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Competing risks analysis with misclassified outcome and sensitivity analysis

Research Project

Project/Area Number 18K10073
Research Category

Grant-in-Aid for Scientific Research (C)

Allocation TypeMulti-year Fund
Section一般
Review Section Basic Section 58030:Hygiene and public health-related: excluding laboratory approach
Research InstitutionJichi Medical University

Principal Investigator

Mieno Makiko  自治医科大学, 医学部, 准教授 (60464707)

Co-Investigator(Kenkyū-buntansha) 田中 紀子  国立研究開発法人国立国際医療研究センター, 研究所, ゲノム医科学プロジェクト 特任研究員 (10376460)
新井 富生  地方独立行政法人東京都健康長寿医療センター(東京都健康長寿医療センター研究所), 東京都健康長寿医療センター研究所, 研究員 (20232019)
沢辺 元司  東京医科歯科大学, 大学院医歯学総合研究科, 教授 (30196331)
石川 鎮清  自治医科大学, 医学部, 教授 (70306140)
Project Period (FY) 2018-04-01 – 2024-03-31
Project Status Completed (Fiscal Year 2023)
Budget Amount *help
¥4,290,000 (Direct Cost: ¥3,300,000、Indirect Cost: ¥990,000)
Fiscal Year 2020: ¥1,430,000 (Direct Cost: ¥1,100,000、Indirect Cost: ¥330,000)
Fiscal Year 2019: ¥1,690,000 (Direct Cost: ¥1,300,000、Indirect Cost: ¥390,000)
Fiscal Year 2018: ¥1,170,000 (Direct Cost: ¥900,000、Indirect Cost: ¥270,000)
Keywords誤分類 / アウトカム / 競合リスク / 感度分析 / 死亡診断書 / アウトカム誤分類 / 生存時間解析 / 死因
Outline of Final Research Achievements

In clinical and epidemiological studies, when analyzing the original cause of death on the death certificates, large bias in the estimated risk factors should be found if there is a large misclassification between the recorded causes of death. In this study, we investigated risk estimation methods and sensitivity analysis methods using a method that takes into account the characteristics of misclassification of causes of death. It was suggested that misclassification may have a particularly large impact on the conclusions in large-scale epidemiological studies, and that it is necessary to carefully consider factors that affect the accuracy of outcome classification when estimating risks.

Academic Significance and Societal Importance of the Research Achievements

死亡診断書での死因の誤分類を起こすもっとも強い要因は原死因であり、疾患による違いが大きいこと、高齢者であるほど誤分類率は上昇することが示唆されていたが、死亡診断書の死因データを用いたリスク推定研究において全症例の原資料まで精査することは現実的ではない。我々は測定誤差の問題と考え、感度分析を行って結果を解釈する方法について検討したところ、実際の長期追跡コホートデータ解析からも、アウトカム誤分類の影響に留意して結果を解釈する必要性が示唆された。

Report

(7 results)
  • 2023 Annual Research Report   Final Research Report ( PDF )
  • 2022 Research-status Report
  • 2021 Research-status Report
  • 2020 Research-status Report
  • 2019 Research-status Report
  • 2018 Research-status Report
  • Research Products

    (3 results)

All 2022 2019

All Presentation (3 results) (of which Int'l Joint Research: 2 results)

  • [Presentation] 潜在アウトカムの誤分類が及ぼすオッズ比の推定値への影響2022

    • Author(s)
      田中紀子、三重野牧子
    • Organizer
      第32回日本疫学会学術総会
    • Related Report
      2021 Research-status Report
  • [Presentation] Censored quantile regression model for competing events with long follow-up period2019

    • Author(s)
      Makiko N Mieno, Noriko Tanaka, Motoji Sawabe, Tomio Arai, Shizukiyo Ishikawa
    • Organizer
      40th Annual Conference of the International Society for Clinical Biostatistics
    • Related Report
      2019 Research-status Report
    • Int'l Joint Research
  • [Presentation] Censored quantile regression model for competing events with long follow-up period.2019

    • Author(s)
      Makiko Mieno
    • Organizer
      International Society for Clinical Biostatistics
    • Related Report
      2018 Research-status Report
    • Int'l Joint Research

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Published: 2018-04-23   Modified: 2025-01-30  

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