Citation

Zhu XQ, Hu JQ, Deng SH, Tan YQ, Wang ZZ, Lu HY, Ni XJ, Li L, Zhang M, Shang DW, Wen YG. Chinese Journal of New Drugs 2021; 30(1): 87-93.

Copyright

(Copyright © 2021)

DOI

unavailable

PMID

unavailable

Abstract

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. © 2021, Chinese Journal of New Drugs Co. Ltd. All right reserved.

Language: zh

Keywords

human; suicide; drug use; data mining; risk assessment; clozapine; drug overdose; Olanzapine; major clinical study; mental disease; quetiapine; somnolence; haloperidol; olanzapine; risperidone; drug marketing; chlorpromazine; data analysis; ziprasidone; perphenazine; drug interaction; aripiprazole; neuroleptic malignant syndrome; Article; adverse drug reaction; Reporting odds ratio; body weight gain; security; big data; pharmacovigilance; lack of drug effect; Adverse drug events; Big data mining; Disproportionality analysis; FDA adverse events reporting system (FAERS); OpenFDA; Security alert signals