Comparisons of adverse events associated with immune checkpoint inhibitors in the treatment of non-small cell lung cancer: a real-world disproportionality analysis based on the FDA adverse event reporting system
Abstract Background Immune checkpoint inhibitor (ICI) therapy is increasingly used to treat non-small cell lung cancer (NSCLC). However, little attention has been given to the comparative analysis of adverse events (AEs) associated with different ICIs. Methods Disproportionality analysis and Bayesia...
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2025-02-01
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| Series: | BMC Cancer |
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| Online Access: | https://doi.org/10.1186/s12885-025-13614-1 |
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| author | Ruichen Gao Wenjun Liang Jintao Chen Mingxia Yang Xiaowei Yu Xiaohua Wang |
| author_facet | Ruichen Gao Wenjun Liang Jintao Chen Mingxia Yang Xiaowei Yu Xiaohua Wang |
| author_sort | Ruichen Gao |
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| description | Abstract Background Immune checkpoint inhibitor (ICI) therapy is increasingly used to treat non-small cell lung cancer (NSCLC). However, little attention has been given to the comparative analysis of adverse events (AEs) associated with different ICIs. Methods Disproportionality analysis and Bayesian confidence propagation neural network (BCPNN) were utilized to identify pharmacovigilance signals from the FDA Adverse Event Reporting System (FAERS). We compared the sex distribution of patients, risk of suffering more severe adverse reactions, and risk of hospitalization associated with different ICIs, using pairwise matrices that displayed odds ratio (OR) and their 95% confidence interval (CI). And we also compared the outcomes of reactions by using ordinal logistic regression. Results We analyzed 13,580 reports of AEs associated with five ICIs, namely, durvalumab, pembrolizumab, ipilimumab, atezolizumab, and nivolumab from January 2013 to October 2022. Significant differences were observed in sex distribution of patients, risk of suffering more severe adverse reactions, risk of hospitalization, and the outcomes of reactions. In terms of respiratory AEs, pembrolizumab exhibited a higher risk compared to durvalumab (OR = 2.48, 95% CI: 1.72–3.59), atezolizumab (OR = 1.84, 95% CI: 1.07–3.16), and nivolumab (OR = 4.21, 95% CI: 1.72–10.28), while ipilimumab exhibited a higher risk compared to durvalumab (OR = 2.76, 95% CI: 1.14–6.65) and nivolumab (OR = 4.67, 95% CI: 1.14–15.51). In terms of endocrine and metabolic AEs, durvalumab (OR = 7.80, 95% CI: 1.33–45.90) and nivolumab (OR = 5.20, 95% CI: 1.17–23.03) exhibited a higher risk compared to ipilimumab. Conclusion Each ICI has distinctive features of pharmacovigilance signals. It is essential to acknowledge the AEs associated with the relevant system when clinicians administer ICIs. |
| format | Article |
| id | doaj-art-f3d5e9cb57fe46fda40942cc4430279d |
| institution | Kabale University |
| issn | 1471-2407 |
| language | English |
| publishDate | 2025-02-01 |
| publisher | BMC |
| record_format | Article |
| series | BMC Cancer |
| spelling | doaj-art-f3d5e9cb57fe46fda40942cc4430279d2025-02-09T12:41:34ZengBMCBMC Cancer1471-24072025-02-012511910.1186/s12885-025-13614-1Comparisons of adverse events associated with immune checkpoint inhibitors in the treatment of non-small cell lung cancer: a real-world disproportionality analysis based on the FDA adverse event reporting systemRuichen Gao0Wenjun Liang1Jintao Chen2Mingxia Yang3Xiaowei Yu4Xiaohua Wang5Department of Pulmonary and Critical Care Medicine, Affiliated Changzhou Second Hospital of Nanjing Medical UniversityDepartment of Pulmonary and Critical Care Medicine, Affiliated Changzhou Second Hospital of Nanjing Medical UniversityDepartment of Pulmonary and Critical Care Medicine, Affiliated Changzhou Second Hospital of Nanjing Medical UniversityDepartment of Pulmonary and Critical Care Medicine, Affiliated Changzhou Second Hospital of Nanjing Medical UniversityDepartment of Pulmonary and Critical Care Medicine, Affiliated Changzhou Second Hospital of Nanjing Medical UniversityDepartment of Pulmonary and Critical Care Medicine, Affiliated