Cargando…
Data mining techniques for detecting signals of adverse drug reaction of cardiac therapy drugs based on Jinan adverse event reporting system database: a retrospective study
OBJECTIVE: Cardiac therapy drugs are widely used in the treatment of heart disease. However, the concern regarding adverse events (AEs) of cardiac therapy drugs have been rising. This study aimed to analyse cardiac therapy drug-related AEs using the Jinan adverse event reporting system (JAERS) datab...
Autores principales: | , , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BMJ Publishing Group
2023
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9872458/ https://www.ncbi.nlm.nih.gov/pubmed/36669842 http://dx.doi.org/10.1136/bmjopen-2022-068127 |
_version_ | 1784877408057294848 |
---|---|
author | Guan, Yuyao Qi, Yingmei Zheng, Lei Yang, Jing Zhang, Mingzhu Zhang, Qiuhong Ji, Lei |
author_facet | Guan, Yuyao Qi, Yingmei Zheng, Lei Yang, Jing Zhang, Mingzhu Zhang, Qiuhong Ji, Lei |
author_sort | Guan, Yuyao |
collection | PubMed |
description | OBJECTIVE: Cardiac therapy drugs are widely used in the treatment of heart disease. However, the concern regarding adverse events (AEs) of cardiac therapy drugs have been rising. This study aimed to analyse cardiac therapy drug-related AEs using the Jinan adverse event reporting system (JAERS) database mining and conduct a comprehensive evaluation to provide safe medication information for patients. DESIGN: Retrospective observational study. SETTING: In this study, cardiac therapy drug-related AEs were detected using the JAERS database from January 2000 to March 2022. METHODS: Reports of cardiac therapy drug-related AEs were extracted from JAERS database, and the basic information of patients, reports and common AEs were analysed. Four disproportionality analysis methods, proportional reporting ratio (PRR), reporting odds ratio (ROR), Bayesian Confidence Propagation Neural Network (BCPNN), Medicines and Healthcare products Regulatory Agency (MHRA), were used to detect cardiac therapy drug-related signals. We further checked whether the detected signals exist on drug labels in China and two developed countries, the USA and Japan. RESULTS: In total, 168 314 AEs were reported, of which 4788 were associated with cardiac therapy drugs. Using the PRR, ROR, MHRA and BCPNN method, we detected 52 signals, 52 signals, 33 signals and 43 signals, respectively. Among the 52 signals, 14 were not included on the drug labels of China. One (isosorbide mononitrate—head bilges) was not included on the drug labels of the three countries. CONCLUSION: We identified 14 new cardiac therapy drug signals that did not appear on drug labels in China and 1 new signal that did not appear on drug labels in 3 counties. A causal link between cardiac therapy drugs and AEs should be evaluated in further studies. |
format | Online Article Text |
id | pubmed-9872458 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | BMJ Publishing Group |
record_format | MEDLINE/PubMed |
spelling | pubmed-98724582023-01-25 Data mining techniques for detecting signals of adverse drug reaction of cardiac therapy drugs based on Jinan adverse event reporting system database: a retrospective study Guan, Yuyao Qi, Yingmei Zheng, Lei Yang, Jing Zhang, Mingzhu Zhang, Qiuhong Ji, Lei BMJ Open Cardiovascular Medicine OBJECTIVE: Cardiac therapy drugs are widely used in the treatment of heart disease. However, the concern regarding adverse events (AEs) of cardiac therapy drugs have been rising. This study aimed to analyse cardiac therapy drug-related AEs using the Jinan adverse event reporting system (JAERS) database mining and conduct a comprehensive evaluation to provide safe medication information for patients. DESIGN: Retrospective observational study. SETTING: In this study, cardiac therapy drug-related AEs were detected using the JAERS database from January 2000 to March 2022. METHODS: Reports of cardiac therapy drug-related AEs were extracted from JAERS database, and the basic information of patients, reports and common AEs were analysed. Four disproportionality analysis methods, proportional reporting