著者

藤田 利治

出版者

一般社団法人 日本薬剤疫学会

雑誌

薬剤疫学 (ISSN:13420445)

巻号頁・発行日

vol.14, no.1, pp.27-36, 2009 (Released:2009-09-30)

参考文献数

11

被引用文献数

23 22

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During the post-approval period, hypotheses about potentially new adverse drug reactions (ADR) have traditionally emerged from passive surveillance systems that collect large volumes of spontaneous case reports of suspected adverse drug reactions. With signal detection by traditional (or conventional, or manual) methods, quantitative (or statistical, or automated) methods for spontaneous reporting system (SRS) databases were introduced in the late 1990’s in order to detect serious ADR as early as possible. Most quantitative methods rely on comparisons of relative reporting frequencies, also known as disproportionality analyses. In FY 2009, the Pharmaceuticals and Medical Device Agency (PMDA) plans to introduce the quantitative methods (data mining method) used on Japanese SRS database. This paper introduces the recent situation on signal detection and signal management of adverse drug reactions.