Evidence map›Paper›PMID 28933038›Full record

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).

Md Motiur Rahman, Yasser Alatawi, Ning Cheng, Jingjing Qian, Peggy L Peissig, Richard L Berg, David C Page, Richard A Hansen

Open access · greenAbstract readComparative Study
In one paragraph

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.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
1.0field-weighted citation impact, top 30% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

6 citing papers in PubMed, 13 citations in OpenAlex.

  1. Article
  2. Impact and implications of national centralized drug procurement in China.International journal of clinical pharmacy · 2024
    Article
  3. Article
  4. Article
  5. Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors at 3 institutions in 1 country.

Md Motiur RahmanDepartment of Health Outcomes Research and Policy, Harrison School of Pharmacy, Auburn University, 2316 Walker Building, Auburn, AL, 36849, USA.
Yasser AlatawiDepartment of Health Outcomes Research and Policy, Harrison School of Pharmacy, Auburn University, 2316 Walker Building, Auburn, AL, 36849, USA.
Ning ChengDepartment of Health Outcomes Research and Policy, Harrison School of Pharmacy, Auburn University, 2316 Walker Building, Auburn, AL, 36849, USA.
Jingjing QianDepartment of Health Outcomes Research and Policy, Harrison School of Pharmacy, Auburn University, 2316 Walker Building, Auburn, AL, 36849, USA.
Peggy L PeissigBiomedical Informatics Research Center, Marshfield Clinic Research Foundation, Marshfield, WI, USA.
Richard L BergBiomedical Informatics Research Center, Marshfield Clinic Research Foundation, Marshfield, WI, USA.
David C PageDepartment of Computer Science, Department of Biostatistics and Medical Informatics, School of Medicine and Public Health, University of Wisconsin, Madison, WI, USA.
Richard A HansenDepartment of Health Outcomes Research and Policy, Harrison School of Pharmacy, Auburn University, 2316 Walker Building, Auburn, AL, 36849, USA. rah0019@auburn.edu.
Walker (United States) · USMarshfield Clinic · USUniversity of Wisconsin–Madison · US

Funding

Post-market Authorized Generic Evaluation (PAGE)U01FD005272 · FDA · AUBURN UNIVERSITY AT AUBURN · PI HANSEN, RICHARD A. · 2014 to 2015
$400k
FDA HHS U01 FD005272U.S. Food and Drug Administration 1U01FD005272
6 · The paper itself

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.

Indexed as

Adverse Drug Reaction Reporting SystemsDatabases, FactualDrug-Related Side Effects and Adverse ReactionsDrugs, GenericHumansOdds RatioRetrospective StudiesUnited StatesUnited States Food and Drug AdministrationDrugs, Generic

Identifiers

PMID28933038
PMCPMC5842081
OpenAlexW2755005466

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

Registered trials

None linked

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.