Evidence map›Paper›PMID 36198428›Full record

ArticleBMJ (Clinical research ed.)2022

Characterization and corroboration of safety signals identified from the US Food and Drug Administration Adverse Event Reporting System, 2008-19: cross sectional study.

Meera M Dhodapkar, Xiaoting Shi, Reshma Ramachandran, Evan M Chen, Joshua D Wallach, Joseph S Ross

Abstract read
In one paragraph

Article in BMJ (Clinical research ed.), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 45 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
45citing papers in PubMed, 1 pooled it
–field-weighted citation impact
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

45 citing papers in PubMed, 1 synthesis or guideline pooled it.

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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

6 authors.

Meera M DhodapkarYale School of Medicine, Yale University, New Haven, CT, USA.
Xiaoting ShiDepartment of Environmental Health Sciences, Yale School of Public Health, New Haven, CT, USA.
Reshma RamachandranNational Clinician Scholars Program, Department of Internal Medicine, Yale School of Medicine, New Haven, CT, USA.
Evan M ChenDepartment of Ophthalmology, UCSF Medical Center, San Francisco, CA, USA.
Joshua D WallachDepartment of Environmental Health Sciences, Yale School of Public Health, New Haven, CT, USA.
Joseph S RossNational Clinician Scholars Program, Department of Internal Medicine, Yale School of Medicine, New Haven, CT, USA joseph.ross@yale.edu.ORCID 0000-0002-9218-3320

Funding

Yale Clinical and Translational Science Award (U Component)UL1TR001863 · NCATS · YALE UNIVERSITY · PI John H. Krystal, LUCILA OHNO-MACHADO · 2016 to 2026
$102.9M
Identifying Patient Subgroups That Are Most Likely To Benefit From Medications Used To Treat Alcohol Use DisorderK01AA028258 · NIAAA · YALE UNIVERSITY · PI WALLACH, JOSHUA DAVID · 2021 to 2025
$892k
NCATS NIH HHS UL1 TR001863NIAAA NIH HHS K01 AA028258
6 · The paper itself

Abstract

objectiveTo characterize potential drug safety signals identified from the US Food and Drug Administration (FDA) Adverse Event Reporting System (FAERS), from 2008 to 2019, to determine how often these signals resulted in regulatory action by the FDA and whether these actions were corroborated by published research findings or public assessments by the Sentinel Initiative.

designCross sectional study.

settingUSA. POPULATION: Safety signals identified from the FAERS and publicly reported by the FDA between 2008 and 2019; and review of the relevant literature published before and after safety signals were reported in 2014-15. Literature searches were performed in November 2019, Sentinel Initiative assessments were searched in December 2021, and data analysis was finalized in December 2021.

main outcome measuresSafety signals and resulting regulatory actions; number and characteristics of published studies, including corroboration of regulatory action as evidenced by significant associations (or no associations) between the drug related to the signal and the adverse event.

resultsFrom 2008 to 2019, 603 potential safety signals identified from the FAERS were reported by the FDA (median 48 annually, interquartile range 41-61), of which 413 (68.5%) were resolved as of December 2021 (372 of 399 (93.2%) signals ≥3 years old were resolved). Among the resolved safety signals, 91 (22.0%) led to no regulatory action and 322 (78.0%) resulted in regulatory action, including 319 (77.2%) changes to drug labeling and 59 (14.3%) drug safety communications or other public communications from the FDA. For a subset of 82 potential safety signals reported in 2014-15, a literature search identified 1712 relevant publications; 1201 (70.2%) were case reports or case series. Among these 82 safety signals, 76 (92.7%) were resolved, of which relevant published research was identified for 57 (75.0%) signals and relevant Sentinel Initiative assessments for four (5.3%) signals. Regulatory actions by the FDA were corroborated by at least one relevant published research study for 17 of the 57 (29.8%) resolved safety signals; none of the relevant Sentinel Initiative assessments corroborated FDA regulatory action.

conclusionsMost potential safety signals identified from the FAERS led to regulatory action by the FDA. Only a third of regulatory actions were corroborated by published research, however, and none by public assessments from the Sentinel Initiative. These findings suggest that either the FDA is taking regulatory actions based on evidence not made publicly available or more comprehensive safety evaluations might be needed when potential safety signals are identified.

Indexed as

Adverse Drug Reaction Reporting SystemsDrug-Related Side Effects and Adverse ReactionsChild, PreschoolCross-Sectional StudiesDrug LabelingHumansUnited StatesUnited States Food and Drug Administration

Identifiers

PMID36198428
PMCPMC9533298

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Registered trials

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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.