ratio (PRR), reporting odds ratio (ROR), Bayesian Confidence Propagation Neural Network (BCPNN), Medicines and Healthcare products Regulatory Agency (MHRA), were used to detect cardiac therapy drug-related signals. We further checked whether the detected signals exist on drug labels in China and two developed countries, the USA and Japan. RESULTS: In total, 168 314 AEs were reported, of which 4788 were associated with cardiac therapy drugs. Using the PRR, ROR, MHRA and BCPNN method, we detected 52 signals, 52 signals, 33 signals and 43 signals, respectively. Among the 52 signals, 14 were not included on the drug labels of China. One (isosorbide mononitrate—head bilges) was not included on the drug labels of the three countries. CONCLUSION: We identified 14 new cardiac therapy drug signals that did not appear on drug labels in China and 1 new signal that did not appear on drug labels in 3 counties. A causal link between cardiac therapy drugs and AEs should be evaluated in further studies. BMJ Publishing Group 2023-01-20 /pmc/articles/PMC9872458/ /pubmed/36669842 http://dx.doi.org/10.1136/bmjopen-2022-068127 Text en © Author(s) (or their employer(s)) 2023. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ. https://creativecommons.org/licenses/by-nc/4.0/This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/ (https://creativecommons.org/licenses/by-nc/4.0/) . |
spellingShingle | Cardiovascular Medicine Guan, Yuyao Qi, Yingmei Zheng, Lei Yang, Jing Zhang, Mingzhu Zhang, Qiuhong Ji, Lei Data mining techniques for detecting signals of adverse drug reaction of cardiac therapy drugs based on Jinan adverse event reporting system database: a retrospective study |
title | Data mining techniques for detecting signals of adverse drug reaction of cardiac therapy drugs based on Jinan adverse event reporting system database: a retrospective study |
title_full | Data mining techniques for detecting signals of adverse drug reaction of cardiac therapy drugs based on Jinan adverse event reporting system database: a retrospective study |
title_fullStr | Data mining techniques for detecting signals of adverse drug reaction of cardiac therapy drugs based on Jinan adverse event reporting system database: a retrospective study |
title_full_unstemmed | Data mining techniques for detecting signals of adverse drug reaction of cardiac therapy drugs based on Jinan adverse event reporting system database: a retrospective study |
title_short | Data mining techniques for detecting signals of adverse drug reaction of cardiac therapy drugs based on Jinan adverse event reporting system database: a retrospective study |
title_sort | data mining techniques for detecting signals of adverse drug reaction of cardiac therapy drugs based on jinan adverse event reporting system database: a retrospective study |
topic | Cardiovascular Medicine |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9872458/ https://www.ncbi.nlm.nih.gov/pubmed/36669842 http://dx.doi.org/10.1136/bmjopen-2022-068127 |
work_keys_str_mv | AT guanyuyao dataminingtechniquesfordetectingsignalsofadversedrugreactionofcardiactherapydrugsbasedonjinanadverseeventreportingsystemdatabasearetrospectivestudy AT qiyingmei dataminingtechniquesfordetectingsignalsofadversedrugreactionofcardiactherapydrugsbasedonjinanadverseeventreportingsystemdatabasearetrospectivestudy AT zhenglei dataminingtechniquesfordetectingsignalsofadversedrugreactionofcardiactherapydrugsbasedonjinanadverseeventreportingsystemdatabasearetrospectivestudy AT yangjing dataminingtechniquesfordetectingsignalsofadversedrugreactionofcardiactherapydrugsbasedonjinanadverseeventreportingsystemdatabasearetrospectivestudy AT zhangmingzhu dataminingtechniquesfordetectingsignalsofadversedrugreactionofcardiactherapydrugsbasedonjinanadverseeventreportingsystemdatabasearetrospectivestudy AT zhangqiuhong dataminingtechniquesfordetectingsignalsofadversedrugreactionofcardiactherapydrugsbasedonjinanadverseeventreportingsystemdatabasearetrospectivestudy AT jilei dataminingtechniquesfordetectingsignalsofadversedrugreactionofcardiactherapydrugsbasedonjinanadverseeventreportingsystemdatabasearetrospectivestudy |