Department of Neurosurgery, The First Affiliated Hospital of Jinan University, Guangzhou, China; Department of Clinical Research, The First Affiliated Hospital of Jinan University, Guangzhou, China.
Department of Clinical Research, The First Affiliated Hospital of Jinan University, Guangzhou, China; School of Public Health, Xi'an Jiaotong University Health Science Center, Xi'an, Shaanxi, China.
World Neurosurg. 2021 Nov;155:e131-e141. doi: 10.1016/j.wneu.2021.08.034. Epub 2021 Aug 14.
Socioeconomic status (SES) is presented as a complex structure and has not been studied adequately among adult patients with glioma. This study aims to identify the intrinsic linkages of community-level SES multivariables and discover the effects of the various patterns of these indicators on prognosis of adult gliomas.
Based on data from the SEER (Surveillance Epidemiology and End Results) database, 44,816 adults diagnosed with gliomas from 2007 to 2016 were enrolled for the research. We first used factor analysis and cluster analysis to process SES data. Then, univariable and multivariable Cox proportional hazards models were used to analyze the risk indicators.
Four integrated SES factors were identified: factor 1, economic and social disadvantage (economic and education disadvantage); factor 2, immigration-associated characteristics (foreign-born, language isolation, less household room, recent interstate residential stability); factor 3, housing instability; and factor 4, absence of intrastate mobility. Factor 1 was a risk indicator for survival, whereas factor 2 and factor 4 were protective indicators. All patients fell into 7 cluster groups. Compared with cluster 1, clusters 2, 3, 4, and 7 had a better prognosis, whereas cluster 6 had a shorter survival.
The combinatorial patterns of SES indicators and pattern-based groups do influence the outcomes of adult gliomas. Special attention is given to patients living in areas with specialized economic-educational disadvantages, relocation instability, and immigration-related characteristics.
社会经济地位（SES）被认为是一个复杂的结构，在成年胶质细胞瘤患者中尚未得到充分研究。本研究旨在确定社区层面 SES 多变量的内在联系，并发现这些指标的各种模式对成年胶质细胞瘤预后的影响。
本研究基于 SEER（监测、流行病学和最终结果）数据库的数据，纳入了 2007 年至 2016 年间诊断为胶质细胞瘤的 44816 名成年人。我们首先使用因子分析和聚类分析处理 SES 数据。然后，使用单变量和多变量 Cox 比例风险模型分析风险指标。
确定了四个综合 SES 因素：因素 1，经济和社会劣势（经济和教育劣势）；因素 2，与移民相关的特征（外国出生、语言孤立、家庭房间较少、最近州际居住稳定性）；因素 3，住房不稳定；因素 4，州内流动缺失。因素 1 是生存的风险指标，而因素 2 和因素 4 是保护指标。所有患者分为 7 个聚类组。与聚类 1 相比，聚类 2、3、4 和 7 的预后较好，而聚类 6 的生存时间较短。
SES 指标的组合模式和基于模式的分组确实会影响成年胶质细胞瘤的结果。特别关注生活在具有专业经济教育劣势、搬迁不稳定和与移民相关特征的地区的患者。
