ArticleHead & neck2025
Evaluation of radiomics as a predictor of efficacy and the tumor immune microenvironment in anti-PD-1 mAb treated recurrent/metastatic squamous cell carcinoma of the head and neck patients.
Article in Head & neck, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
7 citing papers in PubMed.
- Application of artificial intelligence in head and neck squamous cell carcinoma.Annals of medicine · 2026Review
- Radiomics as a spatial context for treatment decision-making in head and neck cancer.British journal of cancer · 2026Review
- Stratifying tumor immune microenvironment in head and neck squamous cell carcinoma: from parsing out immune-subtype prognosis to clinically applicable CT-radiomics models.Journal of translational medicine · 2026Article
- [Application of neoadjuvant immunotherapy in head and neck squamous cell carcinoma: From mechanisms to clinical practice].Zhong nan da xue xue bao. Yi xue ban = Journal of Central South University. Medical sciences · 2025Review
- Targeting Cancer Cell Fate: Apoptosis, Autophagy, and Gold Nanoparticles in Treatment Strategies.Current issues in molecular biology · 2025Review
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Authors and funding
13 authors.
Funding
Abstract
backgroundWe retrospectively evaluated radiomics as a predictor of the tumor microenvironment (TME) and efficacy with anti-PD-1 mAb (IO) in R/M HNSCC.
methodsRadiomic feature extraction was performed on pre-treatment CT scans segmented using 3D slicer v4.10.2 and key features were selected using LASSO regularization method to build classification models with XGBoost algorithm by incorporating cross-validation techniques to calculate accuracy, sensitivity, and specificity. Outcome measures evaluated were disease control rate (DCR) by RECIST 1.1, PFS, and OS and hypoxia and CD8 T cells in the TME.
resultsRadiomics features predicted DCR with accuracy, sensitivity, and specificity of 76%, 73%, and 83%, for OS 77%, 86%, 70%, PFS 82%, 75%, 89%, and in the TME, for high hypoxia 80%, 88%, and 72% and high CD8 T cells 91%, 83%, and 100%, respectively.
conclusionRadiomics accurately predicted the efficacy of IO and features of the TME in R/M HNSCC. Further study in a larger patient population is warranted.
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