ReviewCardiovascular toxicology2026
Immune Checkpoint Inhibitor-Associated Cardiovascular Toxicity: Mechanisms, Clinical Manifestations, and Clinical Impact.
Review in Cardiovascular toxicology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Authors and funding
5 authors.
Funding
Abstract
Immune checkpoint inhibitors (ICIs) represent a class of novel anticancer agents that enhance T cell-mediated recognition and elimination of tumor cells by inhibiting immune checkpoints such as CTLA-4 and PD-1/PD-L1. These therapeutics are widely employed in the treatment of various malignancies, including melanoma and non-small cell lung cancer, and have markedly improved clinical outcomes. However, ICIs are associated with immune-related adverse events (irAEs). Among these, cardiovascular toxicities, though relatively uncommon (occurring in approximately 3.1% of patients receiving monotherapy and 5.8% on combination therapy), are linked with the highest mortality rates. Cardiovascular toxicities associated with ICIs mainly encompass myocarditis (incidence: 1%-2%; mortality: 39.7%-66.0%), pericarditis (case fatality rate: ~13%), and accelerated atherosclerosis. Risk profiles differ across ICI agents; CTLA-4 inhibitors, for example, demonstrate more pronounced and dose-dependent cardiotoxicity, and combination therapies are associated with higher risks compared to monotherapy. The pathogenic mechanisms are attributed to loss of immune tolerance, which involves excessive activation of T cells, triggering autoimmune responses; cross-reactive T cells targeting shared cardiac antigens; and cytokine release storms that promote systemic inflammation. Although advances have been made in the diagnosis and management of cardiovascular toxicities associated with ICIs, several challenges persist. These include an incomplete understanding of the underlying mechanisms and a lack of reliable predictive biomarkers. Research should prioritize elucidating the pathogenic pathways, refining combination therapy regimens, identifying novel therapeutic targets, and developing artificial intelligence (AI)-based predictive models. Such efforts are crucial in mitigating toxicity, enhancing patients' quality of life, and improving long-term outcomes.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.