ArticleClinical pharmacology and therapeutics2013
Performance of pharmacovigilance signal-detection algorithms for the FDA adverse event reporting system.
Article in Clinical pharmacology and therapeutics, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 185 papers, 2 of them syntheses that pooled it.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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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
185 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- The quantity, reliability, transparency, reporting, and interpretation of pharmacovigilance signal detection studies in pregnancy: a meta-epidemiological study.European journal of clinical pharmacology · 2025Pooled it
- Antifungal Therapy with Azoles Induced the Syndrome of Acquired Apparent Mineralocorticoid Excess: a Literature and Database Analysis.Antimicrobial agents and chemotherapy · 2022Pooled it
- Analysis of vaccine adverse events associated with rheumatoid arthritis: A pharmacovigilance study based on the VAERS database.Human vaccines & immunotherapeutics · 2026Article
- Timing between public safety signals and label strengthening in targeted oncology therapies.European journal of clinical pharmacology · 2026Article
- Safety Signals of GLP-1 Receptor Agonists: A Multi-Method Pharmacovigilance Analysis of FAERS (2018-2025) With Sensitivity-Stratified Prioritisation, Notoriety-Bias Assessment, and Cross-Database Validation.Diabetes, obesity & metabolism · 2026Article
- Integration of artificial intelligence and multi-omics for precision medicine.Functional & integrative genomics · 2026Review
- Optimising Pharmacovigilance Efficiency with MLIT (Machine Learning for Intelligent Triage): A Tool for Statistical Safety Alerts.Drug safety · 2026Article
- Using Natural Language Processing to Identify Adverse Drug Events Characterized by Medication Replacement in Primary Care Electronic Medical Records: Algorithm and Validation Study.Journal of medical Internet research · 2026Article
- Exploring Risks of Adverse Drug Events From Single Drug to Three-Drug Combination.Clinical and translational science · 2026Article
- Comment on "Comparative safety analysis of enfortumab vedotin and pembrolizumab: monotherapy vs. combination therapy insights from FDA adverse event reporting system data".World journal of urology · 2026Article
- Comparison of a pharmacovigilance screening heuristic with expert clinical consensus for adverse drug reaction signal classification at a Pakistani tertiary care hospital.Pakistan journal of medical sciences · 2026Article
- Safety evaluation of bleomycin in ovarian cancer treatment: A pharmacovigilance analysis using Food and Drug Administration adverse event reporting system data.The Journal of international medical research · 2026Observational
- Psychiatric Safety Signals of GLP-1 Receptor Agonists: A FAERS-Based Pharmacovigilance Study with Explainable Machine Learning.Pharmaceuticals (Basel, Switzerland) · 2026Article
- Predicting Serious Adverse Events, Medication Abuse, Misuse, and Risk of Dependence for Medications with High Dependence Potential: Role of Patient-Reported Factors and Machine Learning Approach.Healthcare (Basel, Switzerland) · 2026Article
- Evaluating COVID-19 Vaccine Masking and Unmasking Methods in Two National Pharmacovigilance Databases.Drug safety · 2026Article
- Posterior Reversible Encephalopathy Syndrome with Angiogenesis Inhibitors for Solid Tumours: Clues from a Disproportionality Analysis of the FDA Adverse Event Reporting System and Pharmacodynamics.Targeted oncology · 2026Article
- Disproportionality Analysis and Timing of Drug-Associated Guillain-Barré Syndrome Onset Based on the Japanese Adverse Drug Event Report Database.Pharmaceuticals (Basel, Switzerland) · 2026Article
- Seizures Risk Related to Atypical Antipsychotics: A Disproportionality Analysis Based on the FDA Adverse Event Reporting System (FAERS).Alpha psychiatry · 2026Article
- Calcitonin gene-related peptide antagonists in Raynaud's phenomenon: a disproportionality study based on real data and drug-gene network analysis.Naunyn-Schmiedeberg's archives of pharmacology · 2026Article
- A systematic safety assessment of zuranolone: real-world adverse event analysis from the FAERS database.Archives of women's mental health · 2026Article
125 more citing papers are in PubMed but not listed here.
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Authors and funding
6 authors.
Funding
Abstract
Signal-detection algorithms (SDAs) are recognized as vital tools in pharmacovigilance. However, their performance characteristics are generally unknown. By leveraging a unique gold standard recently made public by the Observational Medical Outcomes Partnership (OMOP) and by conducting a unique systematic evaluation, we provide new insights into the diagnostic potential and characteristics of SDAs that are routinely applied to the US Food and Drug Administration (FDA) Adverse Event Reporting System (AERS). We find that SDAs can attain reasonable predictive accuracy in signaling adverse events. Two performance classes emerge, indicating that the class of approaches that address confounding and masking effects benefits safety surveillance. Our study shows that not all events are equally detectable, suggesting that specific events might be monitored more effectively using other data sources. We provide performance guidelines for several operating scenarios to inform the trade-off between sensitivity and specificity for specific use cases. We also propose an approach and demonstrate its application in identifying optimal signaling thresholds, given specific misclassification tolerances.
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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.