Skip to main content
Log in

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)

  • Original Research Article
  • Published:
Clinical Drug Investigation Aims and scope Submit manuscript

Abstract

Background

The 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.

Objective

To explore the methods for identifying and analyzing brand versus generic adverse event (AE) reports.

Methods

Public 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.

Results

Based 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.

Conclusion

Differentiation 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.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5

Similar content being viewed by others

References

  1. Generic Pharmaceutical Association (GPhA). 2016 Generic drug savings and access in the United States report. http://www.gphaonline.org/media/generic-drug-savings-2016/index.html. Accessed 28 Nov 2016.

  2. Crawford P, et al. Are there potential problems with generic substitution of antiepileptic drugs? A review of issues. Seizure. 2006;15(3):165–76.

    Article  CAS  Google Scholar 

  3. Del Tacca M, et al. Lack of pharmacokinetic bioequivalence between generic and branded amoxicillin formulations. A post-marketing clinical study on healthy volunteers. Br J Clin Pharmacol. 2009;68(1):34–42.

    Article  Google Scholar 

  4. Colombo GL, et al. Off-patent generic medicines vs. off-patent brand medicines for six reference drugs: a retrospective claims data study from five local healthcare units in the Lombardy Region of Italy. PLoS One. 2013;8(12):e82990.

    Article  Google Scholar 

  5. Erickson SC, et al. Clinical and pharmacy utilization outcomes with brand to generic antiepileptic switches in patients with epilepsy. Epilepsia. 2011;52(7):1365–71.

    Article  Google Scholar 

  6. Kim SH, et al. Efficacy and tolerability of a generic and a branded formulation of atorvastatin 20 mg/d in hypercholesterolemic Korean adults at high risk for cardiovascular disease: a multicenter, prospective, randomized, double-blind, double-dummy clinical trial. Clin Ther. 2010;32(11):1896–905.

    Article  CAS  Google Scholar 

  7. Tsadok MA, et al. Amiodarone-induced thyroid dysfunction: brand-name versus generic formulations. CMAJ. 2011;183(12):E817–23.

    Article  Google Scholar 

  8. Borgheini G. The bioequivalence and therapeutic efficacy of generic versus brand-name psychoactive drugs. Clin Ther. 2003;25(6):1578–92.

    Article  Google Scholar 

  9. Drugs@FDA Glossary of Terms. http://www.fda.gov/Drugs/InformationOnDrugs/ucm079436.htm#ANDA. Accessed 28 Nov 2016.

  10. Faasse K, C T, Gamble G, Petrie KJ. The effect of an apparent change to a branded or generic medication on drug effectiveness and side effects. Psychosom Med. 2013;75:90–6.

    Article  CAS  Google Scholar 

  11. Kesselheim AS, et al. Variations in patients’ perceptions and use of generic drugs: results of a national survey. J Gen Intern Med. 2016;31(6):609–14.

    Article  Google Scholar 

  12. Kesselheim AS, et al. Prevalence and predictors of generic drug skepticism among physicians: results of a national survey. JAMA Intern Med. 2016;176(6):845–7.

    Article  Google Scholar 

  13. US Food and Drug Administration. List of authorized generic drugs. 2014. http://www.fda.gov/drugs/developmentapprovalprocess/howdrugsaredevelopedandapproved/approvalapplications/abbreviatednewdrugapplicationandagenerics/ucm126389.htm. 22 May 2014.

  14. Ahmad SR. Adverse drug event monitoring at the Food and Drug Administration. J Gen Intern Med. 2003;18(1):57–60.

    Article  Google Scholar 

  15. FDA Adverse Event Reporting System (FAERS). https://www.fda.gov/Drugs/GuidanceComplianceRegulatoryInformation/Surveillance/AdverseDrugEffects/default.htm. Accessed 24 Apr 2017.

  16. Sakaeda T, et al. Data mining of the public version of the FDA adverse event reporting system. Int J Med Sci. 2013;10(7):796–803.

