic and Genomic Medicine","reference-count":43,"publisher":"openRxiv","license":[{"start":{"date-parts":[[2026,5,21]],"date-time":"2026-05-21T00:00:00Z","timestamp":1779321600000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"accepted":{"date-parts":[[2026,5,21]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                <jats:sec>\n                  <jats:title>Importance<\/jats:title>\n                  <jats:p>\n                    <jats:italic>BRCA<\/jats:italic>\n                    genetic testing is critical for cancer risk assessment, treatment and personalization, yet substantial underutilization persists. Socioeconomic and clinical factors may strongly influence testing uptake; therefore, identifying the potential drivers to\n                    <jats:italic>BRCA<\/jats:italic>\n                    testing and treatment is essential for addressing gaps in access, increasing retention into care, and improving cancer outcomes.\n                  <\/jats:p>\n                <\/jats:sec>\n                <jats:sec>\n                  <jats:title>Objective<\/jats:title>\n                  <jats:p>\n                    To quantify the putatively causal effects of SDoH on\n                    <jats:italic>BRCA<\/jats:italic>\n                    genetic testing among individuals with breast, ovarian, pancreatic, and prostate cancers and to develop a predictive model to identify patients at risk for underuse of testing.\n                  <\/jats:p>\n                <\/jats:sec>\n                <jats:sec>\n                  <jats:title>Design, Setting, and Participants<\/jats:title>\n                  <jats:p>This observational case-control study used data from a large multistate clinical research data network covering southern US (2012-2023). The network contained records of more than 26 million individuals and was linked with ZIP code-level SDoH variables derived from national socioeconomic datasets. Adults diagnosed with breast, ovarian, pancreatic, or prostate cancer were eligible for cases (received BRCA testing) or controls (did not receive BRCA testing, matched by cancer diagnosis).<\/jats:p>\n                <\/jats:sec>\n                <jats:sec>\n                  <jats:title>Exposure<\/jats:title>\n                  <jats:p>SDoH categories, including economic conditions, education, healthcare access, neighborhood conditions, and social connectedness.<\/jats:p>\n                <\/jats:sec>\n                <jats:sec>\n                  <jats:title>Main Outcomes and Measures<\/jats:title>\n                  <jats:p>\n                    The primary outcome was receipt of\n                    <jats:italic>BRCA<\/jats:italic>\n                    genetic testing after cancer diagnosis.\n                  <\/jats:p>\n                <\/jats:sec>\n                <jats:sec>\n                  <jats:title>Results<\/jats:title>\n                  <jats:p>\n                    Among 3,279 people diagnosed with cancer, 748 received\n                    <jats:italic>BRCA<\/jats:italic>\n                    testing and 2,531 served as controls. Study population\u2019s mean [SD] age was 66.8 [15.7] years; 1,758 were women [53.6%], 2,238 [69.6%] were White and 616 [18.8%] were Black or African American. Breast (1,420 [42.8%]) and prostate (1,342 [40.9%]) cancers were the most common diagnoses, followed by pancreatic (242 [7.4%]), ovarian (238 [7.2%]), and multiple cancers (55 [1.7%]). Upon adjusting for potential confounding, higher educational attainment (odds ratio [OR], 1.19), public-sector employment (OR, 1.42), neighborhood safety (OR, 1.28), and social participation (OR, 1.72) showed an increased likelihood of undergoing\n                    <jats:italic>BRCA<\/jats:italic>\n                    testing, whereas economic instability, including housing cost burden and reliance on public insurance, had an effect of reduced testing. A random forest classifier demonstrated good discriminative performance (AUROC, 0.776) to predict cancer patients who were likely to take\n                    <jats:italic>BRCA<\/jats:italic>\n                    testing, where nativity, language, and residential stability ranked among the most influential social determinants according to SHapley Additive exPlanations (SHAP) analysis.