4.7 Article

Comparison of Online Patient Reviews and National Pharmacovigilance Data for Tramadol-Related Adverse Events: Comparative Observational Study

期刊

出版社

JMIR PUBLICATIONS, INC
DOI: 10.2196/33311

关键词

drug safety; pharmacovigilance; tramadol; social media; adverse effect

资金

  1. BK21 FOUR (Community-Based Intelligent Novel Drug Discovery Education Unit at Kyungpook National University)
  2. Basic Science Research Program through the National Research Foundation of Korea (NRF) - Ministry of Education [2021R1I1A1A01059268]
  3. National Research Foundation of Korea [2021R1I1A1A01059268] Funding Source: Korea Institute of Science & Technology Information (KISTI), National Science & Technology Information Service (NTIS)

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This study explored new adverse events (AEs) related to tramadol use using both social media and conventional pharmacovigilance data. The results identified several novel AEs associated with tramadol use, some of which were not listed on the drug label. Vascular disorders and tramadol-induced pain were found to be potentially serious AEs.
Background: Tramadol is known to cause fewer adverse events (AEs) than other opioids. However, recent research has raised concerns about various safety issues. Objective: We aimed to explore these new AEs related to tramadol using social media and conventional pharmacovigilance data. Methods: This study used 2 data sets, 1 from patients' drug reviews on WebMD (January 2007 to January 2021) and 1 from the US Food and Drug Administration (FDA) Adverse Event Reporting System (FAERS; January 2016 to December 2020). We analyzed 2062 and 29,350 patient reports from WebMD and FAERS, respectively. Patient posts on WebMD were manually assigned the preferred terms of the Medical Dictionary for Regulatory Activities. To analyze AEs from FAERS, a disproportionality analysis was performed with 3 measures: proportional reporting ratio, reporting odds ratio, and information component. Results: From the 869 AEs reported, we identified 125 new signals related to tramadol use not listed on the drug label that satisfied all 3 signal detection criteria. In addition, 20 serious AEs were selected from new signals. Among new serious AEs, vascular disorders had the largest signal detection criteria value. Based on the disproportionality analysis and patients' symptom descriptions, tramadol-induced pain might also be an unexpected AE. Conclusions: This study detected several novel signals related to tramadol use, suggesting newly identified possible AEs. Additionally, this study indicates that unexpected AEs can be detected using social media analysis alongside traditional pharmacovigilance data.

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