ArticleDrug safety2016
A Pharmacovigilance Signaling System Based on FDA Regulatory Action and Post-Marketing Adverse Event Reports.
Article in Drug safety, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.
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The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
17 citing papers in PubMed.
- Timing between public safety signals and label strengthening in targeted oncology therapies.European journal of clinical pharmacology · 2026Article
- Real world pharmacovigilance comparison of viloxazine and dextroamphetamine adverse reaction profiles.Scientific reports · 2025Article
- Safety comparisons among different subcutaneous anticoagulants for venous thromboembolism using FDA adverse event reporting system.Scientific reports · 2025Article
- Drug Repurposing Using FDA Adverse Event Reporting System (FAERS) Database.Current drug targets · 2024Review
- Assessing the performance of large language models in literature screening for pharmacovigilance: a comparative study.Frontiers in drug safety and regulation · 2024Article
- Automatic text classification of drug-induced liver injury using document-term matrix and XGBoost.Frontiers in artificial intelligence · 2024Article
- Exploring the impact of design criteria for reference sets on performance evaluation of signal detection algorithms: The case of drug-drug interactions.Pharmacoepidemiology and drug safety · 2023Article
- Potential Adverse Events Reported With the Janus Kinase Inhibitors Approved for the Treatment of Rheumatoid Arthritis Using Spontaneous Reports and Online Patient Reviews.Frontiers in pharmacology · 2021Article
- Article
- BERT-Based Natural Language Processing of Drug Labeling Documents: A Case Study for Classifying Drug-Induced Liver Injury Risk.Frontiers in artificial intelligence · 2021Article
- Assessment of factors associated with completeness of spontaneous adverse event reporting in the United States: A comparison between consumer reports and healthcare professional reports.Journal of clinical pharmacy and therapeutics · 2020Article
- Respiratory concerns of gabapentin and pregabalin: What does it mean to the pharmacovigilance systems in developing countries?F1000Research · 2020Article
- Serious Cardiovascular Adverse Events Reported with Intravenous Sedatives: A Retrospective Analysis of the MedWatch Adverse Event Reporting System.Drugs - real world outcomes · 2019Article
- The "rights" of precision drug development for Alzheimer's disease.Alzheimer's research & therapy · 2019Review
- Crowdsourcing sugammadex adverse event rates using an in-app survey: feasibility assessment from an observational study.Therapeutic advances in drug safety · 2018Article
- Analysis of Spontaneous Postmarket Case Reports Submitted to the FDA Regarding Thromboembolic Adverse Events and JAK Inhibitors.Drug safety · 2018Review
- TwiMed: Twitter and PubMed Comparable Corpus of Drugs, Diseases, Symptoms, and Their Relations.JMIR public health and surveillance · 2017Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
Abstract
introductionMany serious drug adverse events (AEs) only manifest well after regulatory approval. Therefore, the development of signaling methods to use with post-approval AE databases appears vital to comprehensively assess real-world drug safety. However, with millions of potential drug-AE pairs to analyze, the issue of focus is daunting.
objectiveOur objective was to develop a signaling platform that focuses on AEs with historically demonstrated regulatory interest and to analyze such AEs with a disproportional reporting method that offers broad signal detection and acceptable false-positive rates.
methodsWe analyzed over 1500 US FDA regulatory actions (safety communications and drug label changes) from 2008 to 2015 to construct a list of eligible signal AEs. The FDA Adverse Event Reporting System (FAERS) was used to evaluate disproportional reporting rates, constrained by minimum case counts and confidence interval limits, of these selected AEs for 109 training drugs. This step led to 45 AEs that appeared to have a low likelihood of being added to a label by FDA, so they were removed from the signal eligible list. We measured disproportional reporting for the final group of eligible AEs on a test group of 29 drugs that were not used in either the eligible list construction or the training steps.
resultsIn a group of 29 test drugs, our model reduced the number of potential drug-AE signals from 41,834 to 97 and predicted 73 % of individual drug label changes. The model also predicted at least one AE-drug pair label change in 66 % of all the label changes for the test drugs.
conclusionsBy concentrating on AE types with already demonstrated interest to FDA, we constructed a signaling system that provided focus regarding drug-AE pairs and suitable accuracy with regard to the issuance of FDA labeling changes. We suggest that focus on historical regulatory actions may increase the utility of pharmacovigilance signaling systems.
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Registered trials
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.