\n                  <\/jats:p>\n                <\/jats:sec>\n                <jats:sec>\n                  <jats:title>Conclusions and Relevance<\/jats:title>\n                  <jats:p>\n                    In this observational case-control study, SDoHs were strongly associated with receipt of\n                    <jats:italic>BRCA<\/jats:italic>\n                    genetic testing among people with cancer. These findings suggest that disparities in genetic testing may reflect structural and social barriers rather than differences in clinical eligibility alone. Efforts to improve equitable access to genetic testing may benefit from integrating social-context information into clinical workflows and targeting outreach or navigation strategies toward socially disadvantaged populations.\n                  <\/jats:p>\n                <\/jats:sec>\n                <jats:sec>\n                  <jats:title>Key Points<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Question<\/jats:title>\n                    <jats:p>\n                      Do socioeconomic and clinical circumstances contribute to care access gaps to\n                      <jats:italic>BRCA<\/jats:italic>\n                      genetic testing among people with breast, ovarian, prostate, and pancreatic cancers?\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Findings<\/jats:title>\n                    <jats:p>\n                      In a case-control study of 3,279 adults with cancer from a large multi-state US clinical research data network, multiple social determinants of health, including economic conditions, education, healthcare access, neighborhood conditions, and social connectedness, were identified as key determinants of\n                      <jats:italic>BRCA<\/jats:italic>\n                      genetic testing uptake, with variation across age and sex groups.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Meaning<\/jats:title>\n                    <jats:p>\n                      Improving equal access to\n                      <jats:italic>BRCA<\/jats:italic>\n                      genetic testing may require interventions that address financial barriers and strengthen social, and community supports that influence engagement with genetic services.\n                    <\/jats:p>\n                  <\/jats:sec>\n                <\/jats:sec>","DOI":"10.64898\/2026.05.14.26353261","type":"posted-content","created":{"date-parts":[[2026,5,22]],"date-time":"2026-05-22T00:35:18Z","timestamp":1779410118000},"source":"Crossref","is-referenced-by-count":0,"title":["Socioeconomic and Clinical Determinants Driving Access to BRCA Genetic Testing in Cancer : A Case-Control Study Using Observational Electronic Health Records Across Multiple Sites"],"prefix":"10.64898","author":[{"given":"Qiang","family":"Yang","sequence":"first","affiliation":[{"name":"Department of Health Outcomes and Biomedical Informatics, University of Florida, College of Medicine, Gainesville, FL 32610, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Chengrong","family":"Wang","sequence":"additional","affiliation":[{"name":"Department of Health Outcomes and Biomedical Informatics, University of Florida, College of Medicine, Gainesville, FL 32610, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Charite","family":"Ricker","sequence":"additional","affiliation":[{"name":"Keck School of Medicine, University of Southern California, Los Angeles, CA 