Abstract

In recent years, social media websites have been suggested as a novel, vast source of data which may be useful for deriving drug safety information. Despite this, there are few published reports of drug safety profiles derived in this way. The aims of this study were to detect and quantify glucocorticoid-related adverse events using a computerised system for automated detection of suspected adverse drug reactions (ADR) from narrative text in Twitter, and to compare the frequency of specific ADR mentions within Twitter to the frequency and patterns of spontaneous ADR reporting to a national drug regulatory body. Of 159,297 tweets mentioning either prednisolone or prednisone between 1st October 2012 and 30th June 2015, 20,206 tweets were deemed to contain information resembling an ADR. The top AE MedDRA® Preferred Terms were ‘insomnia’ and ‘weight increased’, both recognised non-serious but common side effects. These were proportionally over-reported in Twitter when compared to spontaneous reports in the UK regulator’s ADR reporting scheme. Serious glucocorticoid related AEs were reported less frequently. Pharmacovigilance using Twitter data has the potential to be a valuable, supplementary source of drug safety information. In particular, it can illustrate which drug side effects patients discuss most commonly, potentially because of important impacts on quality of life. This information could help clinicians to inform patients about frequent and relevant non-serious side effects as well as more serious side effects.

Social media: Twitter posts track common side effects of steroid therapy

Patients on steroid drugs often complain of insomnia and weight gain on Twitter, offering a window into commonly experienced side effects. William Dixon from the University of Manchester, UK, and colleagues searched for mentions of either prednisolone or prednisone on Twitter between October 2012 and June 2015. They documented around 20,000 tweets on the social media platform that contained discussion of an adverse drug reaction. The top side effects cited were “insomnia” and “weight increased”, both of which constituted a larger proportion of total steroid-related complaints on Twitter than in the official UK regulator’s reporting scheme. Serious side effects were mentioned less frequently on Twitter. The findings show the power of social media data to identify the side effects impacting quality of life among patients.

Details

Title
Frequent discussion of insomnia and weight gain with glucocorticoid therapy: an analysis of Twitter posts
Author
Patel Rikesh 1   VIAFID ORCID Logo  ; Belousov Maksim 2   VIAFID ORCID Logo  ; Jani Meghna 3 ; Dasgupta Nabarun 4   VIAFID ORCID Logo  ; Winokur Carly 4 ; Nenadic Goran 5 ; Dixon, William G 6 

 University of Manchester, Arthritis Research UK Centre for Epidemiology, Manchester, UK (GRID:grid.5379.8) (ISNI:0000000121662407) 
 University of Manchester, School of Computer Science, Manchester, UK (GRID:grid.5379.8) (ISNI:0000000121662407) 
 University of Manchester, Arthritis Research UK Centre for Epidemiology, Manchester, UK (GRID:grid.5379.8) (ISNI:0000000121662407); Central Manchester University Hospitals NHS Foundation Trust, NIHR Manchester Musculoskeletal Biomedical Research Unit, Manchester, UK (GRID:grid.411037.0) (ISNI:0000 0004 0430 9101) 
 Epidemico Inc., Boston, USA (GRID:grid.411037.0) 
 University of Manchester, School of Computer Science, Manchester, UK (GRID:grid.5379.8) (ISNI:0000000121662407); Health eResearch Centre, Manchester, UK (GRID:grid.5379.8) 
 University of Manchester, Arthritis Research UK Centre for Epidemiology, Manchester, UK (GRID:grid.5379.8) (ISNI:0000000121662407); Central Manchester University Hospitals NHS Foundation Trust, NIHR Manchester Musculoskeletal Biomedical Research Unit, Manchester, UK (GRID:grid.411037.0) (ISNI:0000 0004 0430 9101); Health eResearch Centre, Manchester, UK (GRID:grid.411037.0); Salford Royal NHS Foundation Trust, Rheumatology Department, Salford, UK (GRID:grid.412346.6) (ISNI:0000 0001 0237 2025) 
Publication year
2018
Publication date
Dec 2018
Publisher
Nature Publishing Group
e-ISSN
23986352
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
2531380414
Copyright
© The Author(s) 2018. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.