聯合用藥不良反應信號檢測研究進展_West China Medical Journal

Authors：

 唐利 ^1,2 , 王程程 ^1,2 , 彭媛 ^1,2 ,  張志勇 ¹

1. ;
2. ;

Corresponding?author：

張志勇, Email: asg-yong@163.com

Keywords：

聯合用藥; 不良反應; 信號檢測

DOI：

10.7507/1002-0179.20150168

Video：

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臨床聯合用藥目前已廣泛使用，其安全性問題也隨之引起廣泛關注。而聯合用藥不良反應信號檢測方法能快速有效地篩選藥物相互作用信號，對加強合理聯合用藥及安全監測具有重要意義，有利于將有限的醫療資源集中于高度危險的藥物組合。目前已有多種方法被嘗試引入該領域，為給我國聯合用藥不良反應的研究與發展提供參考，現對國內外在藥物安全警戒工作中所運用的聯合用藥不良反應信號檢測方法及其優缺點作一綜述。

Citation： 唐利, 王程程, 彭媛, 張志勇. 聯合用藥不良反應信號檢測研究進展. West China Medical Journal, 2015, 30(3): 585-588. doi: 10.7507/1002-0179.20150168 Copy

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2.	王盼. 基線模型在清開靈注射液與抗生素聯合用藥ADR信號檢測中的應用研究[D]. 北京:北京中醫藥大學, 2012.
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11.	Almenoff JS, DuMouchel W, KindmanLA, et al. Disproportionality analysis using empirical Bayes data mining:a tool for the evaluation of drug interaction in the post-marketing setting[J]. Pharmacoepidemiol Drug Saf, 2003, 12(6):517-521.
12.	Van Puijenbroek EP, Egberts AC, Meyboom RH, et al. Signalling possible drug-drug interactions in a spontaneous reporting system:delay of withdrawal bleeding during concomitant use of oral contraceptives and itraconazole[J]. Br J Clin Pharmacol, 1999, 47(6):689-693.
13.	Wu XT, Barbar? D, Ye Y. Screening and interpreting multi-item associations based on log-linear modeling[C]//ACM SIGKDD International Conference on Knowledge Discovery and Date Mining. Washington, DC:SIGKDD, 2003:276-285.
14.	Thakrar BT, Grundschober SB, Doessegger L. Detecting signals of drug-drug interactions in a spontaneous reports database[J]. Br J Clin Pharmacol, 2007, 64(4):489-495.
15.	Norén GB, Bate A, Johansson K, et al. Duplicate detection in the WHO adverse drug reaction database[DB/OL].[2013-12-03]. http://www.who-umc.org/graphics/9717.pdf.
16.	羅寶章, 錢軼峰, 葉小飛, 等. 聯合用藥不良反應信號檢測的兩種基線模型及應用[J]. 中國衛生統計, 2009, 26(6):586-591.
17.	Bate A, Evans S. Quantitative signal detection using spontaneous ADR reporting[J]. Pharmacoepidemiol Drug Saf, 2009, 18(6):427-436.
18.	Tatonetti NP, Fernald GH, Altman RB. A novel signal detection algorithm for identifying hidden drug-drug interactions in adverse event reports[J]. J Am Med Inform Assoc, 2011, 19(1):79-85.
19.	Tatonetti NP, Denny JC, Murphy SN, et al. Detecting drug interactions from adverse-event reports:interaction between paroxetine and pravastatin increases blood glucose levels[J]. Clin Pharmacol Ther, 2011, 90(1):133-142.
20.	Gooden KM, Pan X, Kawabata H, et al. Use of an algorithm for identifying hidden drug-drug interactions in adverse event reports[J]. J Am Med Inform Assoc, 2013, 20(3):590.
21.	Tatonetti NP, Denny JC, Altman RB. Response to "Use of an algorithm for identifying hidden drug-drug interactions in adverse event reports" by Gooden et al[J]. J Am Med Inform Assoc, 2013, 20(3):591.
22.	Cami A, Manzi S, Arnold A, et al. Pharmacointeraction network models predict unknown drug-drug interactions[J]. PLoS One, 2013, 8(4):1-9.