90033, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Sandra G.","family":"Suther","sequence":"additional","affiliation":[{"name":"College of Pharmacy and Pharmaceutical Sciences, Institute of Public Health, Florida Agricultural and Mechanical University, Tallahassee, FL 32307, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4455-5302","authenticated-orcid":false,"given":"Qianqian","family":"Song","sequence":"additional","affiliation":[{"name":"Department of Health Outcomes and Biomedical Informatics, University of Florida, College of Medicine, Gainesville, FL 32610, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Sarah","family":"Khan","sequence":"additional","affiliation":[{"name":"UF Health Breast Center, University of Florida, Jacksonville, FL 32209, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0587-4105","authenticated-orcid":false,"given":"Yi","family":"Guo","sequence":"additional","affiliation":[{"name":"Department of Health Outcomes and Biomedical Informatics, University of Florida, College of Medicine, Gainesville, FL 32610, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Thomas J","family":"George","sequence":"additional","affiliation":[{"name":"Department of Medicine, Division of Hematology & Oncology, University of Florida, Gainesville, FL 32610, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mattia","family":"Prosperi","sequence":"additional","affiliation":[{"name":"Department of Epidemiology, College of Public Health and Health Professions, College of Medicine, University of Florida, Gainesville, FL 32610, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1403-0396","authenticated-orcid":false,"given":"Rui","family":"Yin","sequence":"additional","affiliation":[{"name":"Department of Health Outcomes and Biomedical Informatics, University of Florida, College of Medicine, Gainesville, FL 32610, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"54368","reference":[{"key":"2026052307301078000_2026.05.14.26353261v1.1","doi-asserted-by":"publisher","DOI":"10.1093\/annonc\/mdv278"},{"key":"2026052307301078000_2026.05.14.26353261v1.2","first-page":"369","article-title":"The importance of BRCA1 and BRCA2 genes mutations in breast cancer development","volume":"30","year":"2016","journal-title":"Med. J. Islam. Repub. Iran"},{"key":"2026052307301078000_2026.05.14.26353261v1.3","doi-asserted-by":"publisher","DOI":"10.1016\/j.ejca.2020.12.023"},{"key":"2026052307301078000_2026.05.14.26353261v1.4","doi-asserted-by":"crossref","first-page":"815","DOI":"10.2147\/OTT.S369844","article-title":"Management strategies of breast cancer patients with BRCA1 and BRCA2 pathogenic germline variants","volume":"15","year":"2022","journal-title":"Onco. Targets. Ther"},{"key":"2026052307301078000_2026.05.14.26353261v1.5","doi-asserted-by":"crossref","first-page":"111","DOI":"10.9734\/jcti\/2025\/v15i2296","article-title":"BRCA mutations in breast cancer insights into genetic risk and tailored therapeutic interventions","volume":"15","year":"2025","journal-title":"J. Canc. Tumor Int"},{"key":"2026052307301078000_2026.05.14.26353261v1.6","doi-asserted-by":"crossref","unstructured":"Kurian, A. W. et al. Genetic testing and counseling among patients with newly diagnosed breast cancer. JAMA 317, 531 (2017).","DOI":"10.1001\/jama.2016.16918"},{"key":"2026052307301078000_2026.05.14.26353261v1.7","doi-asserted-by":"publisher","DOI":"10.1038\/s41416-018-0127-5"},{"key":"2026052307301078000_2026.05.14.26353261v1.8","doi-asserted-by":"crossref","first-page":"839","DOI":"10.1007\/s10549-020-06038-x","article-title":"BRCA testing and outcomes in women with breast cancer","volume":"186","year":"2021","journal-title":"Breast Cancer