Objective:This study aimed to identify the factors associated with overall survival (OS) in adult patients with primary gliomas, construct a nomogram prediction model, and evaluate its predictive performance.Methods:Clinical data were retrospectively collected from adult patients newly diagnosed with gliomas who underwent surgical treatment in the Department of Neurosurgery of the Fourth Hospital of Hebei Medical University, between January 2019 and December 2023. External validation was conducted using data from the China Glioma Genome Atlas (CGGA) database. Data analysis and visualization were performed using SPSS 26.0 and R software (Version 4.4.1).Results:A total of 257 adult patients were included in this study. Multivariate Cox regression analysis identified age, Karnofsky Performance Status (KPS) score, tumor diameter, WHO grade, and postoperative radiotherapy and chemotherapy, as well as the expression of ATRX, IDH1, and Ki-67, as independent prognostic factors. These factors were incorporated into a nomogram for predicting 1-year, 2-year, and 3-year survival rates. The model demonstrated excellent discrimination, calibration, and clinical utility in both internal and external validations.Conclusions:The nomogram model incorporating clinical factors (age, WHO grade), treatment (radiotherapy, chemotherapy), and tumor markers (ATRX, IDH1, Ki-67) has good predictive efficacy and may serve as a practical and effective alternative to molecular testing for prediction of survival in adult patients with primary glioma.
目的：本研究旨在识别与成人原发性胶质瘤患者总生存期相关的因素，构建列线图预测模型，并评估其预测性能。 方法：回顾性收集2019年1月至2023年12月期间在河北医科大学第四医院神经外科接受手术治疗的初诊成人胶质瘤患者的临床资料。使用中国胶质瘤基因组图谱数据库的数据进行外部验证。数据分析与可视化采用SPSS 26.0和R软件完成。 结果：本研究共纳入257例成人患者。多因素Cox回归分析显示，年龄、卡氏功能状态评分、肿瘤直径、世界卫生组织分级、术后放化疗以及ATRX、IDH1和Ki-67的表达情况是独立的预后因素。基于这些因素构建了预测1年、2年和3年生存率的列线图模型。该模型在内部和外部验证中均表现出良好的区分度、校准度和临床实用性。 结论：整合临床因素、治疗因素及肿瘤标志物的列线图模型具有良好的预测效能，可作为预测成人原发性胶质瘤患者生存期的实用有效工具。
肿瘤(癌症)患者之家