Comparison of Online Patient Reviews and National Pharmacovigilance Data for Tramadol-Related Adverse Events: Comparative Observational Study
BackgroundTramadol is known to cause fewer adverse events (AEs) than other opioids. However, recent research has raised concerns about various safety issues. ObjectiveWe aimed to explore these new AEs related to tramadol using social media and conventional pharmac...
| Main Authors: | , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
JMIR Publications
2022-01-01
|
| Series: | JMIR Public Health and Surveillance |
| Online Access: | https://publichealth.jmir.org/2022/1/e33311 |
| _version_ | 1827858743531929600 |
|---|---|
| author | Susan Park So Hyun Choi Yun-Kyoung Song Jin-Won Kwon |
| author_facet | Susan Park So Hyun Choi Yun-Kyoung Song Jin-Won Kwon |
| author_sort | Susan Park |
| collection | DOAJ |
| description |
BackgroundTramadol is known to cause fewer adverse events (AEs) than other opioids. However, recent research has raised concerns about various safety issues.
ObjectiveWe aimed to explore these new AEs related to tramadol using social media and conventional pharmacovigilance data.
MethodsThis 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.
ResultsFrom 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.
ConclusionsThis 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. |
| first_indexed | 2024-03-12T12:58:24Z |
| format | Article |
| id | doaj.art-5cdcc91a9501464cbffbdea46cd5058f |
| institution | Directory Open Access Journal |
| issn | 2369-2960 |
| language | English |
| last_indexed | 2024-03-12T12:58:24Z |
| publishDate | 2022-01-01 |
| publisher | JMIR Publications |
| record_format | Article |
| series | JMIR Public Health and Surveillance |
| spelling | doaj.art-5cdcc91a9501464cbffbdea46cd5058f2023-08-28T20:17:38ZengJMIR PublicationsJMIR Public Health and Surveillance2369-29602022-01-0181e3331110.2196/33311Comparison of Online Patient Reviews and National Pharmacovigilance Data for Tramadol-Related Adverse Events: Comparative Observational StudySusan Parkhttps://orcid.org/0000-0002-7082-8554So Hyun Choihttps://orcid.org/0000-0002-1703-9580Yun-Kyoung Songhttps://orcid.org/0000-0003-3687-4052Jin-Won Kwonhttps://orcid.org/0000-0003-3467-7805 BackgroundTramadol is known to cause fewer adverse events (AEs) than other opioids. However, recent research has raised concerns about various safety issues. ObjectiveWe aimed to explore these new AEs related to tramadol using social media and conventional pharmacovigilance data. MethodsThis 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. ResultsFrom 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. ConclusionsThis 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.https://publichealth.jmir.org/2022/1/e33311 |
| spellingShingle | Susan Park So Hyun Choi Yun-Kyoung Song Jin-Won Kwon Comparison of Online Patient Reviews and National Pharmacovigilance Data for Tramadol-Related Adverse Events: Comparative Observational Study JMIR Public Health and Surveillance |
| title | Comparison of Online Patient Reviews and National Pharmacovigilance Data for Tramadol-Related Adverse Events: Comparative Observational Study |
| title_full | Comparison of Online Patient Reviews and National Pharmacovigilance Data for Tramadol-Related Adverse Events: Comparative Observational Study |
| title_fullStr | Comparison of Online Patient Reviews and National Pharmacovigilance Data for Tramadol-Related Adverse Events: Comparative Observational Study |
| title_full_unstemmed | Comparison of Online Patient Reviews and National Pharmacovigilance Data for Tramadol-Related Adverse Events: Comparative Observational Study |
| title_short | Comparison of Online Patient Reviews and National Pharmacovigilance Data for Tramadol-Related Adverse Events: Comparative Observational Study |
| title_sort | comparison of online patient reviews and national pharmacovigilance data for tramadol related adverse events comparative observational study |
| url | https://publichealth.jmir.org/2022/1/e33311 |
| work_keys_str_mv | AT susanpark comparisonofonlinepatientreviewsandnationalpharmacovigilancedatafortramadolrelatedadverseeventscomparativeobservationalstudy AT sohyunchoi comparisonofonlinepatientreviewsandnationalpharmacovigilancedatafortramadolrelatedadverseeventscomparativeobservationalstudy AT yunkyoungsong comparisonofonlinepatientreviewsandnationalpharmacovigilancedatafortramadolrelatedadverseeventscomparativeobservationalstudy AT jinwonkwon comparisonofonlinepatientreviewsandnationalpharmacovigilancedatafortramadolrelatedadverseeventscomparativeobservationalstudy |