Factors inducing cutaneous adverse reactions in cancer patients treated with PD-1 and PD-L1 inhibitors: a machine-learning algorithm approach
This pioneering study contributes crucial insights into predictive modeling for ICI-induced skin reactions, emphasizing the importance of personalized treatment strategies. By identifying risk factors and utilizing tailored predictive models, healthcare providers can proactively manage adverse events, optimizing the benefits of ICIs while mitigating potential side effects.
Authors
- Young‐Ah Cho
- Yerin Lee (ORCID: https://orcid.org/0000-0001-5038-0548)
- Youn-Sung Moon
- Woo‐Young Park (ORCID: https://orcid.org/0000-0003-2250-3613)
- Dong Chul Kim (ORCID: https://orcid.org/0000-0002-9484-7792)
- Kyung-Eun Lee (ORCID: https://orcid.org/0000-0003-1048-9068)
- Woorim Kim (ORCID: https://orcid.org/0000-0001-7267-6745)
Institutions
- Chungbuk National University (KR)
- Kangwon National University (KR)
- Gyeongsang National University (KR)
- Gyeongsang National University Hospital (KR)
- Public Risk Management Association (US)
Publication Details
- Journal
- Immunopharmacology and Immunotoxicology
- Published
- 2024-11-15
- DOI
- https://doi.org/10.1080/08923973.2024.2430670
- Citations
- 2
- Primary Topic
- Cancer Immunotherapy and Biomarkers
- Type
- article
- Field-Weighted Citation Impact
- 0.57