确定有助于诊断为脑胶质瘤的老年人的生存因素并制定预后列线图。组织学诊断为脑胶质瘤的老年人（年龄≥65岁）的数据来源于监测、流行病学和最终结果（SEER） ） 数据库。数据集按 6:4 的比例随机分为训练队列和内部验证队列。此外，从唐都医院获得的数据构成了该研究的外部验证队列。通过最小绝对收缩和选择算子 (LASSO) 和多元 Cox 回归分析实现了独立预后因素的识别，从而能够构建列线图。使用 C 指数、ROC 曲线、校准图和决策曲线分析 (DCA) 评估模型性能。从 SEER 数据库中选择了 20 483 名老年胶质瘤患者队列。研究发现，五个预后因素（年龄、婚姻状况、组织学类型、分期和治疗）显着影响总生存期 (OS) 和癌症特异性生存期 (CSS)，其中肿瘤位置成为与 CSS 独立相关的第六个变量。随后，开发了列线图模型来预测 6、12 和 24 个月的生存概率。验证队列的评估结果表明该模型表现出强大的性能。我们的列线图可以作为评估老年神经胶质瘤患者生存概率的有价值的预后工具。它们可能有助于风险分层和临床决策。© 2024。华中科技大学。

To determine the factors that contribute to the survival of elderly individuals diagnosed with brain glioma and develop a prognostic nomogram.Data from elderly individuals (age ≥65 years) histologically diagnosed with brain glioma were sourced from the Surveillance, Epidemiology, and End Results (SEER) database. The dataset was randomly divided into a training cohort and an internal validation cohort at a 6:4 ratio. Additionally, data obtained from Tangdu Hospital constituted an external validation cohort for the study. The identification of independent prognostic factors was achieved through the least absolute shrinkage and selection operator (LASSO) and multivariate Cox regression analysis, enabling the construction of a nomogram. Model performance was evaluated using C-index, ROC curves, calibration plot and decision curve analysis (DCA).A cohort of 20 483 elderly glioma patients was selected from the SEER database. Five prognostic factors (age, marital status, histological type, stage, and treatment) were found to significantly impact overall survival (OS) and cancer-specific survival (CSS), with tumor location emerging as a sixth variable independently linked to CSS. Subsequently, nomogram models were developed to predict the probabilities of survival at 6, 12, and 24 months. The assessment findings from the validation queue indicate a that the model exhibited strong performance.Our nomograms serve as valuable prognostic tools for assessing the survival probability of elderly glioma patients. They can potentially assist in risk stratification and clinical decision-making.© 2024. Huazhong University of Science and Technology.