Res. Treat"},{"key":"2026052307301078000_2026.05.14.26353261v1.9","doi-asserted-by":"publisher","DOI":"10.6004\/jnccn.2006.0050"},{"key":"2026052307301078000_2026.05.14.26353261v1.10","doi-asserted-by":"publisher","DOI":"10.1001\/jama.298.24.2869"},{"key":"2026052307301078000_2026.05.14.26353261v1.11","doi-asserted-by":"crossref","first-page":"871","DOI":"10.1001\/jamaoncol.2022.0476","article-title":"Expansion of cancer risk profile for BRCA1 and BRCA2 pathogenic variants","volume":"8","year":"2022","journal-title":"JAMA Oncol"},{"key":"2026052307301078000_2026.05.14.26353261v1.12","doi-asserted-by":"crossref","unstructured":"Grindedal, E. M. et al. Current guidelines for BRCA testing of breast cancer patients are insufficient to detect all mutation carriers. BMC Cancer 17, (2017).","DOI":"10.1186\/s12885-017-3422-2"},{"key":"2026052307301078000_2026.05.14.26353261v1.13","doi-asserted-by":"crossref","first-page":"349","DOI":"10.3390\/curroncol32060349","article-title":"Beyond barriers: Achieving true equity in cancer care","volume":"32","year":"2025","journal-title":"Curr. Oncol"},{"key":"2026052307301078000_2026.05.14.26353261v1.14","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pone.0259815"},{"key":"2026052307301078000_2026.05.14.26353261v1.15","first-page":"51","article-title":"Health disparities and cancer: racial disparities in cancer mortality in the United States, 2000-2010","volume":"3","year":"2015","journal-title":"Front. Public Health"},{"key":"2026052307301078000_2026.05.14.26353261v1.16","doi-asserted-by":"crossref","unstructured":"Link, B. G. & Phelan, J . Social conditions as fundamental causes of disease. J. Health Soc. Behav. Spec No, 80\u201394 (1995).","DOI":"10.2307\/2626958"},{"key":"2026052307301078000_2026.05.14.26353261v1.17","doi-asserted-by":"crossref","first-page":"385","DOI":"10.1001\/jamaoncol.2019.5672","article-title":"Association of insurance status and racial disparities with the detection of early-stage breast cancer","volume":"6","year":"2020","journal-title":"JAMA Oncol"},{"key":"2026052307301078000_2026.05.14.26353261v1.18","first-page":"e33425","article-title":"The role of social determinants of health in promoting health equality: A narrative review","volume":"15","year":"2023","journal-title":"Cureus"},{"key":"2026052307301078000_2026.05.14.26353261v1.19","doi-asserted-by":"crossref","first-page":"263","DOI":"10.52403\/ijshr.20240236","article-title":"Role of social determinants in Reshaping the Public Health Policies: A comprehensive study","volume":"9","year":"2024","journal-title":"Int J Sci Healthcare Res"},{"key":"2026052307301078000_2026.05.14.26353261v1.20","doi-asserted-by":"crossref","first-page":"342","DOI":"10.1186\/s12913-025-12494-2","article-title":"Impact of hospital and health system initiatives to address Social Determinants of Health (SDOH) in the United States: a scoping review of the peer-reviewed literature","volume":"25","year":"2025","journal-title":"BMC Health Serv. Res"},{"key":"2026052307301078000_2026.05.14.26353261v1.21","doi-asserted-by":"crossref","first-page":"369","DOI":"10.1038\/s42256-020-0197-y","article-title":"Causal inference and counterfactual prediction in machine learning for actionable healthcare","volume":"2","year":"2020","journal-title":"Nat. Mach. Intell"},{"key":"2026052307301078000_2026.05.14.26353261v1.22","unstructured":"https:\/\/udsmapper.org\/zip-code-to-zcta-crosswalk\/."},{"key":"2026052307301078000_2026.05.14.26353261v1.23","doi-asserted-by":"crossref","first-page":"480","DOI":"10.1093\/aje\/kwae183","article-title":"The health implications of cumulative exposure to contextual (dis)advantage: methodological and substantive advances from a unique data linkage","volume":"194","year":"2025","journal-title":"Am. J. Epidemiol"},{"key":"2026052307301078000_2026.05.14.26353261v1.24","unstructured":"Perkovi\u0107, E. , Textor, J. , Kalisch, M. & Maathuis, M. H . A complete generalized adjustment criterion. arXiv [math.ST] (2015)."