Evidence map›Paper›PMID 28044249›Full record

ArticleDrug safety2017

Evaluation of Facebook and Twitter Monitoring to Detect Safety Signals for Medical Products: An Analysis of Recent FDA Safety Alerts.

Carrie E Pierce, Khaled Bouri, Carol Pamer, Scott Proestel, Harold W Rodriguez, Hoa Van Le, Clark C Freifeld, John S Brownstein, Mark Walderhaug, I Ralph Edwards and 1 more

Abstract read
In one paragraph

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 55 papers.

0numbers the graph read from it
0cells of the map it votes in
55citing papers in PubMed
–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

55 citing papers in PubMed.

  1. Review
  2. Pharmacovigilance in the digital age: gaining insight from social media data.Experimental biology and medicine (Maywood, N.J.) · 2025
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

11 authors.

Carrie E PierceEpidemico, Inc., Boston, MA, USA.
Khaled BouriUS Food and Drug Administration, Silver Spring, MD, USA.
Carol PamerUS Food and Drug Administration, Silver Spring, MD, USA.
Scott ProestelUS Food and Drug Administration, Silver Spring, MD, USA.
Harold W RodriguezEpidemico, Inc., Boston, MA, USA.
Hoa Van LeEpidemico, Inc., Boston, MA, USA.
Clark C FreifeldEpidemico, Inc., Boston, MA, USA.
John S BrownsteinEpidemico, Inc., Boston, MA, USA.
Mark WalderhaugUS Food and Drug Administration, Silver Spring, MD, USA.
I Ralph EdwardsUppsala Monitoring Centre, WHO Collaborating Centre for International Drug Monitoring, Uppsala, Sweden.
Nabarun DasguptaEpidemico, Inc., Boston, MA, USA. nabarun@epidemico.com.ORCID 0000-0002-4098-605X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionThe rapid expansion of the Internet and computing power in recent years has opened up the possibility of using social media for pharmacovigilance. While this general concept has been proposed by many, central questions remain as to whether social media can provide earlier warnings for rare and serious events than traditional signal detection from spontaneous report data.

objectiveOur objective was to examine whether specific product-adverse event pairs were reported via social media before being reported to the US FDA Adverse Event Reporting System (FAERS).

methodsA retrospective analysis of public Facebook and Twitter data was conducted for 10 recent FDA postmarketing safety signals at the drug-event pair level with six negative controls. Social media data corresponding to two years prior to signal detection of each product-event pair were compiled. Automated classifiers were used to identify each 'post with resemblance to an adverse event' (Proto-AE), among English language posts. A custom dictionary was used to translate Internet vernacular into Medical Dictionary for Regulatory Activities (MedDRA

findingsA total of 935,246 posts were harvested from Facebook and Twitter, from March 2009 through October 2014. The automated classifier identified 98,252 Proto-AEs. Of these, 13 posts were selected for causality assessment of product-event pairs. Clinical assessment revealed that posts had sufficient information to warrant further investigation for two possible product-event associations: dronedarone-vasculitis and Banana Boat Sunscreen--skin burns. No product-event associations were found among the negative controls. In one of the positive cases, the first report occurred in social media prior to signal detection from FAERS, whereas the other case occurred first in FAERS.

conclusionsAn efficient semi-automated approach to social media monitoring may provide earlier insights into certain adverse events. More work is needed to elaborate additional uses for social media data in pharmacovigilance and to determine how they can be applied by regulatory agencies.

Indexed as

Adverse Drug Reaction Reporting SystemsSocial MediaDrug-Related Side Effects and Adverse ReactionsHumansPharmacovigilanceRetrospective StudiesUnited StatesUnited States Food and Drug Administration

Identifiers

PMID28044249
PMCPMC5362648

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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.