Radiomic biomarkers for platinum‐refractory head and neck cancer in the era of immunotherapy

Author:

Lu Hsueh‐Ju12ORCID,Shen Chao‐Yu23,Chiu Yu‐Wei45,Lin Wea‐Lung26,Peng Chih‐Yu45,Tseng Hsien‐Chun27,Hsin Chung‐Han28,Chuang Chun‐Yi28,Chen Chun‐Chia29,Wu Ming‐Fang12,Huang Wei‐Shiou12,Shen Wei‐Chih1011

Affiliation:

1. Division of Hematology and Oncology, Department of Internal Medicine Chung Shan Medical University Hospital Taichung Taiwan

2. College of Medicine Chung Shan Medical University Taichung Taiwan

3. Department of Medical Imaging Chung Shan Medical University Hospital Taichung Taiwan

4. Department of Stomatology Chung Shan Medical University Hospital Taichung Taiwan

5. College of Oral Medicine Chung Shan Medical University Taichung Taiwan

6. Department of Pathology Chung Shan Medical University and Hospital Taichung Taiwan

7. Department of Radiation Oncology Chung Shan Medical University Hospital Taichung Taiwan

8. Department of Otolaryngology Chung Shan Medical University Hospital Taichung Taiwan

9. Division of Plastic Surgery, Department of Surgery Chung Shan Medical University Hospital Taichung Taiwan

10. Department of Medical Informatics Chung Shan Medical University Taichung Taiwan

11. Artificial Intelligence Center Chung Shan Medical University Hospital Taichung Taiwan

Abstract

AbstractObjectiveImmune 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.MethodsA 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.ResultsThe 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.ConclusionsRadiomic features were effective prognostic and predictive biomarkers. Future studies are warranted.

Publisher

Wiley

Subject

General Dentistry,Otorhinolaryngology

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