Development of the integrated database for IgA nephropathy with standard clinical items
| Project/Area Number |
18K17380
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| Research Category |
Grant-in-Aid for Early-Career Scientists
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| Allocation Type | Multi-year Fund |
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| Review Section |
Basic Section 58030:Hygiene and public health-related: excluding laboratory approach
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| Research Institution | Kitasato University (2022)
Kyoto University (2018-2021) |
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Principal Investigator |
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| Project Period (FY) |
2018-04-01 – 2023-03-31
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| Project Status |
Completed (Fiscal Year 2022)
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| Budget Amount *help |
¥4,030,000 (Direct Cost: ¥3,100,000、Indirect Cost: ¥930,000)
Fiscal Year 2020: ¥1,040,000 (Direct Cost: ¥800,000、Indirect Cost: ¥240,000)
Fiscal Year 2019: ¥1,300,000 (Direct Cost: ¥1,000,000、Indirect Cost: ¥300,000)
Fiscal Year 2018: ¥1,690,000 (Direct Cost: ¥1,300,000、Indirect Cost: ¥390,000)
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| Keywords | IgA腎症 / レジストリー / CDISC SDTM / データベース / システマティックレビュー / 標準化 |
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| Outline of Final Research Achievements |
We developed the integrated database for IgA nephropathy with standard clinical items. Furthermore, we deployed it on the electric data capture (EDC) system on a trial basis. To confirm the robustness and stability, we collated results from database and from statistical software. On the other hand, to use the EDC system for the stable operation of the database was mainly limited by financial constraints. In the future, the database will be developed into a new EDC system based on the findings of this study, and will be planned for use in new cohort studies.
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| Academic Significance and Societal Importance of the Research Achievements |
IgA腎症は本邦における慢性糸球体腎炎のなかで最も多く、慢性の経過を辿ることも少なくないために、日常診療における様々なクリニカルクエスチョンに対応するエビデンスが確立されているとは言い難い。本研究の成果によって、散在するコホート研究の結果をデータ単位で統合することが可能となり、今後診療データ・予後データがデータベース化されることが期待される。これにより、様々なエビデンスの創出がなされ、IgA腎症診療のみならず慢性腎不全診療における一助となり、IgA腎症の早期治療に寄与することが期待される。
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Report
(6 results)
Research Products
(10 results)
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[Journal Article] A Pragmatic Method to Integrate Data from Pre-existing Cohort Studies using the Clinical Data Interchange Standards Consortium (CDISC) Study Data Tabulation Model (SDTM): Practical use of REDCap2SDTM2023
Author(s)
Matsuzaki K, Kitayama M, Yamamoto K, Aida R, Imai T, Ishida M, Katafichi R, Kawamura T, Yokoo T, Narita I, Suzuki Y
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Journal Title
DOI
Related Report
Peer Reviewed / Open Access
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