| アブストラクト | AIMS: To compare the predictive performance of CHA(2)DS(2)-VASc and HAS-BLED scores in atrial fibrillation (AF) patients with and without cancer. METHODS AND RESULTS: Using data from the Clinical Practice Research Datalink in England, we performed a retrospective cohort study of patients with new diagnoses of AF from 2009 to 2019. Cancer was defined as history of breast, prostate, colorectal, lung, or haematological cancer. We calculated the CHA(2)DS(2)-VASc and HAS-BLED scores for the 1-year risk of stroke and major bleeding events. Scores performance was estimated by discrimination [area under the receiver operating characteristic curve (AUC)] and calibration plots. Of 141 796 patients with AF, 10.3% had cancer. The CHA(2)DS(2)-VASc score had good to modest discrimination in prostate cancer AUC = 0.74 (95% confidence interval: 0.71, 0.77), haematological cancer AUC = 0.71 (0.66, 0.76), colorectal cancer AUC = 0.70 (0.66, 0.75), breast cancer AUC = 0.70 (0.66, 0.74), and lung cancer AUC = 0.69 (0.60, 0.79), compared with no-cancer AUC = 0.73 (0.72, 0.74). HAS-BLED discrimination was poor in prostate cancer AUC = 0.58 (0.55, 0.61), haematological cancer AUC = 0.59 (0.55, 0.64), colorectal cancer AUC = 0.57 (0.53, 0.61), breast cancer AUC = 0.56 (0.52, 0.61), and lung cancer AUC = 0.59 (0.51, 0.67), compared with no-cancer AUC = 0.61 (0.60, 0.62). Both the CHA(2)DS(2)-VASc score and HAS-BLED score were well calibrated across all study cohorts. CONCLUSION: Amongst certain cancer cohorts in the AF population, CHA(2)DS(2)-VASc performs similarly in predicting stroke to AF patients without cancer. Our findings highlight the importance of cancer diagnosis during the development of risk scores and opportunities to optimize the HAS-BLED risk score to better serve cancer patients with AF. |
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| ジャーナル名 | European heart journal open |
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| 投稿日 | 2024/7/11 |
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| 投稿者 | Ajabnoor, Alyaa M; Zghebi, Salwa S; Parisi, Rosa; Ashcroft, Darren M; Faivre-Finn, Corinne; Mamas, Mamas A; Kontopantelis, Evangelos |
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| 組織名 | Department of Pharmacy Practice, Faculty of Pharmacy, King Abdulaziz University,;P.O. Box 80324, Jeddah 21589, Saudi Arabia.;Division of Informatics, Imaging and Data Sciences, School of Health Sciences,;Faculty of Biology, Medicine and Health, Manchester Academic Health Science;Centre (MAHSC), University of Manchester, Manchester M13 9PL, UK.;Division of Population Health, Health Services Research and Primary Care, School;of Health Sciences, Faculty of Biology, Medicine and Health, Manchester Academic;Health Science Centre (MAHSC), University of Manchester, Manchester M13 9PL, UK.;Division of Pharmacy and Optometry, Centre for Pharmacoepidemiology and Drug;Safety, School of Health Sciences, Faculty of Biology, Medicine and Health,;University of Manchester, Manchester M13 9PL, UK.;National Institute for Health and Care Research (NIHR) Greater Manchester Patient;Safety Research Collaboration (PSRC), University of Manchester, Manchester M13;9PL, UK.;The Christie NHS Foundation Trust and The University of Manchester, Manchester,;UK.;Keele Cardiovascular Research Group, Centre for Prognosis Research, Institute for;Primary Care and Health Sciences, Keele University, Keele, UK.;National Institute for Health and Care Research (NIHR) Birmingham Biomedical;Research Center, UK. |
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| Pubmed リンク | https://www.ncbi.nlm.nih.gov/pubmed/38988675/ |
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