PMID- 35491804
OWN - NLM
STAT- MEDLINE
DCOM- 20230117
LR  - 20230228
IS  - 1878-6847 (Electronic)
IS  - 0924-6479 (Linking)
VI  - 34
IP  - 1
DP  - 2023
TI  - Can Twitter posts serve as early indicators for potential safety signals? A 
      retrospective analysis.
PG  - 41-61
LID - 10.3233/JRS-210024 [doi]
AB  - BACKGROUND: As Twitter has gained significant popularity, tweets can serve as 
      large pool of readily available data to estimate the adverse events (AEs) of 
      medications. OBJECTIVE: This study evaluated whether tweets were an early 
      indicator for potential safety warnings. Additionally, the trend of AEs posted on 
      Twitter was compared with AEs from the Yellow Card system in the United Kingdom. 
      METHODS: English Tweets for 35 drug-event pairs for the period 2017-2019, two 
      years prior to the date of EMA Pharmacovigilance Risk Assessment Committee (PRAC) 
      meeting, were collected. Both signal and non-signal AEs were manually identified 
      and encoded using the MedDRA dictionary. AEs from Yellow Card were also gathered 
      for the same period. Descriptive and inferential statistical analysis was 
      conducted using Fisher's exact test to assess the distribution and proportion of 
      AEs from the two data sources. RESULTS: Of the total 61,661 English tweets, 1,411 
      had negative or neutral sentiment and mention of at least one AE. Tweets for 15 
      out of the 35 drugs (42.9%) contained AEs associated with the signals. On pooling 
      data from Twitter and Yellow Card, 24 out of 35 drug-event pairs (68.6%) were 
      identified prior to the respective PRAC meetings. Both data sources showed 
      similar distribution of AEs based on seriousness, however, the distribution based 
      on labelling was divergent. CONCLUSION: Twitter cannot be used in isolation for 
      signal detection in current pharmacovigilance (PV) systems. However, it can be 
      used in combination with traditional PV systems for early signal detection, as it 
      can provide a holistic drug safety profile.
FAU - Pathak, Revati
AU  - Pathak R
AD  - UC3M Medialab, Department of Communication and Media Studies, University Carlos 
      III of Madrid, Madrid, Spain.
AD  - Eu2P Programme, University of Bordeaux, Bordeaux, France.
FAU - Catalan-Matamoros, Daniel
AU  - Catalan-Matamoros D
AD  - UC3M Medialab, Department of Communication and Media Studies, University Carlos 
      III of Madrid, Madrid, Spain.
AD  - Eu2P Programme, University of Bordeaux, Bordeaux, France.
AD  - Health Research Centre, University of Almeria, Almeria, Spain.
LA  - eng
PT  - Journal Article
PL  - Netherlands
TA  - Int J Risk Saf Med
JT  - The International journal of risk & safety in medicine
JID - 9100907
SB  - IM
MH  - Humans
MH  - Retrospective Studies
MH  - *Social Media
MH  - Pharmacovigilance
MH  - United Kingdom
MH  - Risk Assessment
OTO - NOTNLM
OT  - Safety signal
OT  - Twitter
OT  - adverse events
OT  - pharmacovigilance
OT  - social media
EDAT- 2022/05/03 06:00
MHDA- 2023/01/18 06:00
CRDT- 2022/05/02 04:23
PHST- 2022/05/03 06:00 [pubmed]
PHST- 2023/01/18 06:00 [medline]
PHST- 2022/05/02 04:23 [entrez]
AID - JRS210024 [pii]
AID - 10.3233/JRS-210024 [doi]
PST - ppublish
SO  - Int J Risk Saf Med. 2023;34(1):41-61. doi: 10.3233/JRS-210024.