計量生物学
Online ISSN : 2185-6494
Print ISSN : 0918-4430
ISSN-L : 0918-4430
総説
重要な安全性情報を早期に検出する仕組み
—シグナル検出の最近の手法について—
渡邉 裕之松下 泰之渡辺 篤前田 敏郎温井 一彦小川 嘉正澤 淳悟前田 博
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ジャーナル フリー

2004 年 25 巻 1 号 p. 37-60

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It is very important to provide safety information of new drugs to physicians and patients as soon as possible after the early postmarketing period. For that purpose, it is important to appropriately collect and analyze the spontaneous reports accumulated in databases of companies and regulatory agencies. This paper reviews the analytical methods to assess spontaneous reports. Bate et al. (1998) presented Bayesian Confidence Propagation Neural Network (BCPNN) Method used by Uppsala Monitoring Centre (UMC) of the World Health Organization (WHO). DuMouchel (1999) presented Gamma-Poisson Shrinker (GPS) Program of U. S. Food and Drug Administration (FDA), and Evans et al. (2001) presented Proportional Reporting Ratios (PRR) of the Medicines Control Agency (MCA). Furthermore, DuMouchel and Pregibon (2001) extended the GPS Program, proposing the Multi-Item Gamma Poisson Shrinker (MGPS) Program, which then became the standard method for the FDA. This report also reviews the practical problems (e.g. database, duplication cases, code of Medical Dictionary for Regulatory Activities (MedDRA)) encountered in Japan.

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© 2004 日本計量生物学会
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