| ID | JOS-ijms.76139 |
| 著者：名前 | |
| 著者：別形式 | Negishi, Akio / Oshima, Shinji / Mutoh, Mizue / Horii, Norimitsu / Inoue, Naoko / Numajiri, Sachihiko / Ohshima,Shigeru / Kobayashi, Daisuke |
| 著者：カナ | |
| 著者：所属 | 城西大学薬学部薬学科薬剤作用解析学研究室 / 城西大学薬学部薬学科薬剤作用解析学研究室 / 城西大学薬学部薬学科薬局管理学研究室 / 城西大学薬学部薬学科薬局管理学研究室 / 城西大学薬学部薬学科薬局管理学研究室 / 城西大学薬学部薬学科教育支援室 / 城西大学薬学部薬学科薬局管理学研究室 / 城西大学薬学部薬学科薬剤作用解析学研究室 |
| 著者：所属(別形式） | Josai University, Faculty of Pharmacy and Pharmaceutical Sciences, Laboratory of Analytical Pharmaceutics and Informatics / Josai University, Faculty of Pharmacy and Pharmaceutical Sciences, Laboratory of Analytical Pharmaceutics and Informatics / Josai University, Faculty of Pharmacy and Pharmaceutical Sciences, Laboratory of Pharmacy Management / Josai University, Faculty of Pharmacy and Pharmaceutical Sciences, Laboratory of Pharmacy Management / Josai University, Faculty of Pharmacy and Pharmaceutical Sciences, Laboratory of Pharmacy Management / Josai University, Faculty of Pharmacy and Pharmaceutical Sciences, Student Learning Assistance Center / Josai University, Faculty of Pharmacy and Pharmaceutical Sciences, Laboratory of Pharmacy Management / Josai University, Faculty of Pharmacy and Pharmaceutical Sciences, Laboratory of Analytical Pharmaceutics and Informatics |
| 著者版フラグ | publisher |
| 出版地 | Sydney |
| 出版者 | Ivyspring International Publisher |
| 電子ISSN | 14491907 |
| 掲載誌名 | |
| 巻 | 19 |
| 号 | 12 |
| 刊行年月 | 2022-10 |
| 開始ページ | 1816 |
| 終了ページ | 1823 |
| コンテンツ作成日 | 2022-06-14 |
| コンテンツ修正日 | 2022-09-13 |
| コンテンツ登録日 | 2022-12-24 |
| 識別番号：DOI | info:doi/10.7150/ijms.76139 |
| 識別番号：DOI（リンク） | |
| PubMed番号 | 36313225 |
| 抄録 | Adverse drug events due to drug-drug interactions can be prevented by avoiding concomitant use of causative drugs; therefore, it is important to understand drug combinations that cause drug-drug interactions. Although many attempts to identify drug-drug interactions from real-world databases such as spontaneous reporting systems have been performed, little is known about drug-drug interactions caused by three or more drugs in polypharmacy, i.e., multiple drug-drug interactions. Therefore, we attempted to detect multiple drug-drug interactions using decision tree analysis using the Japanese Adverse Drug Event Report (JADER) database, a Japanese spontaneous reporting system. First, we used decision tree analysis to detect drug combinations that increase the risk of rhabdomyolysis in cases registered in the JADER database that used six statins. Next, the risk of three or more drug combinations that significantly increased the risk of rhabdomyolysis was validated with in vivo experiments in rats. The analysis identified a multiple drug-drug interaction signal only for pitavastatin. The reporting rate of rhabdomyolysis for pitavastatin in the JADER database was 0.09, and it increased to 0.16 in combination with allopurinol. Furthermore, the rate was even higher (0.40) in combination with valsartan. Additionally, necrosis of leg muscles was observed in some rats simultaneously treated with these three drugs, and their creatine kinase and myoglobin levels were elevated. The combination of pitavastatin, allopurinol, and valsartan should be treated with caution as a multiple drug-drug interaction. Since multiple drug-drug interactions were detected with decision tree analysis and the increased risk was verified in animal experiments, decision tree analysis is considered to be an effective method for detecting multiple drug-drug interactions. |
| キーワード | |
| 注記 | This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/). See http://ivyspring.com/terms for full terms and conditions. |
| 言語 | eng |
| 資源タイプ | text |
| ジャンル | |
| フォーマット | application/pdf |
| 権利 | Copyright © The author(s). |
| このアイテムを表示する：本文(pdf) | |
| このアイテムを表示する：URI | |
