Center for Technology and Behavioral Health, Geisel School of Medicine, Dartmouth College, Lebanon, NH, United States; Department of Psychiatry, Geisel School of Medicine, Dartmouth College, Hanover, NH, United States; Department of Biomedical Data Science, Geisel School of Medicine, Dartmouth College, Lebanon, NH, United States.
Microsoft Research Israel, Herzeliya, Israel; Faculty of Industrial Engineering and Management, Technion - Israel Institute of Technology, Haifa, Israel.
J Psychiatr Res. 2024 Oct;178:219-224. doi: 10.1016/j.jpsychires.2024.08.001. Epub 2024 Aug 3.
Selective Serotonin Reuptake Inhibitors (SSRIs) represent a diverse class of medications widely prescribed for depression and anxiety. Despite their common use, there is an absence of large-scale, real-world evidence capturing the heterogeneity in their effects on individuals. This study addresses this gap by utilizing naturalistic search data to explore the varied impact of six different SSRIs on user behavior.
The study sample included ∼508 thousand Bing users with searches for one of six SSRIs (citalopram, escitalopram, fluoxetine, fluvoxamine, paroxetine, sertraline) from April-December 2022, comprising 510 million queries. Cox proportional hazard models were employed to examine 30 topics (e.g., shopping, tourism, health) and 195 health symptoms (e.g., anxiety, weight gain, impotence), using each SSRI as a reference. We assessed the relative hazard ratios between drugs and, where feasible, ranked the SSRIs based on their observed effects. We used Cox proportional hazard models in order to account for both the likelihood of users searching for a particular topic or symptom and the associated time to that search. The temporal aspect aided in distinguishing between potential symptoms of the disorder, short-term medication side effects, and later appearing side effects.
Differences were found in search behaviors associated with each SSRI. E.g., fluvoxamine was associated with a significantly higher likelihood of searching weight gain compared to all other SSRIs (HRs 1.85-2.93). Searches following citalopram were associated with significantly higher rates of later impotence queries compared to all other SSRIs (HRs 5.11-7.76), except fluvoxamine. Fluvoxamine was associated with a significantly higher rate of health related searches than all other SSRIs (HRs 2.11-2.36).
Our study reveals new insights into the varying SSRI impacts, suggesting distinct symptom profiles. This novel use of large-scale, naturalistic search data contributes to pharmacovigilance efforts, enhancing our understanding of intra-class variation among SSRIs, potentially uncovering previously unidentified drug effects.
选择性 5-羟色胺再摄取抑制剂（SSRIs）是一类广泛用于治疗抑郁症和焦虑症的药物。尽管它们被广泛使用，但缺乏大规模的真实世界证据来捕捉它们对个体的影响的异质性。本研究利用自然搜索数据来探索六种不同 SSRIs 对用户行为的不同影响，从而填补了这一空白。
研究样本包括约 50.8 万在 2022 年 4 月至 12 月期间使用 Bing 搜索六种 SSRIs（西酞普兰、艾司西酞普兰、氟西汀、氟伏沙明、帕罗西汀、舍曲林）之一的用户，共包含 5.1 亿次查询。使用 Cox 比例风险模型，对 30 个主题（如购物、旅游、健康）和 195 个健康症状（如焦虑、体重增加、阳痿）进行了检查，每个 SSRI 作为参考。我们评估了药物之间的相对危险比，并在可行的情况下，根据观察到的效果对 SSRIs 进行了排序。我们使用 Cox 比例风险模型，以同时考虑用户搜索特定主题或症状的可能性以及与该搜索相关的时间。时间方面有助于区分潜在的疾病症状、短期药物副作用和后来出现的副作用。
发现了与每种 SSRI 相关的搜索行为差异。例如，与所有其他 SSRIs 相比，氟伏沙明与搜索体重增加的可能性显著更高（HRs 1.85-2.93）。与所有其他 SSRIs 相比，西酞普兰的搜索与随后出现的阳痿查询的发生率显著更高（HRs 5.11-7.76），除了氟伏沙明。与所有其他 SSRIs 相比，氟伏沙明与更高的健康相关搜索率相关（HRs 2.11-2.36）。
我们的研究揭示了 SSRIs 影响的新见解，表明了不同的症状特征。这种对大规模自然搜索数据的新颖利用有助于药物警戒工作，增强了我们对 SSRIs 内类变异的理解，有可能发现以前未被识别的药物效应。
