ArticleJMIR public health and surveillance2020
Complementing the US Food and Drug Administration Adverse Event Reporting System With Adverse Drug Reaction Reporting From Social Media: Comparative Analysis.
Article in JMIR public health and surveillance, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 29 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.
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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.
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Who cites it
29 citing papers in PubMed, 50 citations in OpenAlex.
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- Comparative Analysis of Potential Side Effects of Targeted Oral Hypoglycemic Agents Using Spontaneous Adverse Event Reports and Social Media Data.Pharmacoepidemiology and drug safety · 2026Article
- Post-marketing safety surveillance of tarlatamab: a real-world pharmacovigilance study based on the FAERS database.Naunyn-Schmiedeberg's archives of pharmacology · 2026Article
- Detecting Adverse Drug Events in Social Media: A Brief Literature Review.SN computer science · 2026Article
- Pharmacovigilance analysis of iodinated contrast media related respiratory adverse effects based on the FDA adverse event reporting system.Frontiers in pharmacology · 2026Article
- Risk factors for drug-related gastrointestinal ulcer:a retrospective pharmacovigilance study.Frontiers in pharmacology · 2026Article
- Exploring 1400 Plasma Metabolites and Polycystic Ovary Syndrome: A Bidirectional Mendelian Randomization Study.Brain and behavior · 2025Article
- Disproportionality analysis of vibegron-associated adverse events using the FDA adverse event reporting system (FAERS): a real-world pharmacovigilance study.European journal of medical research · 2025Article
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- Analysis of User-Generated Posts on Social Media of Adjuvant Analgesics: A Machine Learning Study.International journal of medical sciences · 2025Article
- A pharmacovigilance study on probiotic preparations based on the FDA Adverse Event Reporting System from 2005 to 2023.Frontiers in cellular and infection microbiology · 2025Article
- Effect and mechanism of resveratrol against polycystic ovary syndrome: a review.Frontiers in endocrinology · 2025Review
- The Value of Social Media Analysis for Adverse Events Detection and Pharmacovigilance: Scoping Review.JMIR public health and surveillance · 2024Article
- Identifying Medicine Shortages With the Twitter Social Network: Retrospective Observational Study.Journal of medical Internet research · 2024Observational
- Examining the Gateway Hypothesis and Mapping Substance Use Pathways on Social Media: Machine Learning Approach.JMIR formative research · 2024Article
- A disproportionality analysis of low molecular weight heparin in the overall population and in pregnancy women using the FDA adverse event reporting system (FAERS) database.Frontiers in pharmacology · 2024Article
- Neratinib safety evaluation: real-world adverse event analysis from the FAERS database.Frontiers in pharmacology · 2024Article
- Which fluoroquinolone is safer when combined with bedaquiline for tuberculosis treatment: evidence from FDA Adverse Event Reporting System database from 2013 to 2024.Frontiers in pharmacology · 2024Article
- Analysis of eplerenone in the FDA adverse event reporting system (FAERS) database: a focus on overall patient population and gender-specific subgroups.Frontiers in pharmacology · 2024Article
Corrections and comments
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Authors and funding
2 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundAdverse drug reactions (ADRs) can occur any time someone uses a medication. ADRs are systematically tracked and cataloged, with varying degrees of success, in order to better understand their etiology and develop methods of prevention. The US Food and Drug Administration (FDA) has developed the FDA Adverse Event Reporting System (FAERS) for this purpose. FAERS collects information from myriad sources, but the primary reporters have traditionally been medical professionals and pharmacovigilance data from manufacturers. Recent studies suggest that information shared publicly on social media platforms related to medication use could be of benefit in complementing FAERS data in order to have a richer picture of how medications are actually being used and the experiences people are having across large populations.
objectiveThe aim of this study is to validate the accuracy and precision of social media methodology and conduct evaluations of Twitter ADR reporting for commonly used pharmaceutical agents.
methodsADR data from the 10 most prescribed medications according to pharmacy claims data were collected from both FAERS and Twitter. In order to obtain data from FAERS, the SafeRx database, a curated collection of FAERS data, was used to collect data from March 1, 2016, to March 31, 2017. Twitter data were manually scraped during the same time period to extract similar data using an algorithm designed to minimize noise and false signals in social media data.
resultsA total of 40,539 FAERS ADR reports were obtained via SafeRx and more than 40,000 tweets containing the drug names were obtained from Twitter's Advanced Search engine. While the FAERS data were specific to ADRs, the Twitter data were more limited. Only hydrocodone/acetaminophen, prednisone, amoxicillin, gabapentin, and metformin had a sufficient volume of ADR content for review and comparison. For metformin, diarrhea was the side effect that resulted in no difference between the two platforms (P=.30). For hydrocodone/acetaminophen, ineffectiveness as an ADR that resulted in no difference (P=.60). For gabapentin, there were no differences in terms of the ADRs ineffectiveness and fatigue (P=.15 and P=.67, respectively). For amoxicillin, hypersensitivity, nausea, and rash shared similar profiles between platforms (P=.35, P=.05, and P=.31, respectively).
conclusionsFAERS and Twitter shared similarities in types of data reported and a few unique items to each data set as well. The use of Twitter as an ADR pharmacovigilance platform should continue to be studied as a unique and complementary source of information rather than a validation tool of existing ADR databases.
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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.