| アブストラクト | The data-mining statistical methods used for disproportionality analysis of drug-adverse event combinations from large drug safety databases such as the FDA's Adverse Event Reporting System (FAERS), consisting of spontaneous reports on adverse events for postmarket drugs, are called passive surveillance methods. However, the statistical signal detection methods for longitudinal data, as the data accrue in time, are called active surveillance methods. A review of the most commonly used passive surveillance statistical methods and the relationships among them is presented with unified notations. These methods are applied to the 2006-2012 FAERS data; the number of drug signals of disproportionate rates (SDRs) detected by each of these methods with the common SDRs from all of these methods, for the adverse event myocardial infarction, are given. Finally, there is a brief discussion on the recently developed active surveillance methods. |
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| ジャーナル名 | Therapeutic innovation & regulatory science |
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| 投稿日 | 2014/1/1 |
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| 投稿者 | Huang, Lan; Guo, Ted; Zalkikar, Jyoti N; Tiwari, Ram C |
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| 組織名 | 1 Division of Biostatistics V, Office of Biostatistics, Center for Drug;Evaluation and Research, Food and Drug Administration, Silver Spring, MD, USA.;2 Office of Biostatistics, Center for Drug Evaluation and Research, Food and Drug;Administration, Silver Spring, MD, USA. |
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| Pubmed リンク | https://www.ncbi.nlm.nih.gov/pubmed/30231423/ |
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