1. Radiomic biomarkers for platinum‐refractory head and neck cancer in the era of immunotherapy.
- Author
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Lu, Hsueh‐Ju, Shen, Chao‐Yu, Chiu, Yu‐Wei, Lin, Wea‐Lung, Peng, Chih‐Yu, Tseng, Hsien‐Chun, Hsin, Chung‐Han, Chuang, Chun‐Yi, Chen, Chun‐Chia, Wu, Ming‐Fang, Huang, Wei‐Shiou, and Shen, Wei‐Chih
- Subjects
MORTALITY risk factors ,SQUAMOUS cell carcinoma ,RISK assessment ,CISPLATIN ,RESEARCH funding ,CANCER relapse ,PREDICTION models ,RADIOMICS ,HEAD & neck cancer ,IMMUNOTHERAPY ,PROGRAMMED death-ligand 1 ,TUMOR markers ,CARBOPLATIN ,DECISION making in clinical medicine ,RETROSPECTIVE studies ,DESCRIPTIVE statistics ,IMMUNE checkpoint inhibitors ,METASTASIS ,GENE expression ,DRUG efficacy ,OVERALL survival ,EVALUATION - Abstract
Objective: Immune checkpoint inhibitors (ICI) are recommended as the first‐line therapy for platinum‐refractory head and neck squamous cell carcinoma (HNSCC), a disease with a poor prognosis. However, biomarkers in this situation are rare. The objective was to identify radiomic features‐associated biomarkers to guide the prognosis and treatment opinions in the era of ICI. Methods: A total of 31 platinum‐refractory HNSCC patients were retrospectively enrolled. Of these, 65.5% (20/31) received ICI‐based therapy and 35.5% (11/31) did not. Radiomic features of the primary site at the onset of recurrent metastatic (R/M) status were extracted. Prognostic and predictive radiomic biomarkers were analysed. Results: The median overall survival from R/M status (R/M OS) was 9.6 months. Grey‐level co‐occurrence matrix‐associated texture features were the most important in identifying the patients with or without 9‐month R/M death. A radiomic risk‐stratification model was established and equally separated the patients into high‐, intermittent‐ and lower‐risk groups (1‐year R/M death rate, 100.0% vs. 70.8% vs. 27.1%, p = 0.001). Short‐run high grey‐level emphasis (SRHGE) was more suitable than programmed death ligand 1 (PD‐L1) expression in selecting whether patients received ICI‐based therapy. Conclusions: Radiomic features were effective prognostic and predictive biomarkers. Future studies are warranted. [ABSTRACT FROM AUTHOR]
- Published
- 2024
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