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

Abstract Background We retrospectively evaluated radiomics as a predictor of the tumor microenvironment (TME) and efficacy with anti‐PD‐1 mAb (IO) in R/M HNSCC. Methods Radiomic 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. Results Radiomics 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. Conclusion Radiomics accurately predicted the efficacy of IO and features of the TME in R/M HNSCC. Further study in a larger patient population is warranted.