Risk prediction models for mortality in patients with cardiovascular disease: The BioBank Japan project

• Hata Jun

  Department of Epidemiology and Public Health, Graduate School of Medical Sciences, Kyushu University

• Nagai Akiko

  Department of Public Policy, Institute of Medical Science, The University of Tokyo

• Hirata Makoto

  Laboratory of Genome Technology, Institute of Medical Science, The University of Tokyo

• Kamatani Yoichiro

  Laboratory for Statistical Analysis, RIKEN Center for Integrative Medical Sciences

• Tamakoshi Akiko

  Department of Public Health, Hokkaido University Graduate School of Medicine

• Yamagata Zentaro

  Department of Health Sciences, University of Yamanashi

• Muto Kaori

  Department of Public Policy, Institute of Medical Science, The University of Tokyo

• Matsuda Koichi

  Laboratory of Molecular Medicine, Institute of Medical Science, The University of Tokyo

• Kubo Michiaki

  RIKEN Center for Integrative Medical Sciences

• Nakamura Yusuke

  Laboratory of Molecular Medicine, Institute of Medical Science, The University of Tokyo

• Biobank Japan Cooperative Hospital Group

• Kiyohara Yutaka

  Hisayama Research Institute for Lifestyle Diseases

• Ninomiya Toshiharu

  Department of Epidemiology and Public Health, Graduate School of Medical Sciences, Kyushu University

抄録

Background: Cardiovascular disease (CVD) is a leading cause of death in Japan. The present study aimed to develop new risk prediction models for long-term risks of all-cause and cardiovascular death in patients with chronic phase CVD. Methods: Among the subjects registered in the BioBank Japan database, 15,058 patients aged ≥40 years with chronic ischemic CVD (ischemic stroke or myocardial infarction) were divided randomly into a derivation cohort (n = 10,039) and validation cohort (n = 5019). These subjects were followed up for 8.55 years in median. Risk prediction models for all-cause and cardiovascular death were developed using the derivation cohort by Cox proportional hazards regression. Their prediction performances for 5-year risk of mortality were evaluated in the validation cohort. Results: During the follow-up, all-cause and cardiovascular death events were observed in 2962 and 962 patients from the derivation cohort and 1536 and 481 from the validation cohort, respectively. Risk prediction models for all-cause and cardiovascular death were developed from the derivation cohort using ten traditional cardiovascular risk factors, namely, age, sex, CVD subtype, hypertension, diabetes, total cholesterol, body mass index, current smoking, current drinking, and physical activity. These models demonstrated modest discrimination (c-statistics, 0.703 for all-cause death; 0.685 for cardiovascular death) and good calibration (Hosmer-Lemeshow χ²-test, P = 0.17 and 0.15, respectively) in the validation cohort. Conclusions: We developed and validated risk prediction models of all-cause and cardiovascular death for patients with chronic ischemic CVD. These models would be useful for estimating the long-term risk of mortality in chronic phase CVD.

収録刊行物

• Ｊｏｕｒｎａｌ　ｏｆ　Ｅｐｉｄｅｍｉｏｌｏｇｙ

  Ｊｏｕｒｎａｌ　ｏｆ　Ｅｐｉｄｅｍｉｏｌｏｇｙ 27 (Supplement_III), S71-S76, 2017

  日本疫学会

キーワード

• Risk prediction model
• Ischemic stroke
• Myocardial infarction
• All-cause death
• Cardiovascular death

詳細情報

• CRID: 1390001204476324352
• NII論文ID: 130006832559
• DOI: 10.1016/j.je.2016.10.007
• ISSN: 13499092
• ISSN: 09175040
• Web Site: http://api.elsevier.com/content/article/PII:S0917504016301022?httpAccept=text/xml
• Web Site: http://api.elsevier.com/content/article/PII:S0917504016301022?httpAccept=text/plain
• Web Site: https://search.jamas.or.jp/link/ui/2018049267
• 本文言語コード: en
• データソース種別:
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  • CiNii Articles
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