    Article  Google Scholar 

  17. Medical Dictionary for Regulatory Activities. Standardised MedDRA Queries. 2015. http://www.meddra.org/standardised-meddra-queries. Cited 3 Jan 2015.

  18. Medical Dictionary for Regulatory Activities. MedDRA hierarchy. 2015. http://www.meddra.org/how-to-use/basics/hierarchy. Cited 3 Jan 2015.

  19. Postmarketing reporting of adverse drug experiences. http://www.accessdata.fda.gov/scripts/cdrh/cfdocs/cfcfr/CFRSearch.cfm?fr=314.80. Accessed 22 Sept 2016.

  20. Request for waiversto postmarketing safety reporting requirements. http://www.fda.gov/BiologicsBloodVaccines/GuidanceComplianceRegulatoryInformation/Guidances/Vaccines/ucm074850.htm#REQUESTSFORWAIVERSTOPOSTMARKETINGSAFETYREPORTINGREQUIREMENTS. Accessed 22 Sept 2016.

  21. Almenoff J, et al. Perspectives on the use of data mining in pharmaco-vigilance. Drug Saf. 2005;28(11):981–1007.

    Article  CAS  Google Scholar 

  22. Egberts AC, Meyboom RH, van Puijenbroek EP. Use of measures of disproportionality in pharmacovigilance: three Dutch examples. Drug Saf. 2002;25(6):453–8.

    Article  Google Scholar 

  23. Rahman MM, et al. Comparison of brand versus generic antiepileptic drug adverse event reporting rates in the US Food and Drug Administration Adverse Event Reporting System (FAERS). Epilepsy Res. 2017;135:71–8.

    Article  CAS  Google Scholar 

  24. Authorized Generics. http://www.authorizedgenerics.com/default.asp?contentID=29. Accessed 19 Sept 2016.

  25. Guidance for Industry. E2E pharmacovigilance planning. https://www.fda.gov/downloads/Drugs/GuidanceComplianceRegulatoryInformation/Guidances/UCM073107.pdf. Accessed 24 Apr 2017.

  26. Iyer G, et al. An algorithm to identify generic drugs in the FDA adverse event reporting system. Drug Saf. 2017. doi:https://doi.org/10.1007/s40264-017-0550-1

    Article  PubMed  Google Scholar 

  27. Drugs@FDA. Lamotrigine. http://www.accessdata.fda.gov/scripts/cder/daf/index.cfm?event=BasicSearch.process. Accessed 01 Dec 2016.

Download references

Acknowledgements

The authors thank Wenlei Jiang, PhD (FDA) and Saranrat Wittayanukorn, PhD (FDA) for their thoughtful contributions to the study design and data analysis.

Funding for this work was made possible by the FDA through grant 1U01FD005272. Views expressed do not necessarily reflect the official policies of the Department of Health and Human Services, nor does any mention of trade names, commercial practices, or organization imply endorsement by the US Government.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Richard A. Hansen.

Ethics declarations

Funding

This study was funded by the US Food and Drug Administration through Grant 1U01FD005272.

Conflict of interest

In the past 3 years, Richard Hansen has provided expert testimony for Boehringer Ingelheim and Daiichi Sankyo. No other authors declare a potential conflict of interest. The sponsor of this study (FDA) has provided suggestions for study design, interpretation of the results and development of the manuscripts. However, the ultimate decisions came from all the authors. Views expressed do not necessarily reflect the official policies of the Department of Health and Human Services; nor does any mention of trade names, commercial practices, or organization imply endorsement by the United States Government.

Electronic supplementary material

Below is the link to the electronic supplementary material.

Supplementary material 1 (DOCX 30 kb)

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Rahman, M.M., Alatawi, Y., Cheng, N. et al. 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). Clin Drug Investig 37, 1143–1152 (2017). https://doi.org/10.1007/s40261-017-0574-4

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s40261-017-0574-4

Navigation