{"doi":"10.1002/hed.27878","title":"Evaluation of radiomics as a predictor of efficacy and the tumor immune microenvironment in anti‐<scp>PD</scp>‐1 <scp>mAb</scp> 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.","journal":"Head & Neck","year":2024,"id":449014,"datarank":0.0,"base_score":0.0,"endowment":0.0,"self_citation_contribution":0.0,"citation_network_contribution":0.0,"self_endowment_contribution":0.0,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":5,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.9222,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2024-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":821046,"name":"Şerafettin Zenkin","orcid":null,"position":1,"is_corresponding":false},{"id":661413,"name":"Murat Ak","orcid":"0000-0001-7384-478X","position":2,"is_corresponding":false},{"id":661414,"name":"Priyadarshini Mamindla","orcid":"0000-0002-5070-1353","position":3,"is_corresponding":false},{"id":820662,"name":"Vishal Peddagangireddy","orcid":"0000-0002-3912-2713","position":4,"is_corresponding":false},{"id":1186973,"name":"Ronan W. Hsieh","orcid":"0000-0003-1899-9812","position":5,"is_corresponding":false},{"id":1268381,"name":"Jennifer L. Anderson","orcid":"0000-0002-1471-5803","position":6,"is_corresponding":false},{"id":237079,"name":"Greg M. Delgoffe","orcid":"0000-0002-2957-8135","position":7,"is_corresponding":false},{"id":1268842,"name":"Ashely Menk","orcid":null,"position":8,"is_corresponding":false},{"id":299195,"name":"Heath D. Skinner","orcid":"0000-0003-1836-151X","position":9,"is_corresponding":false},{"id":109271,"name":"Umamaheswar Duvvuri","orcid":"0000-0003-1968-3756","position":10,"is_corresponding":false},{"id":109277,"name":"Robert L. Ferris","orcid":"0000-0001-6605-2071","position":11,"is_corresponding":false},{"id":106286,"name":"Rivka R. Colen","orcid":"0000-0002-0882-0607","position":12,"is_corresponding":false},{"id":477535,"name":"Dan P. Zandberg","orcid":"0000-0002-1002-8301","position":0,"is_corresponding":true}],"reference_count":22,"raw_metadata":null,"created_at":"2026-07-19T02:02:16.291892Z","pmid":"39080968","pmcid":null,"fwci":null,"citation_percentile":null,"influential_citations":0,"oa_status":null,"license":null,"views":0,"total_file_size_bytes":0,"version_count":0,"fair_f":null,"fair_a":null,"fair_i":null,"fair_r":null,"fair_zscore":null,"fair_rationale":null,"fair_model":null,"fair_agent_version":null,"fair_fulltext_source":null,"fair_has_llm":null,"fair_computed_at":null,"clinical_trials":[],"software_tools":[],"db_accessions":[],"linked_datasets":[],"topics":[]}