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儿童少突胶质细胞瘤临床结局的预测因素:个体患者数据的荟萃分析与多重填补

Predictors of clinical outcome in pediatric oligodendroglioma: meta-analysis of individual patient data and multiple imputation.

作者信息

Wang Kevin Yuqi, Vankov Emilian R, Lin Doris Da May

机构信息

1Department of Radiology, Baylor College of Medicine, Houston, Texas.

2Center for Energy Studies, Baker Institute for Public Policy, Rice University, Houston, Texas; and.

出版信息

J Neurosurg Pediatr. 2018 Feb;21(2):153-163. doi: 10.3171/2017.7.PEDS17133. Epub 2017 Dec 1.

Abstract

OBJECTIVE Oligodendroglioma is a rare primary CNS neoplasm in the pediatric population, and only a limited number of studies in the literature have characterized this entity. Existing studies are limited by small sample sizes and discrepant interstudy findings in identified prognostic factors. In the present study, the authors aimed to increase the statistical power in evaluating for potential prognostic factors of pediatric oligodendrogliomas and sought to reconcile the discrepant findings present among existing studies by performing an individual-patient-data (IPD) meta-analysis and using multiple imputation to address data not directly available from existing studies. METHODS A systematic search was performed, and all studies found to be related to pediatric oligodendrogliomas and associated outcomes were screened for inclusion. Each study was searched for specific demographic and clinical characteristics of each patient and the duration of event-free survival (EFS) and overall survival (OS). Given that certain demographic and clinical information of each patient was not available within all studies, a multivariable imputation via chained equations model was used to impute missing data after the mechanism of missing data was determined. The primary end points of interest were hazard ratios for EFS and OS, as calculated by the Cox proportional-hazards model. Both univariate and multivariate analyses were performed. The multivariate model was adjusted for age, sex, tumor grade, mixed pathologies, extent of resection, chemotherapy, radiation therapy, tumor location, and initial presentation. A p value of less than 0.05 was considered statistically significant. RESULTS A systematic search identified 24 studies with both time-to-event and IPD characteristics available, and a total of 237 individual cases were available for analysis. A median of 19.4% of the values among clinical, demographic, and outcome variables in the compiled 237 cases were missing. Multivariate Cox regression analysis revealed subtotal resection (p = 0.007 [EFS] and 0.043 [OS]), initial presentation of headache (p = 0.006 [EFS] and 0.004 [OS]), mixed pathologies (p = 0.005 [EFS] and 0.049 [OS]), and location of the tumor in the parietal lobe (p = 0.044 [EFS] and 0.030 [OS]) to be significant predictors of tumor progression or recurrence and death. CONCLUSIONS The use of IPD meta-analysis provides a valuable means for increasing statistical power in investigations of disease entities with a very low incidence. Missing data are common in research, and multiple imputation is a flexible and valid approach for addressing this issue, when it is used conscientiously. Undergoing subtotal resection, having a parietal tumor, having tumors with mixed pathologies, and suffering headaches at the time of diagnosis portended a poorer prognosis in pediatric patients with oligodendroglioma.

摘要

目的

少突胶质细胞瘤是儿科人群中一种罕见的原发性中枢神经系统肿瘤,文献中仅有有限的研究对该实体进行了特征描述。现有研究受样本量小以及已确定的预后因素在不同研究间结果不一致的限制。在本研究中,作者旨在提高评估小儿少突胶质细胞瘤潜在预后因素时的统计效能,并试图通过进行个体患者数据(IPD)荟萃分析以及使用多重填补法处理现有研究中无法直接获取的数据,来调和现有研究之间存在的不一致结果。方法:进行了系统检索,筛选出所有与小儿少突胶质细胞瘤及相关结局有关的研究以纳入分析。在每项研究中查找每位患者的特定人口统计学和临床特征以及无事件生存期(EFS)和总生存期(OS)的时长。鉴于并非所有研究都能获取每位患者的某些人口统计学和临床信息,在确定缺失数据机制后,使用链式方程模型进行多变量填补以估算缺失数据。主要关注的终点是通过Cox比例风险模型计算的EFS和OS的风险比。进行了单变量和多变量分析。多变量模型对年龄、性别、肿瘤分级、混合病理类型、切除范围、化疗、放疗、肿瘤位置和初始表现进行了校正。p值小于0.05被认为具有统计学意义。结果:系统检索确定了24项具有事件发生时间和IPD特征的研究,共有237例个体病例可供分析。在汇总的237例病例中,临床、人口统计学和结局变量中值有19.4%的数据缺失。多变量Cox回归分析显示,次全切除(EFS的p = 0.007,OS的p = 0.043)、初始表现为头痛(EFS的p = 0.006,OS的p = 0.004)、混合病理类型(EFS的p = 0.005,OS的p = 0.049)以及肿瘤位于顶叶(EFS的p = 0.044,OS的p = 0.030)是肿瘤进展或复发及死亡的显著预测因素。结论:使用IPD荟萃分析为在发病率极低的疾病实体研究中提高统计效能提供了一种有价值的方法。缺失数据在研究中很常见,当认真使用时,多重填补是解决这一问题的一种灵活且有效的方法。接受次全切除、患有顶叶肿瘤、具有混合病理类型的肿瘤以及在诊断时出现头痛预示着小儿少突胶质细胞瘤患者的预后较差。

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