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- Preciosa M Coloma, Benedikt Becker, Miriam C J M Sturkenboom, Erik M van Mulligen, and Jan A Kors.
- Department of Medical Informatics, Erasmus University Medical Center, PO Box 2040, 3000 CA, Rotterdam, The Netherlands. p.coloma@erasmusmc.nl.
- Drug Saf. 2015 Oct 1; 38 (10): 921-30.
IntroductionThere is growing interest in whether social media can capture patient-generated information relevant for medicines safety surveillance that cannot be found in traditional sources.ObjectiveThe aim of this study was to evaluate the potential contribution of mining social media networks for medicines safety surveillance using the following associations as case studies: (1) rosiglitazone and cardiovascular events (i.e. stroke and myocardial infarction); and (2) human papilloma virus (HPV) vaccine and infertility.MethodsWe collected publicly accessible, English-language posts on Facebook, Google+, and Twitter until September 2014. Data were queried for co-occurrence of keywords related to the drug/vaccine and event of interest within a post. Messages were analysed with respect to geographical distribution, context, linking to other web content, and author's assertion regarding the supposed association.ResultsA total of 2537 posts related to rosiglitazone/cardiovascular events and 2236 posts related to HPV vaccine/infertility were retrieved, with the majority of posts representing data from Twitter (98 and 85%, respectively) and originating from users in the US. Approximately 21% of rosiglitazone-related posts and 84% of HPV vaccine-related posts referenced other web pages, mostly news items, law firms' websites, or blogs. Assertion analysis predominantly showed affirmation of the association of rosiglitazone/cardiovascular events (72%; n = 1821) and of HPV vaccine/infertility (79%; n = 1758). Only ten posts described personal accounts of rosiglitazone/cardiovascular adverse event experiences, and nine posts described HPV vaccine problems related to infertility.ConclusionsPublicly available data from the considered social media networks were sparse and largely untrackable for the purpose of providing early clues of safety concerns regarding the prespecified case studies. Further research investigating other case studies and exploring other social media platforms are necessary to further characterise the usefulness of social media for safety surveillance.
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