The DOI matches its Crossref record; 42 of the 42 references it cites were found in a registry or an index.
A review of cancer immunotherapy toxicity
Open accessAbstract
Cancer immunotherapies, including checkpoint inhibitors and adoptive cell therapy, manipulate the immune system to recognize and attack cancer cells. These therapies have the potential to induce durable responses in multiple solid and hematologic malignancies and thus have transformed treatment algorithms for numerous tumor types. Cancer immunotherapies lead to unique toxicity profiles distinct from the toxicities of other cancer therapies, depending on their mechanism of action. These toxicities often require specific management, which can include steroids and immune‐modulating therapy and for which consensus guidelines have been published. This review will focus on the toxicities of checkpoint inhibitors and chimeric antigen receptor T cells, including pathophysiology, diagnosis, and management.
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Cites
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Cited by
Dai, M., Liu, D., Liu, M., Zhou, F., Li, G., Chen, Z., Zhang, Z., You, H., Wu, M., Zheng, Q., et al. (2020) · Cancer Discovery · doi:10.1158/2159-8290.cd-20-0422 · Cited by 1,589
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Artificial intelligence for multimodal data integration in oncology
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Nanoparticles in tumor microenvironment remodeling and cancer immunotherapy
Lu, Q., Kou, D., Lou, S., Ashrafizadeh, M., Aref, A. R., Canadas, I., Tian, Y., Niu, X., Wang, Y., Torabian, P., et al. (2024) · Journal of Hematology & Oncology · doi:10.1186/s13045-024-01535-8 · Cited by 373
Metadata
- Authors
- Kennedy, L. B., & Salama, A. K. S.
- Venue
- CA: A Cancer Journal for Clinicians
- Publisher
- Wiley
- Published
- 2020-01-16
- Volume
- 70
- Issue
- 2
- Pages
- 86-104
- ISSN
- 0007-9235 (ISSN-L)
- 1542-4863
- OpenAlex
- W2999281781
- Cited by
- 1,364
- References
- 42
- FWCI
- 62.48
- Type
- journal article
- Language
- en
- Open access
- gold
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
