Potential therapies for immune-related adverse events associated with immune checkpoint inhibition: from monoclonal antibodies to kinase inhibition
Bibliographic record
Abstract
The therapeutic benefits of immune checkpoint inhibitors (ICIs), which enable antitumor immune responses, can be tempered by unwanted immune-related adverse events (irAEs). Treatment recommendations stratified by irAE phenotype and immunohistopathological findings have only recently been proposed and are often based on those used in primary autoimmune diseases, including targeting of specific proinflammatory cytokines with monoclonal antibodies. Increasing evidence supports the use of such antibody-based strategies as effective steroid-sparing treatments, although the therapies themselves may be associated with additional drug toxicities and reduced ICI efficacy. Kinases are key contributors to the adaptive and innate responses that drive primary autoimmune diseases and irAEs. The janus kinase/signal transducer and activator of transcription, Bruton's tyrosine kinase, and mitogen-activated protein kinase-interacting serine/threonine protein kinases 1 and 2 pathways are also critical to tumor progression and have important roles in cells of the tumor microenvironment. Herein, we review the histopathological, biological, and clinical evidence to support specific monoclonal antibodies and kinase inhibition as management strategies for irAEs.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.004 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".