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Epidemiologic studies of antidiabetic drugs and cancer risk: TMLE method, bias analysis and Mendelian randomization

Research Project

Project/Area Number 21K10500
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 InstitutionYokohama City University

Principal Investigator

GOTO Atsushi  横浜市立大学, 医学研究科, 教授 (80644822)

Co-Investigator(Kenkyū-buntansha) 田栗 正隆  東京医科大学, 医学部, 主任教授 (20587589)
岩崎 基  国立研究開発法人国立がん研究センター, がん対策研究所, 部長 (60392338)
Project Period (FY) 2021-04-01 – 2024-03-31
Project Status Completed (Fiscal Year 2023)
Budget Amount *help
¥4,160,000 (Direct Cost: ¥3,200,000、Indirect Cost: ¥960,000)
Fiscal Year 2023: ¥780,000 (Direct Cost: ¥600,000、Indirect Cost: ¥180,000)
Fiscal Year 2022: ¥1,300,000 (Direct Cost: ¥1,000,000、Indirect Cost: ¥300,000)
Fiscal Year 2021: ¥2,080,000 (Direct Cost: ¥1,600,000、Indirect Cost: ¥480,000)
Keywords疫学 / ゲノム / 糖尿病 / メンデルのランダム化 / がん / ゲノム疫学
Outline of Research at the Start

本研究は, レセプト情報・特定健診等情報データベース(NDB)および国内外の大規模ゲノムコホートのデータを用いて,バリデーションで確認されたアウトカム定義を用いて、TMLE,バイアス分析,メンデルのランダム化法をはじめとする画期的な因果推論の方法論を適用することにより,糖尿病治療薬(SGLT2阻害薬とスルホニル尿素薬)とがんリスクに関して総合的に評価し,がん予防に資するエビデンスを提供する.

Outline of Final Research Achievements

To clarify the association between antidiabetic drugs and cancer risk, we comprehensively compared analytical methods using Mendelian randomization. In particular, we compared analytical methods for one sample MR and demonstrated its effectiveness using UK biobank data. This method overcomes the bias issues in conventional methods, allowing for more accurate assessment of the causal relationship between antidiabetic drugs and cancer risk.

Academic Significance and Societal Importance of the Research Achievements

本研究で明らかになった知見は、メンデルランダム化法の適用範囲を広げ、one sample MRにおける因果推論研究に貢献すると考えられる。これにより、治療薬と健康リスクの関連に関するエビデンスの質を高め、薬剤の安全性評価や、個別化医療の実現にもつながることが期待される。メンデルのランダム化法のみならず、操作変数法を適用する際の推定量の選択にも示唆を与えるものであり、今後の活用が期待される。

Report

(4 results)
  • 2023 Annual Research Report   Final Research Report ( PDF )
  • 2022 Research-status Report
  • 2021 Research-status Report
  • Research Products

    (5 results)

All 2025 2024 2023 2022

All Journal Article (4 results) (of which Peer Reviewed: 4 results,  Open Access: 1 results) Presentation (1 results)

  • [Journal Article] Comparison of Instrumental Variable Methods With Continuous Exposure and Binary Outcome: A Simulation Study2025

    • Author(s)
      Orihara S, Goto A
    • Journal Title

      Journal of Epidemiology

      Volume: 35 Issue: 1 Pages: 11-20

    • DOI

      10.2188/jea.JE20230271

    • ISSN
      0917-5040, 1349-9092
    • Year and Date
      2025-01-05
    • Related Report
      2023 Annual Research Report
    • Peer Reviewed / Open Access
  • [Journal Article] Valid instrumental variable selection method using negative control outcomes and constructing efficient estimator2024

    • Author(s)
      Orihara S, Goto A, Taguri M
    • Journal Title

      Biometrical Journal

      Volume: -

    • Related Report
      2023 Annual Research Report
    • Peer Reviewed
  • [Journal Article] Association of Reversal of Renin Suppression With Long-Term Renal Outcome in Medically Treated Primary Aldosteronism2023

    • Author(s)
      Katsuragawa S, Goto A, Shinoda S, Inoue K, Nakai K, Saito J, Nishikawa T, Tsurutani Y
    • Journal Title

      Hypertension

      Volume: 80(9) Issue: 9 Pages: 1909-1920

    • DOI

      10.1161/hypertensionaha.123.21096

    • Related Report
      2023 Annual Research Report
    • Peer Reviewed
  • [Journal Article] Instrumental variable estimation of causal effects with applying some model selection procedures under binary outcomes.2023

    • Author(s)
      Shunichiro Orihara, Atsushi Goto, and Masataka Taguri
    • Journal Title

      Behaviormetrika

      Volume: 50 Issue: 1 Pages: 241-262

    • DOI

      10.1007/s41237-022-00177-9

    • Related Report
      2022 Research-status Report
    • Peer Reviewed
  • [Presentation] Valid Instrumental Variables Selection Methods using Auxiliary Variable and Constructing Efficient Estimator2022

    • Author(s)
      Shunichiro Orihara, Atsushi Goto, and Masataka Taguri
    • Organizer
      The 2022 Annual Meeting of the Biometric Society of Japan
    • Related Report
      2022 Research-status Report

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Published: 2021-04-28   Modified: 2025-01-30  

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