城西大学機関リポジトリJURAQuantitative Evaluation of Initial Symptoms as Predictors to Detect Adverse Drug Reactions Using Bayes’ Theory: Expansion and Evaluation of Drug-Adverse Drug Reaction?Initial Symptom Combinations Using Adverse Event Reporting System Database

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Quantitative Evaluation of Initial Symptoms as Predictors to Detect Adverse Drug Reactions Using Bayes’ Theory: Expansion and Evaluation of Drug-Adverse Drug Reaction?Initial Symptom Combinations Using Adverse Event Reporting System Database

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ID	JOS-bpb.b12-01006
著者：名前	小林, 大介/保坂, 茂/井上, 絵美子/大島, 公恵/久津間, 信明/大島, 新司/奥野, 恭史
著者：別形式	Kobayashi, Daisuke / Hosaka, Shigeru / Inoue, Emiko / Ohshima, Kimie / Kutsuma, Nobuaki / Oshima, Shinji / Okuno, Yasushi
著者：カナ	コバヤシ, ダイスケ/ホサカ, シゲル/イノウエ, エミコ/オオシマ, キミエ/クツマ, ノブアキ/オオシマ, シンジ/オクノ, ヤスシ
著者：所属	城西大学薬学部薬剤作用解析学講座 / 株式会社あさひ調剤 / 城西大学薬学部薬剤作用解析学講座 / 株式会社あさひ調剤 / 株式会社あさひ調剤 / 城西大学薬学部薬剤作用解析学講座 / 京都大学大学院薬学研究科
著者：所属(別形式）	Josai University, Faculty of Pharmaceutical Sciences, Department of Analytical Pharmaceutics and Informatics / Asahi-Chozai Co., Ltd. / Josai University, Faculty of Pharmaceutical Sciences, Department of Analytical Pharmaceutics and Informatics / Asahi-Chozai Co., Ltd. / Asahi-Chozai Co., Ltd. / Josai University, Faculty of Pharmaceutical Sciences, Department of Analytical Pharmaceutics and Informatics / Kyoto University, Graduate School of Pharmaceutical Sciences, Department of Systems Biosciences for Drug Discovery
著者版フラグ	publisher
出版地	東京
出版者	日本薬学会
出版者：カナ	ニホンヤクガクカイ
出版者：別名	The Pharmaceutical Society of Japan
NCID	AA10885497
冊子ISSN	09186158
電子ISSN	13475215
掲載誌名	Biological and Pharmaceutical Bulletin
巻	36
号	12
刊行年月	2013-12
開始ページ	1891
終了ページ	1901
コンテンツ作成日	2013-09-30
コンテンツ登録日	2014-03-11
識別番号：DOI	info:doi/10.1248/bpb.b12-01006
識別番号：DOI（リンク）	http://dx.doi.org/10.1248/bpb.b12-01006
識別番号：その他	JOI:DN/JST.JSTAGE/bpb/b12-01006
抄録	In prescription dispensing in Japan, to avoid adverse drug reactions (ADR) pharmacists provide patients with information concerning the initial symptoms (IS) of any ADR that might be caused by the drugs they have been prescribed. However, the usefulness of such information for preventing ADR has not been quantitatively evaluated. We previously performed a trial calculation of the usefulness of rash as a predictor of drug-induced liver disorders by applying Bayes’ theorem and showed that the predictive utility of IS can be quantitatively evaluated using likelihood ratios. However, for other drug-ADR-IS combinations it was difficult to obtain the information required for the calculations from Japanese data alone. In this study, using the Adverse Event Reporting System (AERS) database of the U.S. Food and Drug Administration (FDA), we evaluated 132 drug-ADR-IS combinations that were considered to be potentially clinical significant. Regarding bezafibrate-associated rhabdomyolysis and cibenzoline-associated hypoglycemia, these ADR were not detected in cases involving monotherapy. For 58 combinations, no events that were considered to be IS of the target ADR developed. Fever, nausea, and decreased appetite were the IS of many ADR, making them very useful predictors. In contrast, pruritus and rash were not very useful. Fever might be a predictor of thiamazole-induced agranulocytosis or levofloxacin- or terbinafine-induced liver disorder, tremors might be useful for predicting paroxetine-induced serotonin syndrome, and decreased appetite might be a useful indicator of terbinafine-induced liver dysfunction.
キーワード	Bayes’ theory/initial symptom/Adverse Event Reporting System/adverse drug reaction/information service
注記	Regular Articles
言語	eng
資源タイプ	text
ジャンル	01学術雑誌論文 / Journal Article
フォーマット	application/pdf
権利	Copyright c 2013 by the PHARMACEUTICAL SOCIETY OF JAPAN
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このアイテムを表示する：URI	http://libir.josai.ac.jp/il/meta_pub/G0000284repository_JOS-bpb.b12-01006

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