2021 Fiscal Year Final Research Report
Development and application of statistical methods for small clinical trials
| Project/Area Number |
18K11187
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| Research Category |
Grant-in-Aid for Scientific Research (C)
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| Allocation Type | Multi-year Fund |
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| Section | 一般 |
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| Review Section |
Basic Section 60030:Statistical science-related
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| Research Institution | University of Tsukuba |
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Principal Investigator |
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| Project Period (FY) |
2018-04-01 – 2022-03-31
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| Keywords | 小標本バイアス / スパースデータバイアス / ロバスト分散 / データ欠測 / シグナル検出 |
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| Outline of Final Research Achievements |
The purpose of this study is to develop and apply statistical methods to small clinical trials and databases with a small number of events, for which it is difficult to accumulate sufficient data. During the four-year study period, we proposed statistical methods to correct for bias and test size caused by small samples and rare events. We also studied on statistical analysis for detecting signals with small number of events in adverse drug report databases. We published 19 papers in peer-reviewed international journals based on our study results.
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| Free Research Field |
生物統計学
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| Academic Significance and Societal Importance of the Research Achievements |
治療法が確立されていない希少疾患や小児分野の臨床試験では，必要十分な数の被験者の集積が極めて難しいため，試験規模は必然的に小さくなる．本研究では，データが十分に集積できない状況の中で，より正確で効率的な統計手法を開発し，実データに応用することでその実用性を確認した．本研究で挙げた成果は，データ集積が困難な臨床試験や臨床研究並びに医学系データベース研究全般に適用可能であるため，統計科学にとどまらず，医学の発展に大きく寄与するものである．
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