Department of Health Sciences, University of York, Heslington, York, YO10 5DD, UK.
AbbVie, North Chicago, IL, USA.
Drug Saf. 2019 Mar;42(3):389-400. doi: 10.1007/s40264-018-0731-6.
Adverse effects of medications taken during pregnancy are traditionally studied through post-marketing pregnancy registries, which have limitations. Social media data may be an alternative data source for pregnancy surveillance studies.
The objective of this study was to assess the feasibility of using social media data as an alternative source for pregnancy surveillance for regulatory decision making.
We created an automated method to identify Twitter accounts of pregnant women. We identified 196 pregnant women with a mention of a birth defect in relation to their baby and 196 without a mention of a birth defect in relation to their baby. We extracted information on pregnancy and maternal demographics, medication intake and timing, and birth defects.
Although often incomplete, we extracted data for the majority of the pregnancies. Among women that reported birth defects, 35% reported taking one or more medications during pregnancy compared with 17% of controls. After accounting for age, race, and place of residence, a higher medication intake was observed in women who reported birth defects. The rate of birth defects in the pregnancy cohort was lower (0.44%) compared with the rate in the general population (3%).
Twitter data capture information on medication intake and birth defects; however, the information obtained cannot replace pregnancy registries at this time. Development of improved methods to automatically extract and annotate social media data may increase their value to support regulatory decision making regarding pregnancy outcomes in women using medications during their pregnancies.
传统上,通过上市后妊娠登记处研究药物在怀孕期间的不良影响,但存在局限性。社交媒体数据可能是妊娠监测研究的替代数据源。
本研究旨在评估使用社交媒体数据作为替代妊娠监测源进行监管决策的可行性。
我们创建了一种自动识别孕妇 Twitter 账户的方法。我们确定了 196 名孕妇,她们在提到与婴儿相关的出生缺陷,而另外 196 名孕妇则未提及与婴儿相关的出生缺陷。我们提取了与妊娠和孕产妇人口统计学、药物摄入和时间以及出生缺陷相关的信息。
尽管数据往往不完整,但我们提取了大多数妊娠的数据。在报告出生缺陷的女性中,35%报告在怀孕期间服用了一种或多种药物,而对照组为 17%。在考虑了年龄、种族和居住地后,报告有出生缺陷的女性的药物摄入量更高。妊娠队列中的出生缺陷率(0.44%)低于一般人群(3%)。
Twitter 数据可捕捉药物摄入和出生缺陷的信息;但是,目前,这些信息无法替代妊娠登记处。开发改进的自动提取和注释社交媒体数据的方法可能会增加其价值,以支持关于怀孕期间使用药物的女性妊娠结局的监管决策。