Abstract 7451: Efficacy of chemoradiotherapy in older patients with advanced stage head and neck cancer: A propensity and machine learning analysis

Abstract Background: The rising incidence of head and neck squamous cell carcinoma (HNSCC) is linked with both human papillomavirus and aging population. As a result, there is an emerging need for developing management strategies for older patients with advanced-stage HNSCC. This study aims to use machine learning (ML) techniques to examine the efficacy of definitive, concurrent chemoradiotherapy (CRT) for older patients (≥65 years) with stage III-IV HNSCC. We used permutation feature importance (PFI) to compare the efficacy of CRT with single-modality radiotherapy (RT) for the overall survival (OS) of this HNSCC subgroup. Finally, we compared the results obtained using ML analysis with propensity-score matched (PSM) analysis to clarify the efficacy of CRT in this patient population. Methods: A total of 3570 patients with HNSCC were obtained from the Surveillance, Epidemiology, and End Results (SEER) Program to build the ML model. We compared voting ensemble and extreme gradient boosting algorithms for stratifying older (≥65 years) HNSCC patients into OS risk groups. Furthermore, the PFI analysis was based on stacked ML models to evaluate the efficacy of CRT regarding OS of older (≥65 years) HNSCC patients. Then, we performed a 1:1 propensity-score matched (PSM) analysis to reduce treatment selection bias and analyze the prognostic role of CRT. Results: Our ML model showed a performance accuracy of 85.2% in predicting OS in this subgroup of HNSCC. The aggregate feature importance showed that CRT is the most important feature for OS in this group of HNSCC patients. In addition, patients with stage IV disease showed better survival than those with stage III. The PSM confirmed the efficacy of CRT compared to RT alone. Conclusions: This study showed that CRT may be more feasible and effective than RT alone for older patients with stage III-IV HNSCC. This further emphasized that advanced-stage treatment decisions should rather be made according to other patient-related factors than chronologic (calendar) age alone. Therefore, validating these models with multi-institutional datasets and testing them in the context of clinical trials is warranted to confirm the efficacy of CRT over RT alone for older patients (≥65 years) with stage III-IV HNSCC. Citation Format: Rasheed Omobolaji Alabi, Alhadi Almangush, Antti Mäkitie. Efficacy of chemoradiotherapy in older patients with advanced stage head and neck cancer: A propensity and machine learning analysis [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 7451.