| ID | 69302 |
| FullText URL |
suppl.docx
2.6 MB
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| Author |
Sayer, Michael
School of Pharmacy & Pharmaceutical Sciences, University of California
Hamano, Hirofumi
Department of Pharmacy, Okayama University Hospital
Nagasaka, Misako
Division of Hematology and Oncology, University of California
Lee, Benjamin J.
Department of Pharmacy, University of California Irvine Health
Doh, Jean
Department of Pharmacy, University of California Irvine Health
Patel, Pranav M.
Division of Cardiology, Department of Medicine, University of California
Zamami, Yoshito
Department of Pharmacy, Okayama University Hospital
ORCID
Kaken ID
publons
researchmap
Ozaki, Aya F.
School of Pharmacy & Pharmaceutical Sciences, University of California
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| Abstract | Background: Cardio-inflammatory immune related adverse events (irAEs) while receiving immune checkpoint inhibitor (ICI) therapy are particularly consequential due to their associations with poorer treatment outcomes. Evaluation of predictive factors of these serious irAEs with a time dependent approach allows better understanding of patients most at risk.
Objective: To identify different elements of patient data that are significant predictors of early and late-onset or delayed cardio-inflammatory irAEs through various predictive modeling strategies. Methods: A cohort of patients receiving ICI therapy from January 1, 2010 to May 1, 2022 was identified from TriNetX meeting inclusion/exclusion criteria. Patient data collected included occurrence of early and later cardio-inflammatory irAEs, patient survival time, patient demographic information, ICI therapies, comorbidities, and medication histories. Predictive and statistical modeling approaches identified unique risk factors for early and later developing cardio-inflammatory irAEs. Results: A cohort of 66,068 patients on ICI therapy were identified in the TriNetX platform; 193 (0.30%) experienced early cardio-inflammatory irAEs and 175 (0.26%) experienced later cardio-inflammatory irAEs. Significant predictors for early irAEs included: anti-PD-1 therapy at index, combination ICI therapy at index, and history of peripheral vascular disease. Significant predictors for later irAEs included: a history of myocarditis and/or pericarditis, cerebrovascular disease, and history of non-steroidal anti-inflammatory medication use. Conclusions: Cardio-inflammatory irAEs can be divided into clinically meaningful categories of early and late based on time since initiation of ICI therapy. Considering distinct risk factors for early-onset and late-onset events may allow for more effective patient monitoring and risk assessment. |
| Keywords | Immune checkpoint inhibitors
Immune-Related adverse events
Myocarditis
Pericarditis
Predictive modeling
TriNetx
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| Published Date | 2025-04-28
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| Publication Title |
Cardio-Oncology
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| Volume | volume11
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| Issue | issue1
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| Publisher | Springer Science and Business Media LLC
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| Start Page | 40
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| ISSN | 2057-3804
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| Content Type |
Journal Article
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| language |
English
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| OAI-PMH Set |
岡山大学
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| Copyright Holders | © The Author(s) 2025.
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| File Version | publisher
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| PubMed ID | |
| DOI | |
| Web of Science KeyUT | |
| Related Url | isVersionOf https://doi.org/10.1186/s40959-025-00331-8
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| License | http://creativecommons.org/licenses/by/4.0/
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| Citation | Sayer, M., Hamano, H., Nagasaka, M. et al. Time dependent predictors of cardiac inflammatory adverse events in cancer patients receiving immune checkpoint inhibitors. Cardio-Oncology 11, 40 (2025). https://doi.org/10.1186/s40959-025-00331-8
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