},{"key":"2026052307301078000_2026.05.14.26353261v1.25","doi-asserted-by":"crossref","unstructured":"Okello, G. O . Generalized linear models (GLMs). in Statistical Methods Using SPSS 88\u2013126 (Chapman and Hall\/CRC, Boca Raton, 2024).","DOI":"10.1201\/9781003386636-5"},{"key":"2026052307301078000_2026.05.14.26353261v1.26","doi-asserted-by":"publisher","DOI":"10.1023\/A:1010933404324"},{"key":"2026052307301078000_2026.05.14.26353261v1.27","unstructured":"Lundberg, S. & Lee, S.-I . A unified approach to interpreting model predictions. arXiv [cs.AI] (2017)."},{"key":"2026052307301078000_2026.05.14.26353261v1.28","doi-asserted-by":"publisher","DOI":"10.6004\/jnccn.2021.0001"},{"key":"2026052307301078000_2026.05.14.26353261v1.29","doi-asserted-by":"publisher","DOI":"10.1001\/jama.2019.10987"},{"key":"2026052307301078000_2026.05.14.26353261v1.30","doi-asserted-by":"publisher","DOI":"10.1016\/j.ajog.2017.06.038"},{"key":"2026052307301078000_2026.05.14.26353261v1.31","doi-asserted-by":"crossref","first-page":"334","DOI":"10.1016\/S1043-321X(05)80263-2","article-title":"Racial differences in the use of BRCA1\/2 testing among women with a family history of breast or ovarian cancer","volume":"16","year":"2006","journal-title":"Breast Dis. Year B. Q"},{"key":"2026052307301078000_2026.05.14.26353261v1.32","doi-asserted-by":"publisher","DOI":"10.1097\/GIM.0b013e3182091ba4"},{"key":"2026052307301078000_2026.05.14.26353261v1.33","doi-asserted-by":"publisher","DOI":"10.1200\/JCO.2017.73.6314"},{"key":"2026052307301078000_2026.05.14.26353261v1.34","doi-asserted-by":"crossref","unstructured":"Viswalingam, V. & Kumar, D. Disparities in breast cancer incidence, diagnosis, and outcomes: current status and future directions. in Advancements in the Treatment and Prevention of Breast Cancer 227\u2013254 (Elsevier, 2026).","DOI":"10.1016\/B978-0-443-33653-9.00014-4"},{"key":"2026052307301078000_2026.05.14.26353261v1.35","doi-asserted-by":"publisher","DOI":"10.1111\/j.1525-1497.2004.30266.x"},{"key":"2026052307301078000_2026.05.14.26353261v1.36","doi-asserted-by":"publisher","DOI":"10.1097\/01.mlr.0000129906.95881.83"},{"key":"2026052307301078000_2026.05.14.26353261v1.37","doi-asserted-by":"publisher","DOI":"10.3122\/jabfm.2018.03.170419"},{"key":"2026052307301078000_2026.05.14.26353261v1.38","doi-asserted-by":"publisher","DOI":"10.15585\/mmwr.ss6609a1"},{"key":"2026052307301078000_2026.05.14.26353261v1.39","doi-asserted-by":"publisher","DOI":"10.1002\/cncr.24200"},{"key":"2026052307301078000_2026.05.14.26353261v1.40","doi-asserted-by":"publisher","DOI":"10.1080\/09332480.2019.1579578"},{"key":"2026052307301078000_2026.05.14.26353261v1.41","doi-asserted-by":"publisher","DOI":"10.1001\/jama.2020.2436"},{"key":"2026052307301078000_2026.05.14.26353261v1.42","doi-asserted-by":"crossref","first-page":"lsad020","DOI":"10.1093\/jlb\/lsad020","article-title":"Payer reimbursement practices and incentives for improving interpretation of germline genetic testing","volume":"10","year":"2023","journal-title":"J. Law Biosci"},{"key":"2026052307301078000_2026.05.14.26353261v1.43","doi-asserted-by":"crossref","first-page":"165","DOI":"10.1007\/s10549-015-3658-y","article-title":"Rates of BRCA1\/2 mutation testing among young survivors of breast cancer","volume":"155","year":"2016","journal-title":"Breast Cancer Res. Treat"}],"container-title":[],"original-title":[],"link":[{"URL":"https:\/\/syndication.highwire.org\/content\/doi\/10.64898\/2026.05.14.26353261","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,5,23]],"date-time":"2026-05-23T14:30:23Z","timestamp":1779546623000},"score":1,"resource":{"primary":{"URL":"http:\/\/medrxiv.org\/lookup\/doi\/10.64898\/2026.05.14.26353261"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,5,21]]},"references-count":43,"URL":"https:\/\/doi.org\/10.64898\/2026.05.14.26353261","relation":{},"subject":[],"published":{"date-parts":[[2026,5,21]]},"subtype":"preprint"}}