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Adverse Events Following Cancer Immunotherapy: Obstacles and Opportunities
Open accessAbstract
Oncology has recently undergone a revolutionary change with widespread adoption of immunotherapy for many cancers. Immunotherapy using monoclonal antibodies against checkpoint molecules, including programmed death (PD)-1, PD ligand (PD-L)1, and cytotoxic T lymphocyte-associated antigen (CTLA)-4, is effective in a significant subset of patients. However, immune-related adverse events (irAEs) have emerged as frequent complications of checkpoint blockade, likely due to the physiological role of checkpoint pathways in regulating adaptive immunity and preventing autoimmunity. As immunotherapy becomes more common, a better understanding of the etiology of irAEs and ways to limit these events is needed. At the same time, studying these new therapy-related disorders provides an opportunity to better understand naturally occurring human autoimmune and inflammatory disorders, with the potential to improve therapies for cancer and autoimmune diseases.
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“The breadth of systems affected, severity and timing of irAEs can all vary between agents, specifically between anti-CTLA-4 agents and anti-PD-1/PD-L1 and combinations thereof”
From Hallmarks of response, resistance, and toxicity to immune checkpoint blockade (2021) · cites this paper as Pauken et al., 2019
In the citing paper
“irAEs are common, with a low-grade (Grade 1-2) effect observed in up to more than 90% of patients, while more severe effects (Grades 3-5) can range from 20-60%”
From Hallmarks of response, resistance, and toxicity to immune checkpoint blockade (2021) · cites this paper as Pauken et al., 2019
In the citing paper
“irAEs comprise over 70 different pathologies affecting nearly every organ system including the neurologic, genitourinary, gastrointestinal, pulmonary, cardiovascular, and integumentary systems”
From Hallmarks of response, resistance, and toxicity to immune checkpoint blockade (2021) · cites this paper as Pauken et al., 2019
In the citing paper
“the onset of irAE varies widely with some starting days to weeks after therapy and others months”
From Hallmarks of response, resistance, and toxicity to immune checkpoint blockade (2021) · cites this paper as Pauken et al., 2019
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Metadata
- Authors
- Pauken, K. E., Dougan, M., Rose, N. R., Lichtman, A. H., & Sharpe, A. H.
- Affiliations
- Brigham and Women's Hospital (US)
- Harvard University (US)
- Corresponding author
- Lichtman, Andrew H.
- Sharpe, Arlene H.
- Venue
- Trends in Immunology
- Publisher
- Elsevier BV
- Published
- 2019-06
- Volume
- 40
- Issue
- 6
- Pages
- 511-523
- ISSN
- 1471-4906 (ISSN-L)
- PMC
- PMC6527345
- OpenAlex
- W2943668434
- Cited by
- 280
- References
- 97
- Citations by year
- 2026: 24 · 2025: 33 · 2024: 43 · 2023: 46 · 2022: 42 · 2021: 37 · 2020: 40 · 2019: 15
- FWCI
- 3.19
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Licence
- Locations
- Trends in Immunology (acceptedVersion)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- Funders
- US National Institutes of Health Mentored Clinical Scientist Development Award (1K08DK114563-01)
- American Gastroenterological Association Research Scholars Award (HL121363, HL13186)
- National Institutes of Health (R01 AI040614, P01 AI056299, AI108545)
- Topics
- Health Sciences › Medicine › Oncology › Cancer Immunotherapy and Biomarkers
- Life Sciences › Immunology and Microbiology › Immunology › Immunotherapy and Immune Responses
- Life Sciences › Immunology and Microbiology › Immunology › T-cell and B-cell Immunology
- Keywords
- immune-related adverse events, cancer immunotherapy, immune checkpoint blockade, PD-1, PD-L1, CTLA-4, monoclonal antibodies, autoimmunity, autoimmune disease therapy
- MeSH terms
- Antineoplastic Agents, Immunological, Animals, Disease Susceptibility, Humans, Immunotherapy, Neoplasms, Biomarkers, Tumor, Autoimmunity, T-Lymphocyte Subsets, Disease Management, Immunomodulation, Tumor Microenvironment, Patient Outcome Assessment
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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