{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,31]],"date-time":"2026-08-31T02:15:22Z","timestamp":1788142522836,"version":"build-2803163510"},"reference-count":30,"publisher":"Oxford University Press (OUP)","license":[{"start":{"date-parts":[[2026,8,31]],"date-time":"2026-08-31T00:00:00Z","timestamp":1788134400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"NIHR HealthTech Research Centre in Emergency and Acute Care","award":["NIHR205301"],"award-info":[{"award-number":["NIHR205301"]}]},{"name":"Manchester British Heart Foundation (BHF) Centre for Research Excellence","award":["RE\/24\/130017"],"award-info":[{"award-number":["RE\/24\/130017"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Background and Aims<\/jats:title>\n                    <jats:p>Advances in cancer care have improved survival, increasing the importance of comorbidities at diagnosis for longer-term outcomes. Pre-existing cardiovascular disease (CVD) can complicate management and prognosis, yet its long-term trends and future burden at cancer diagnosis are unclear. This study aimed to quantify temporal trends in pre-existing CVD among patients with newly diagnosed cancer and project prevalence through 2050.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>Linked primary care, cancer registry, and hospitalization records were used to identify 773 590 adults (\u226518 years) diagnosed with the five most common cancers between 2001 and 2020 in England. Serial cross-sectional analyses estimated annual crude and age\u2013standardized prevalence of pre-existing CVD and comorbidities. Temporal trends were assessed using logistic regression adjusted for demographics and cancer type. The contributions of changes in risk factor domains were evaluated using sequential modelling, and CVD prevalence was projected to 2050 using demographic-adjusted spline models.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>The age-standardized prevalence of pre-existing CVD rose from 31.4% [95% confidence interval (CI) 31.2\u201331.6] in 2001\u20132005 to 39.2% (95% CI 39.0\u201339.4) in 2016\u20132020, with the steepest increases in lung and haematological cancers. Valvular disease, heart failure, atrial fibrillation, and diabetes showed the largest subtype rises. Sequential modelling showed the greatest attenuation of the temporal trend after adjustment for cardiometabolic conditions and chronic comorbidities. Projection analyses suggest that, if current temporal patterns continue, approximately half of patients may present with pre-existing CVD at cancer diagnosis by 2050.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>Pre-existing CVD at cancer diagnosis has increased substantially over 2 decades and is projected to affect nearly half of patients by 2050. These trends underscore the need for the expansion of cardio-oncology services.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1093\/eurheartj\/ehag626","type":"journal-article","created":{"date-parts":[[2026,7,29]],"date-time":"2026-07-29T11:13:57Z","timestamp":1785323637000},"source":"Crossref","is-referenced-by-count":0,"title":["Cardiovascular disease burden at cancer diagnosis: temporal trends in a national study from England"],"prefix":"10.1093","author":[{"ORCID":"https:\/\/orcid.org\/0009-0005-2268-5658","authenticated-orcid":false,"given":"Ali A","family":"Alshahrani","sequence":"first","affiliation":[{"name":"Division of Informatics, Imaging and Data Science, School of Health Sciences, Faculty of Biology, Medicine and Health, University of Manchester , Manchester M13 9PL ,","place":["UK"]},{"name":"Department of Invasive Cardiovascular Technology, College of Applied Medical Sciences, King Saud bin Abdulaziz University for Health Sciences , Riyadh 11481, Kingdom of Saudi 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