1. Iyer SV, Harpaz R, Lependu P, et al. Mining clinical text for signals of adverse drug-drug interactions[J]. J Am Inform Assoc, 2014, 21(2):353-362.
2. 王盼. 基線模型在清開靈注射液與抗生素聯合用藥ADR信號檢測中的應用研究[D]. 北京:北京中醫藥大學, 2012.
3. Alsheikh-Ali AA, Abourjaily HM, Karas RH. Risk of adverse events with concomitant use of atorvastatin or simvastatin and glucose-lowering drugs (thiazolidinediones, metformin, sulfonylurea, insulin, and acarbose)[J]. Am J Cardiol, 2002, 89(11):1308-1310.
4. Egberts AC, Meyboom RH, Van Puijenbroek EP. Use of measures of disproportionality in pharmacovigilance:three Dutch examples[J]. Drug Saf, 2002, 25(6):453-458.
5. 江靜, 侯永芳, 劉秀娟, 等. 藥品不良反應信號檢測方法概述[J]. 中國藥物警戒, 2010, 7(2):78-80.
6. 茆詩松. 貝葉斯統計[M]. 北京:中國統計出版社, 1999:1-6.
7. Norén GN, Bate A, Orre R, et al. Extending the methods used to screen the WHO drug safety database towards analysis of complex associations and improved accuracy for rare events[J]. Stat Med, 2006, 25(21):3740-3757.
8. 范道津, 陳偉珂. 風險管理理論與工具[M]. 天津:天津大學出版社, 2010:85-86.
9. Qian Y, Ye X, Du W, et al. A computerized system for detecting signals due to drug-drug interactions in spontaneous reporting systems[J]. Br J Clin Pharmacol, 2010, 69(1):67-73.
10. Choi CA, Chang MJ, Choi HD, et al. Application of a drug-interaction detection method to the Korean National Health Insurance claims database[J]. Regul Toxicol Pharmacol, 2013, 67(2):294-298.
11. Almenoff JS, DuMouchel W, KindmanLA, et al. Disproportionality analysis using empirical Bayes data mining:a tool for the evaluation of drug interaction in the post-marketing setting[J]. Pharmacoepidemiol Drug Saf, 2003, 12(6):517-521.
12. Van Puijenbroek EP, Egberts AC, Meyboom RH, et al. Signalling possible drug-drug interactions in a spontaneous reporting system:delay of withdrawal bleeding during concomitant use of oral contraceptives and itraconazole[J]. Br J Clin Pharmacol, 1999, 47(6):689-693.
13. Wu XT, Barbar? D, Ye Y. Screening and interpreting multi-item associations based on log-linear modeling[C]//ACM SIGKDD International Conference on Knowledge Discovery and Date Mining. Washington, DC:SIGKDD, 2003:276-285.
14. Thakrar BT, Grundschober SB, Doessegger L. Detecting signals of drug-drug interactions in a spontaneous reports database[J]. Br J Clin Pharmacol, 2007, 64(4):489-495.
15. Norén GB, Bate A, Johansson K, et al. Duplicate detection in the WHO adverse drug reaction database[DB/OL].[2013-12-03]. http://www.who-umc.org/graphics/9717.pdf.
16. 羅寶章, 錢軼峰, 葉小飛, 等. 聯合用藥不良反應信號檢測的兩種基線模型及應用[J]. 中國衛生統計, 2009, 26(6):586-591.
17. Bate A, Evans S. Quantitative signal detection using spontaneous ADR reporting[J]. Pharmacoepidemiol Drug Saf, 2009, 18(6):427-436.
18. Tatonetti NP, Fernald GH, Altman RB. A novel signal detection algorithm for identifying hidden drug-drug interactions in adverse event reports[J]. J Am Med Inform Assoc, 2011, 19(1):79-85.
19. Tatonetti NP, Denny JC, Murphy SN, et al. Detecting drug interactions from adverse-event reports:interaction between paroxetine and pravastatin increases blood glucose levels[J]. Clin Pharmacol Ther, 2011, 90(1):133-142.
20. Gooden KM, Pan X, Kawabata H, et al. Use of an algorithm for identifying hidden drug-drug interactions in adverse event reports[J]. J Am Med Inform Assoc, 2013, 20(3):590.
21. Tatonetti NP, Denny JC, Altman RB. Response to "Use of an algorithm for identifying hidden drug-drug interactions in adverse event reports" by Gooden et al[J]. J Am Med Inform Assoc, 2013, 20(3):591.
22. Cami A, Manzi S, Arnold A, et al. Pharmacointeraction network models predict unknown drug-drug interactions[J]. PLoS One, 2013, 8(4):1-9.

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聯合用藥不良反應信號檢測研究進展

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