室管膜瘤
医学
队列
比例危险模型
内科学
多元分析
肿瘤科
生存分析
无进展生存期
外科
总体生存率
作者
Fu Zhao,Tao Wu,Lei‐Ming Wang,Jing Zhang,Heng Zhang,Shiwei Li,Shun Zhang,Peng Li,Bo Wang,Lin Luo,Pinan Liu
标识
DOI:10.1097/pas.0000000000001669
摘要
Adult intracranial ependymomas (EPNs) are extremely rare brain tumors. Currently, clinical and molecular factors that could inform individualized treatment strategies are still lacking for EPNs in this age group. The aim of this study was to investigate potential prognostic indicators and rational therapeutic management in a large cohort of adult intracranial EPNs. Adult patients who underwent resection of World Health Organization (WHO) grade II or III intracranial EPNs were included. The demographic features, clinicopathologic manifestations, molecular subgroups, and outcomes were retrospectively analyzed. Overall survival and progression-free survival were calculated using the Kaplan-Meier analysis. Potential prognostic indicators were identified using multivariable Cox proportional hazards model. This cohort included 236 adult patients with a mean age of 36.2 years (range: 18 to 72 y) at diagnosis. The tumor location was supratentorial (ST) in 102 (43.2%) and infratentorial in 134 (56.8%). Pathologic analysis revealed 43.1% of ST-EPNs with RELA fusion and 88.1% of posterior fossa ependymomas (PF-EPNs) with positive H3K27me3 staining. Gross total removal was achieved in 169 cases (71.6%). During follow-up, 97 (41.1%) patients had disease progression and 39 (16.5%) died. Kaplan-Meier analysis showed that patients with H3K27me3-positive PF-EPN had excellent survival, whereas patients with RELA fusion-positive ST-EPN or H3K27me3-negative PF-EPN had poor prognosis (progression-free survival: P =1.3E−16, overall survival: P =2.5E−12). Multivariate analysis showed that molecular subgroup, extent of resection, and Ki-67 index were strong independent prognostic indicators. In conclusion, our study provides essential information on the prognostic prediction of adult intracranial EPNs that will assist in establishing appropriate risk stratification and individualized treatment strategies in future clinical trials.
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