Immune checkpoint inhibitors-related thyroid dysfunction: influencing factor analysis, prediction model development, and management strategy proposal
Abstract Background With the extensive utilization of immune checkpoint inhibitors (ICIs) across various cancers, ICIs-related thyroid dysfunction (ICI-TD) has become a growing concern in clinical practice. This study aimed to devise an individualized management strategy for ICI-TD to enhance the ea...
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| Format: | Article |
| Language: | English |
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Springer
2024-11-01
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| Series: | Cancer Immunology, Immunotherapy |
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| Online Access: | https://doi.org/10.1007/s00262-024-03816-0 |
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| author | Xinya Li Zaiwei Song Yixuan Chen Jingjing Wu Dan Jiang Zhen Zhang Zeyuan Wang Rongsheng Zhao |
| author_facet | Xinya Li Zaiwei Song Yixuan Chen Jingjing Wu Dan Jiang Zhen Zhang Zeyuan Wang Rongsheng Zhao |
| author_sort | Xinya Li |
| collection | DOAJ |
| description | Abstract Background With the extensive utilization of immune checkpoint inhibitors (ICIs) across various cancers, ICIs-related thyroid dysfunction (ICI-TD) has become a growing concern in clinical practice. This study aimed to devise an individualized management strategy for ICI-TD to enhance the early identification and proactive management in cancer patients. Methods We designed and conducted a three-phase study. Initially, we analyzed the influencing factors through a systematic review and meta-analysis, which adhered to the Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) guidelines. Moreover, the study protocol was registered with PROSPERO (CRD42019131133). Subsequently, prediction models for ICI-TD were developed utilizing 11 algorithms based on the real-world cohort data from July 20, 2018 (the approval date of the first ICIs, Pembrolizumab in China), to October 31, 2022. Considering discrimination, calibration, and clinical utility, we selected the model with the best performance for web calculator development. Finally, individualized management strategies for ICI-TD were proposed by combining evidence-based analysis with practical considerations. Results The systematic review encompassed 21 observational studies involving 4,145 patients, revealing associations between ICI-TD and factors such as female gender, age, receipt of Pembrolizumab (versus other ICIs), and baseline levels of thyroid-stimulating hormone, free thyroxine, and antithyroid antibodies. In the prediction model development phase, 621 participants were enrolled, with 36 patients developing ICI-TD. The model based on the LightGBM algorithm demonstrated superior performance, leading to the development of a web calculator. Based on these findings and existing guidelines, individualized monitoring and treatment pathways for pharmacists were devised. Conclusion This study offers comprehensive insights into managing ICI-TD, potentially enhancing tailored cancer immunotherapy management. |
| format | Article |
| id | doaj-art-4bee2703442546a8b9317d7fd8551598 |
| institution | Kabale University |
| issn | 1432-0851 |
| language | English |
| publishDate | 2024-11-01 |
| publisher | Springer |
| record_format | Article |
| series | Cancer Immunology, Immunotherapy |
| spelling | doaj-art-4bee2703442546a8b9317d7fd85515982025-02-02T12:26:39ZengSpringerCancer Immunology, Immunotherapy1432-08512024-11-0174112010.1007/s00262-024-03816-0Immune checkpoint inhibitors-related thyroid dysfunction: influencing factor analysis, prediction model development, and management strategy proposalXinya Li0Zaiwei Song1Yixuan Chen2Jingjing Wu3Dan Jiang4Zhen Zhang5Zeyuan Wang6Rongsheng Zhao7Department of Pharmacy, Peking University Third HospitalDepartment of Pharmacy, Peking University Third HospitalDepartment of Pharmacy, Peking University Third HospitalDepartment of Pharmacy, Peking University Third HospitalDepartment of Pharmacy, Peking University Third HospitalSentum HealthSentum HealthDepartment of Pharmacy, Peking University Third HospitalAbstract Background With the extensive utilization of immune checkpoint inhibitors (ICIs) across various cancers, ICIs-related thyroid dysfunction (ICI-TD) has become a growing concern in clinical practice. This study aimed to devise an individualized management strategy for ICI-TD to enhance the early identification and proactive management in cancer patients. Methods We designed and conducted a three-phase study. Initially, we analyzed the influencing factors through a systematic review and meta-analysis, which adhered to the Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) guidelines. Moreover, the study protocol was registered with PROSPERO (CRD42019131133). Subsequently, prediction models for ICI-TD were developed utilizing 11 algorithms based on the real-world cohort data from July 20, 2018 (the approval date of the first ICIs, Pembrolizumab in China), to October 31, 2022. Considering discrimination, calibration, and clinical utility, we selected the model with the best performance for web calculator development. Finally, individualized management strategies for ICI-TD were proposed by combining evidence-based analysis with practical considerations. Results The systematic review encompassed 21 observational studies involving 4,145 patients, revealing associations between ICI-TD and factors such as female gender, age, receipt of Pembrolizumab (versus other ICIs), and baseline levels of thyroid-stimulating hormone, free thyroxine, and antithyroid antibodies. In the prediction model development phase, 621 participants were enrolled, with 36 patients developing ICI-TD. The model based on the LightGBM algorithm demonstrated superior performance, leading to the development of a web calculator. Based on these findings and existing guidelines, individualized monitoring and treatment pathways for pharmacists were devised. Conclusion This study offers comprehensive insights into managing ICI-TD, potentially enhancing tailored cancer immunotherapy management.https://doi.org/10.1007/s00262-024-03816-0Immune checkpoint inhibitorsImmune checkpoint inhibitors-related thyroid dysfunctionICI-TDRisk prediction model |
| spellingShingle | Xinya Li Zaiwei Song Yixuan Chen Jingjing Wu Dan Jiang Zhen Zhang Zeyuan Wang Rongsheng Zhao Immune checkpoint inhibitors-related thyroid dysfunction: influencing factor analysis, prediction model development, and management strategy proposal Cancer Immunology, Immunotherapy Immune checkpoint inhibitors Immune checkpoint inhibitors-related thyroid dysfunction ICI-TD Risk prediction model |
| title | Immune checkpoint inhibitors-related thyroid dysfunction: influencing factor analysis, prediction model development, and management strategy proposal |
| title_full | Immune checkpoint inhibitors-related thyroid dysfunction: influencing factor analysis, prediction model development, and management strategy proposal |
| title_fullStr | Immune checkpoint inhibitors-related thyroid dysfunction: influencing factor analysis, prediction model development, and management strategy proposal |
| title_full_unstemmed | Immune checkpoint inhibitors-related thyroid dysfunction: influencing factor analysis, prediction model development, and management strategy proposal |
| title_short | Immune checkpoint inhibitors-related thyroid dysfunction: influencing factor analysis, prediction model development, and management strategy proposal |
| title_sort | immune checkpoint inhibitors related thyroid dysfunction influencing factor analysis prediction model development and management strategy proposal |
| topic | Immune checkpoint inhibitors Immune checkpoint inhibitors-related thyroid dysfunction ICI-TD Risk prediction model |
| url | https://doi.org/10.1007/s00262-024-03816-0 |
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