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Big data mining and analysis of security alert signals of olanzapine
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Xiu-qing ZHU, Jin-qing HU, Shu-hua DENG, Ya-qian TAN, Zhan-zhang WANG, Hao-yang LU, Xiao-jia NI, Lu LI, Ming ZHANG, De-wei SHANG, Yu-guan WEN
Chinese Journal of New Drugs | 2021, 30(1) : 87 - 93
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Chinese Journal of New Drugs | 2021, 30(1): 87-93
Big data mining and analysis of security alert signals of olanzapine
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Xiu-qing ZHU, Jin-qing HU, Shu-hua DENG, Ya-qian TAN, Zhan-zhang WANG, Hao-yang LU, Xiao-jia NI, Lu LI, Ming ZHANG, De-wei SHANG, Yu-guan WEN
Affiliations
  • Department of Pharmacy, The Affiliated Brain Hospital of Guangzhou Medical University/Guangzhou Huiai Hospital; Guangdong Engineering Technology Research Center for Translational Medicine of Mental Disorders, Guangzhou 510370, China
Published: 2021-01-15
Outline
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Objective:

To analyze the security alert signals of olanzapine after marketing by big data mining, and to provide references for rational clinical drug use.

Methods:

The adverse drug events (ADE) of olanzapine since Jan, 2014 were retrieved based on the U.S. Food and Drug Administration (FDA) Adverse Event Reporting System (FAERS) database utilizing the Open Public Data project of FDA (openFDA). The signals were detected by reporting odds ratio (ROR), and the lower bound of 95% confidence interval (ROR 95% CILower bound) >1 was regarded as the suggestion of security alert signals. The disproportionality analysis results of alert signals for olanzapine vs. other antipsychotic drugs (including quetiapine, clozapine, risperidone, perphenazine, aripiprazole, ziprasidone, chlorpromazine, perphenazine, and haloperidol) were compared, and the highest relative reporting ratio (RRR) indicated the drug were the most probably related with the alert signal.

Results:

A total of 11 171 211 reports were retrieved, among which there were 27 705 ADE reports that were suspected to be caused by olanzapine. The number of reports and signals referring to psychiatric disorders were the highest. The ADE signals that were above 1 000 cases included toxicity to various agents, drug ineffective, drug interaction, weight increased, somnolence, completed suicide, overdose, and neuroleptic malignant syndrome (NMS). Among the top 100 ADE signals, a total of 83 security alert signals were detected by ROR, among which sixteen alert signals were not mentioned in the latest label of olanzapine, and the NMS showed the highest risk (ROR 95% CILower bound=58.227). The risk relevance of chlorpromazine (RRR=75.271) and haloperidol (RRR=66.164) in the case of NMS were both greater than that of olanzapine (RRR=52.375).

Conclusion:

It can effectively provide reference for future pharmacovigilance work to detect and analyze the security alert signals of olanzapine using openFDA platform.

openFDA  /  FDA adverse events reporting system (FAERS)  /  olanzapine  /  adverse drug events  /  security alert signals  /  reporting odds ratio  /  disproportionality analysis  /  big data mining
朱秀清, 胡晋卿, 邓书华, 谭亚倩, 王占璋, 卢浩扬, 倪晓佳, 李璐, 张明, 尚德为, 温预关. 奥氮平安全警戒信号的大数据挖掘与分析. 中国新药杂志, 2021 , 30 (1) : 87 -93 .
Xiu-qing ZHU, Jin-qing HU, Shu-hua DENG, Ya-qian TAN, Zhan-zhang WANG, Hao-yang LU, Xiao-jia NI, Lu LI, Ming ZHANG, De-wei SHANG, Yu-guan WEN. Big data mining and analysis of security alert signals of olanzapine[J]. Chinese Journal of New Drugs, 2021 , 30 (1) : 87 -93 .
Year 2021 volume 30 Issue 1
31
9
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  • Online Date:2026-10-29
  • Published:2021-01-15
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  • Accepted:2020-03-24
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    Department of Pharmacy, The Affiliated Brain Hospital of Guangzhou Medical University/Guangzhou Huiai Hospital; Guangdong Engineering Technology Research Center for Translational Medicine of Mental Disorders, Guangzhou 510370, China
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小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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