ArticleEuropean journal of clinical pharmacology2020
Borrowing external information to improve Bayesian confidence propagation neural network.
Article in European journal of clinical pharmacology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers, 1 of them a synthesis that pooled it.
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Who cites it
21 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Romosozumab adverse event profile: a pharmacovigilance analysis based on the FDA Adverse Event Reporting System (FAERS) from 2019 to 2023.Aging clinical and experimental research · 2025Pooled it
- Drug-induced fever: a pharmacovigilance analysis based on the FDA adverse event reporting system.International journal of clinical pharmacy · 2026Article
- Article
- A systematic safety assessment of zuranolone: real-world adverse event analysis from the FAERS database.Archives of women's mental health · 2026Article
- Adverse events associated with targeted therapy and immunotherapy for ovarian cancer: a FAERS pharmacovigilance study.Frontiers in pharmacology · 2026Article
- Drug-associated postpartum hemorrhage: a comprehensive disproportionality analysis based on the FAERS database.Naunyn-Schmiedeberg's archives of pharmacology · 2026Article
- Drug-induced gingival overgrowth: FAERS based real-world pharmacovigilance study and network pharmacology analysis.Frontiers in pharmacology · 2026Article
- Heart failure reporting signals associated with concomitant mavacamten and CYP inhibitors in obstructive hypertrophic cardiomyopathy: a real-world pharmacovigilance study with propensity score matching.Frontiers in pharmacology · 2026Article
- Immune checkpoint inhibitor-associated myocarditis and pericarditis: a pharmacovigilance study based on the FAERS database.BMC cancer · 2025Article
- A real-world pharmacovigilance study of Certolizumab pegol based on FAERS database.Scientific reports · 2025Article
- Characteristics of Adverse Events and Clinical Risks of Omaveloxolone Based on FAERS Data.Cerebellum (London, England) · 2025Article
- A realworld pharmacovigilance study of trazodone based on the FDA adverse event reporting system.Scientific reports · 2025Article
- Real-world pharmacovigilance analysis unveils the toxicity profile of amivantamab targeting EGFR exon 20 insertion mutations in non-small cell lung cancer.BMC pulmonary medicine · 2025Article
- Analysis of ADR reports of cetuximab based on the FDA adverse event reporting system database.Scientific reports · 2025Article
- Adverse drug reaction assessment of pembrolizumab in cervical cancer treatment: a real-world pharmacovigilance study using the FAERS database.Frontiers in immunology · 2025Article
- Post-marketing safety of anakinra and canakinumab: a real-world pharmacovigilance study based on FDA adverse event reporting system.Frontiers in pharmacology · 2025Article
- Adverse drug events associated with tiotropium: a real-world pharmacovigilance study of FDA adverse event reporting system database.Journal of pharmacy & pharmaceutical sciences : a publication of the Canadian Society for Pharmaceutical Sciences, Societe canadienne des sciences pharmaceutiques · 2025Article
- Characteristics of adverse events and clinical risks of intravenous immunoglobulin: a pharmacovigilance study based on FDA Adverse Event Reporting System (FAERS).Frontiers in medicine · 2025Article
- Prostaglandin analogues signal detection by data mining in the FDA Adverse Event Reporting System database.BMJ open ophthalmology · 2024Article
- Gastrointestinal perforation associated with novel antineoplastic agents: A real-world study based on the FDA Adverse Event Reporting System.Journal of pharmacy & pharmaceutical sciences : a publication of the Canadian Society for Pharmaceutical Sciences, Societe canadienne des sciences pharmaceutiques · 2023Article
Corrections and comments
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
purposeA Bayesian confidence propagation neural network (BCPNN) is a signal detection method used by the World Health Organization Uppsala Monitoring Centre to analyze spontaneous reporting system databases. We modify the BCPNN to increase its sensitivity for detecting potential adverse drug reactions (ADRs).
methodIn a BCPNN, the information component (IC) is defined as an index of disproportionality between the observed and expected number of reported drugs and events. Our proposed method adjusts the IC value by borrowing information about events that have occurred in drugs defined as similar to the target drug. We compare the performance of our method with that of a traditional BCPNN through a simulation study.
resultsThe false positive rate of the proposed method was lower than that of the traditional BCPNN method and close to the nominal value, 0.025, around the true difference in ICs between the target drug and similar drugs equal to 0. The sensitivity of the proposed method was much higher than that of the traditional BCPNN method in case in which the difference in ICs between the target drug and similar drugs ranges from 0 to 2. When applied to a database managed by Japanese regulatory authority, the proposed method could detect known ADRs earlier than the traditional method.
conclusionsThe proposed method is a novel criterion for early detection of signals if similar drugs have the same tendencies. The proposed BCPNN tends to have higher sensitivity when the true difference is greater than 0.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.