Effectiveness of radiotherapy or chemoradiotherapy in older patients with advanced-stage, non-surgically treated head and neck cancer: A machine learning analysis.

IF 4.7 4区 医学 Q2 ONCOLOGY
Rasheed Omobolaji Alabi, Alhadi Almangush, Mohammed Elmusrati, Ylva Tiblom Ehrsson, Göran Laurell, Antti A Mäkitie
{"title":"Effectiveness of radiotherapy or chemoradiotherapy in older patients with advanced-stage, non-surgically treated head and neck cancer: A machine learning analysis.","authors":"Rasheed Omobolaji Alabi, Alhadi Almangush, Mohammed Elmusrati, Ylva Tiblom Ehrsson, Göran Laurell, Antti A Mäkitie","doi":"10.1007/s12032-026-03420-5","DOIUrl":null,"url":null,"abstract":"<p><p>The rising incidence of head and neck squamous cell carcinoma (HNSCC) is linked to both the HPV epidemic and the aging population. As a result, there is an emerging need to develop management strategies for older patients with advanced-stage HNSCC. This study aims to apply machine learning (ML) techniques to compare the effectiveness of definitive concurrent chemoradiotherapy (CRT) and radiotherapy (RT) alone in older patients (≥ 65 years) with stage III-IV non-surgically treated HNSCC. We used Kaplan-Meier (KM) survival curves, Cox proportional hazards models, and ML-based permutation feature importance (PFI) to compare the effectiveness of CRT versus single modality radiotherapy (RT) for disease-specific survival (DSS) in this population of patients with HNSCC. Finally, we used propensity-score matched (PSM) analysis to clarify if there is a significant difference between patients that received either CRT or RT alone. A total of 1525 patients with HNSCC were obtained from the Surveillance, Epidemiology, and End Results (SEER) Program to build the ML model. Furthermore, the PFI analysis evaluated the effectiveness of CRT or RT alone regarding DSS of older (≥ 65 year) patients with HNSCC. Then, we performed a 1:1 propensity-score matched (PSM) analysis to reduce treatment selection bias and to analyze the prognostic role of CRT. Our ML model showed performance accuracy of 55.5% in predicting DSS in this group with HNSCC. The aggregate feature importance showed that treatment option (CRT or RT alone) is among the four most important features for enhancing DSS among these patients. Specifically, our KM curves, Cox proportional hazards model, and PFI analyses all showed that CRT seems more feasible and effective than RT alone for older patients with stage III-IV HNSCC who did not receive surgery. In addition, patients with stage III disease had better survival rates than those with stage IV. The PSM confirmed that there are substantial differences in nearly all covariates between patients who received CRT or RT alone. The results from the SEER database provide insight into a potential survival benefit for CRT in older patients with stage III-IV HNSCC who are not candidates for surgery. This further emphasizes that treatment decisions at an advanced stage may be made according to other patient-related factors rather than chronological (calendar) age alone.</p>","PeriodicalId":18433,"journal":{"name":"Medical Oncology","volume":"43 11","pages":""},"PeriodicalIF":4.7000,"publicationDate":"2026-10-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13649891/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Medical Oncology","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1007/s12032-026-03420-5","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ONCOLOGY","Score":null,"Total":0}
引用次数: 0

Abstract

The rising incidence of head and neck squamous cell carcinoma (HNSCC) is linked to both the HPV epidemic and the aging population. As a result, there is an emerging need to develop management strategies for older patients with advanced-stage HNSCC. This study aims to apply machine learning (ML) techniques to compare the effectiveness of definitive concurrent chemoradiotherapy (CRT) and radiotherapy (RT) alone in older patients (≥ 65 years) with stage III-IV non-surgically treated HNSCC. We used Kaplan-Meier (KM) survival curves, Cox proportional hazards models, and ML-based permutation feature importance (PFI) to compare the effectiveness of CRT versus single modality radiotherapy (RT) for disease-specific survival (DSS) in this population of patients with HNSCC. Finally, we used propensity-score matched (PSM) analysis to clarify if there is a significant difference between patients that received either CRT or RT alone. A total of 1525 patients with HNSCC were obtained from the Surveillance, Epidemiology, and End Results (SEER) Program to build the ML model. Furthermore, the PFI analysis evaluated the effectiveness of CRT or RT alone regarding DSS of older (≥ 65 year) patients with HNSCC. Then, we performed a 1:1 propensity-score matched (PSM) analysis to reduce treatment selection bias and to analyze the prognostic role of CRT. Our ML model showed performance accuracy of 55.5% in predicting DSS in this group with HNSCC. The aggregate feature importance showed that treatment option (CRT or RT alone) is among the four most important features for enhancing DSS among these patients. Specifically, our KM curves, Cox proportional hazards model, and PFI analyses all showed that CRT seems more feasible and effective than RT alone for older patients with stage III-IV HNSCC who did not receive surgery. In addition, patients with stage III disease had better survival rates than those with stage IV. The PSM confirmed that there are substantial differences in nearly all covariates between patients who received CRT or RT alone. The results from the SEER database provide insight into a potential survival benefit for CRT in older patients with stage III-IV HNSCC who are not candidates for surgery. This further emphasizes that treatment decisions at an advanced stage may be made according to other patient-related factors rather than chronological (calendar) age alone.

放疗或放化疗对老年晚期非手术治疗头颈癌患者的有效性:机器学习分析。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
Medical Oncology
Medical Oncology 医学-肿瘤学
CiteScore
4.20
自引率
2.90%
发文量
259
审稿时长
1.4 months
期刊介绍: Medical Oncology (MO) communicates the results of clinical and experimental research in oncology and hematology, particularly experimental therapeutics within the fields of immunotherapy and chemotherapy. It also provides state-of-the-art reviews on clinical and experimental therapies. Topics covered include immunobiology, pathogenesis, and treatment of malignant tumors.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术官方微信
小红书