Predicting immunotherapy response in stage III-IV non-small cell lung cancer using integrated radiomics and clinical features
This study developed a predictive model based on clinical and radiomic features for assessing immunotherapy efficacy in NSCLC. The model demonstrated excellent performance, suggesting its potential as a clinical decision-support tool for prognosis prediction and treatment planning in NSCLC immunotherapy.
Authors
- Zhijun Li (ORCID: https://orcid.org/0000-0002-4252-7631)
- Na Geng (ORCID: https://orcid.org/0000-0001-5389-6072)
- Haitao Ma (ORCID: https://orcid.org/0000-0002-0632-1089)
- Yuxiang Li (ORCID: https://orcid.org/0000-0002-9547-1838)
- Langlang Deng
Institutions
- Soochow University (CN)
- Second Affiliated Hospital of Soochow University (CN)
- The Second Affiliated Hospital of Bengbu Medical College (CN)
- First Affiliated Hospital of Soochow University (CN)
Publication Details
- Journal
- Frontiers in Oncology
- Published
- 2025-11-07
- DOI
- https://doi.org/10.3389/fonc.2025.1669469
- Primary Topic
- Radiomics and Machine Learning in Medical Imaging
- Type
- article
- Field-Weighted Citation Impact
- 0.00