Exploring the influence of age on the causes of death in advanced nasopharyngeal carcinoma patients undergoing chemoradiotherapy using machine learning methods

• Published in: Scientific reports Vol. 15; no. 1; pp. 1777 - 10
• Main Authors: Zhang, Mengni, Zhang, Shipeng, Ao, Xudong, Liu, Lisha, Peng, Shunlin
• Format: Journal Article
• Language: English
• Published: London Nature Publishing Group UK 13.01.2025; Nature Publishing Group; Nature Portfolio
• Subjects: 631/67/1059/99; 631/67/70; Adult; Age; Age Factors; Age groups; Aged; Cancer; Cardiovascular diseases; Cause of Death; Chemoradiotherapy; Chemotherapy; Epidemiology; Family income; Fatalities; Female; Histology; Humanities and Social Sciences; Humans; Learning algorithms; Machine Learning; Machine learning models; Male; Marital status; Medical prognosis; Metastases; Metastasis; Middle Aged; multidisciplinary; Nasopharyngeal carcinoma; Nasopharyngeal Carcinoma - mortality; Nasopharyngeal Carcinoma - pathology; Nasopharyngeal Carcinoma - therapy; Nasopharyngeal Neoplasms - mortality; Nasopharyngeal Neoplasms - pathology; Nasopharyngeal Neoplasms - therapy; Patients; Probability learning; Radiation therapy; Science; Science (multidisciplinary); Support vector machines; Survival; Throat cancer; Tumors; Variables; Nasopharyngeal carcinoma; Machine learning models; Chemoradiotherapy; Cause of death; Age

The present study analyzed the impact of age on the causes of death (CODs) in patients with nasopharyngeal carcinoma (NPC) undergoing chemoradiotherapy (CRT) using machine learning approaches. A total of 2841 patients (1037 classified as older, ≥ 60 years and 1804 as younger, < 60 years) were enr...