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Frequent discussion of insomnia and weight gain with glucocorticoid therapy: an analysis of Twitter posts

机译:糖皮质激素治疗引起的失眠和体重增加的频繁讨论:Twitter帖子的分析

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摘要

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.
机译:近年来,社交媒体网站被认为是一种新颖的,庞大的数据源,可能对推导药物安全性信息很有用。尽管如此,很少有以这种方式获得的药物安全性概况的公开报道。这项研究的目的是使用计算机系统从Twitter叙述文本中自动检测可疑药物不良反应(ADR)的计算机系统,以检测和量化与糖皮质激素相关的不良事件,并将Twitter内特定ADR提及的频率与频率相比较。向国家药品监管机构报告的自发ADR的类型和模式。在2012年10月1日至2015年6月30日之间提及强的松龙或泼尼松的159,297条推文中,有20,206条推文被视为包含与ADR类似的信息。 AEMedDRA®首选的最高术语是“失眠”和“体重增加”,它们都是公认的非严重但常见的副作用。与英国监管机构的ADR报告计划中的自发报告相比,这些报告在Twitter中的报告比例过高。严重糖皮质激素相关的不良事件报道较少。使用Twitter数据进行药物警戒可能会成为有价值的药物安全信息补充资源。特别是,它可以说明患者最常讨论哪些药物副作用,这可能是由于对生活质量的重要影响。该信息可以帮助临床医生告知患者频繁且相关的非严重副作用以及更严重的副作用。

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