Changzhou Second Hospital of Nanjing Medical UniversityAbstract Background Immune checkpoint inhibitor (ICI) therapy is increasingly used to treat non-small cell lung cancer (NSCLC). However, little attention has been given to the comparative analysis of adverse events (AEs) associated with different ICIs. Methods Disproportionality analysis and Bayesian confidence propagation neural network (BCPNN) were utilized to identify pharmacovigilance signals from the FDA Adverse Event Reporting System (FAERS). We compared the sex distribution of patients, risk of suffering more severe adverse reactions, and risk of hospitalization associated with different ICIs, using pairwise matrices that displayed odds ratio (OR) and their 95% confidence interval (CI). And we also compared the outcomes of reactions by using ordinal logistic regression. Results We analyzed 13,580 reports of AEs associated with five ICIs, namely, durvalumab, pembrolizumab, ipilimumab, atezolizumab, and nivolumab from January 2013 to October 2022. Significant differences were observed in sex distribution of patients, risk of suffering more severe adverse reactions, risk of hospitalization, and the outcomes of reactions. In terms of respiratory AEs, pembrolizumab exhibited a higher risk compared to durvalumab (OR = 2.48, 95% CI: 1.72–3.59), atezolizumab (OR = 1.84, 95% CI: 1.07–3.16), and nivolumab (OR = 4.21, 95% CI: 1.72–10.28), while ipilimumab exhibited a higher risk compared to durvalumab (OR = 2.76, 95% CI: 1.14–6.65) and nivolumab (OR = 4.67, 95% CI: 1.14–15.51). In terms of endocrine and metabolic AEs, durvalumab (OR = 7.80, 95% CI: 1.33–45.90) and nivolumab (OR = 5.20, 95% CI: 1.17–23.03) exhibited a higher risk compared to ipilimumab. Conclusion Each ICI has distinctive features of pharmacovigilance signals. It is essential to acknowledge the AEs associated with the relevant system when clinicians administer ICIs.https://doi.org/10.1186/s12885-025-13614-1FDA adverse event reporting systemNon-small cell lung cancerImmune checkpoint inhibitorImmune-related adverse eventPharmacovigilance signalMatrix of pairwise comparison |
| spellingShingle | Ruichen Gao Wenjun Liang Jintao Chen Mingxia Yang Xiaowei Yu Xiaohua Wang Comparisons of adverse events associated with immune checkpoint inhibitors in the treatment of non-small cell lung cancer: a real-world disproportionality analysis based on the FDA adverse event reporting system BMC Cancer FDA adverse event reporting system Non-small cell lung cancer Immune checkpoint inhibitor Immune-related adverse event Pharmacovigilance signal Matrix of pairwise comparison |
| title | Comparisons of adverse events associated with immune checkpoint inhibitors in the treatment of non-small cell lung cancer: a real-world disproportionality analysis based on the FDA adverse event reporting system |
| title_full | Comparisons of adverse events associated with immune checkpoint inhibitors in the treatment of non-small cell lung cancer: a real-world disproportionality analysis based on the FDA adverse event reporting system |
| title_fullStr | Comparisons of adverse events associated with immune checkpoint inhibitors in the treatment of non-small cell lung cancer: a real-world disproportionality analysis based on the FDA adverse event reporting system |
| title_full_unstemmed | Comparisons of adverse events associated with immune checkpoint inhibitors in the treatment of non-small cell lung cancer: a real-world disproportionality analysis based on the FDA adverse event reporting system |
| title_short | Comparisons of adverse events associated with immune checkpoint inhibitors in the treatment of non-small cell lung cancer: a real-world disproportionality analysis based on the FDA adverse event reporting system |
| title_sort | comparisons of adverse events associated with immune checkpoint inhibitors in the treatment of non small cell lung cancer a real world disproportionality analysis based on the fda adverse event reporting system |
| topic | FDA adverse event reporting system Non-small cell lung cancer Immune checkpoint inhibitor Immune-related adverse event Pharmacovigilance signal Matrix of pairwise comparison |
| url | https://doi.org/10.1186/s12885-025-13614-1 |
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