Bibliographic Details
| Title: |
Signal mining of adverse events of proteasome inhibitors in multiple myeloma based on FAERS |
| Authors: |
Yuan Peng, Yuying Zhou, Kaisen Shu, Xu Jia, Yan Zhong |
| Source: |
Frontiers in Pharmacology, Vol 15 (2024) |
| Publisher Information: |
Frontiers Media S.A., 2024. |
| Publication Year: |
2024 |
| Collection: |
LCC:Therapeutics. Pharmacology |
| Subject Terms: |
proteasome inhibitors, adverse event, signal mining, multiple myeloma, adverse event reporting system, Therapeutics. Pharmacology, RM1-950 |
| More Details: |
ObjectiveTo mine and analyze adverse events (AEs) related to proteasome inhibitors in multiple myeloma based on the FDA Adverse Event Reporting System (FAERS), providing references for rational clinical medication.MethodsAE data related to multiple myeloma proteasome inhibitors were collected from the FAERS from the first quarter of 2010 to the first quarter of 2024. Signal mining of AEs was conducted using the reporting odds ratio method and Bayesian confidence propagation neural network method.ResultsA total of 8,805 reports for bortezomib, 5,264 for carfilzomib, and 8,771 for ixazomib were collected, with corresponding AE signals of 474, 279, and 287, respectively, involving 23, 21, and 22 System Organ Classes (SOCs). The report information for the three drugs tended to be consistent: more cases were reported in males than in females; the majority of patients were 65 years and over; AEs mostly occurred within 6 months of medication; the outcomes primarily consisted of hospitalization, prolonged hospital stay, and other serious adverse events; the primary reporting country was the United States. The most affected SOCs were infections and infestations, general disorders and administration site conditions, and blood and lymphatic system disorders.ConclusionThe overall distribution of AEs for the three multiple myeloma proteasome inhibitors was consistent, but there were certain differences in specific AE signal characteristics, which should be noted in clinical applications. |
| Document Type: |
article |
| File Description: |
electronic resource |
| Language: |
English |
| ISSN: |
1663-9812 |
| Relation: |
https://www.frontiersin.org/articles/10.3389/fphar.2024.1396378/full; https://doaj.org/toc/1663-9812 |
| DOI: |
10.3389/fphar.2024.1396378 |
| Access URL: |
https://doaj.org/article/cf895cfe321341278426dd8ed678ccee |
| Accession Number: |
edsdoj.f895cfe321341278426dd8ed678ccee |
| Database: |
Directory of Open Access Journals |
