ArticleClinical drug investigation2017
Methodological Considerations for Comparison of Brand Versus Generic Versus Authorized Generic Adverse Event Reports in the US Food and Drug Administration Adverse Event Reporting System (FAERS).
Article in Clinical drug investigation, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
What it found
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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.
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
6 citing papers in PubMed, 13 citations in OpenAlex.
- Adverse Events Reported with Standard-Dose and High-Dose Aflibercept: A FAERS Pharmacovigilance Study.Vision (Basel, Switzerland) · 2026Article
- Impact and implications of national centralized drug procurement in China.International journal of clinical pharmacy · 2024Article
- Contrastive analysis on the safety of brand and generic nebivolol: a real-world pharmacovigilance study based on the FDA adverse event reporting system.Frontiers in pharmacology · 2024Article
- Safety of Marketed Cancer Supportive Care Biosimilars in the US: A Disproportionality Analysis Using the Food and Drug Administration Adverse Event Reporting System (FAERS) Database.BioDrugs : clinical immunotherapeutics, biopharmaceuticals and gene therapy · 2021Article
- Detecting and Filtering Immune-Related Adverse Events Signal Based on Text Mining and Observational Health Data Sciences and Informatics Common Data Model: Framework Development Study.JMIR medical informatics · 2020Article
- Adverse event profiles of solvent-based and nanoparticle albumin-bound paclitaxel formulations using the Food and Drug Administration Adverse Event Reporting System.SAGE open medicine · 2019Article
Corrections and comments
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Authors and funding
8 authors at 3 institutions in 1 country.
Funding
Abstract
backgroundThe US Food and Drug Administration Adverse Event Reporting System (FAERS), a post-marketing safety database, can be used to differentiate brand versus generic safety signals.
objectiveTo explore the methods for identifying and analyzing brand versus generic adverse event (AE) reports.
methodsPublic release FAERS data from January 2004 to March 2015 were analyzed using alendronate and carbamazepine as examples. Reports were classified as brand, generic, and authorized generic (AG). Disproportionality analyses compared reporting odds ratios (RORs) of selected known labeled serious adverse events stratifying by brand, generic, and AG. The homogeneity of these RORs was compared using the Breslow-Day test. The AG versus generic was the primary focus since the AG is identical to brand but marketed as a generic, therefore minimizing generic perception bias. Sensitivity analyses explored how methodological approach influenced results.
resultsBased on 17,521 US event reports involving alendronate and 3733 US event reports involving carbamazepine (immediate and extended release), no consistently significant differences were observed across RORs for the AGs versus generics. Similar results were obtained when comparing reporting patterns over all time and just after generic entry. The most restrictive approach for classifying AE reports yielded smaller report counts but similar results.
conclusionDifferentiation of FAERS reports as brand versus generic requires careful attention to risk of product misclassification, but the relative stability of findings across varying assumptions supports the utility of these approaches for potential signal detection.
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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.