{"title":"Can Twitter posts serve as early indicators for potential safety signals? A retrospective analysis.","authors":"Revati Pathak, Daniel Catalan-Matamoros","doi":"10.3233/JRS-210024","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>As Twitter has gained significant popularity, tweets can serve as large pool of readily available data to estimate the adverse events (AEs) of medications.</p><p><strong>Objective: </strong>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.</p><p><strong>Methods: </strong>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.</p><p><strong>Results: </strong>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.</p><p><strong>Conclusion: </strong>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.</p>","PeriodicalId":45237,"journal":{"name":"INTERNATIONAL JOURNAL OF RISK & SAFETY IN MEDICINE","volume":"34 1","pages":"41-61"},"PeriodicalIF":0.9000,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"INTERNATIONAL JOURNAL OF RISK & SAFETY IN MEDICINE","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.3233/JRS-210024","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH","Score":null,"Total":0}
引用次数: 1
Abstract
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.
期刊介绍:
The International Journal of Risk and Safety in Medicine is concerned with rendering the practice of medicine as safe as it can be; that involves promoting the highest possible quality of care, but also examining how those risks which are inevitable can be contained and managed. This is not exclusively a drugs journal. Recently it was decided to include in the subtitle of the journal three items to better indicate the scope of the journal, i.e. patient safety, pharmacovigilance and liability and the Editorial Board was adjusted accordingly. For each of these sections an Associate Editor was invited. We especially want to emphasize patient safety.