ArticleDrug safety2017
An Algorithm to Identify Generic Drugs in the FDA Adverse Event Reporting System.
Article in Drug safety, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed.
- Analysis of Suffix Use for Biosimilar Product Identification in Postmarketing Adverse Event Reporting.Clinical pharmacology and therapeutics · 2026Article
- Impact and implications of national centralized drug procurement in China.International journal of clinical pharmacy · 2024Article
- Comment on: "Mixed Approach Retrospective Analyses of Suicide and Suicidal Ideation for Brand Compared with Generic Central Nervous System Drugs".Drug safety · 2018Article
- Spontaneous Reporting on Adverse Events by Consumers in the United States: An Analysis of the Food and Drug Administration Adverse Event Reporting System Database.Drugs - real world outcomes · 2018Article
- Mixed Approach Retrospective Analyses of Suicide and Suicidal Ideation for Brand Compared with Generic Central Nervous System Drugs.Drug safety · 2018Article
- The Safety of Generic Prescription Drugs in the United States.Drug safety · 2018Article
- 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).Clinical drug investigation · 2017Article
- Patient-relevant outcomes associated with generic tamsulosin, levothyroxine and amphetamine in the FDA Adverse Event Reporting System: a pilot study.Journal of comparative effectiveness research · 2017Article
Corrections and comments
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Authors and funding
4 authors.
Funding
Abstract
introductionAlthough generic drugs constitute approximately 88% of drugs prescribed in the US, there are no reliable methods to identify generic drugs in the US FDA Adverse Event Reporting System (FAERS).
objectiveThe aim of this study was to develop an algorithm for identifying generic drugs in the FAERS. DATA SOURCE: We used 1237 adverse event reports for tamsulosin, levothyroxine, and amphetamine/dextroamphetamine from the publicly available FAERS from 2011-2013, and 277 source case narratives obtained from the FDA.
methodsTwo reviewers independently and in duplicate used a three-item algorithm including the following criteria: manufacturer name, New Drug Application (NDA) number/abbreviated NDA (ANDA), and specific use of the term 'generic' or 'brand' to classify the focal drug of each case report as definitely generic (two of three criteria), probably generic (one of three criteria), brand, and cannot be assessed. Inter-rater reliability was estimated using kappa coefficients, and internal consistency was estimated using Cronbach's alpha. We compared the classification of the drugs as generic versus non-generic in publicly available FAERS compared with the original case reports (reference).
resultsThe focal drug was classified as generic (definite or probable) in 15.8% (39/234), 9% (67/742), and 16.7% (42/261) of tamsulosin, levothyroxine and amphetamine/dextroamphetamine cases, respectively (overall kappa 0.89, 95% confidence interval 0.85-0.93), while 37% of reports could not be classified due to incomplete information. Among the drugs classified as generics using the publicly available FAERS, we categorized 95.3% as generic drugs using the original case reports. Among those drugs that did not meet the algorithm-based definition of generic in the publicly available data, 20.9% were reclassified as generics using the original case reports.
conclusionsThe algorithm demonstrated high inter-rater reliability with moderate internal consistency for identifying generic drugs in the FAERS, in our sample. Future efforts should focus on improving the reliability and validity of identifying generics through improving the completeness of reporting in the FAERS.
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