Literature DB >> 29192869

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

Kevin Yuqi Wang1, Emilian R Vankov2, Doris Da May Lin3.   

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.

Entities:  

Keywords:  CCA = complete-case analysis; EFS = event-free survival; GTR = gross-total resection; HR = hazard ratio; IPD = individual patient data; MAR = missing at random; MCAR = missing completely at random; MICE = multivariable imputation via chained equations; MNAR = missing not at random; OS = overall survival; RT = radiation therapy; STR = subtotal resection; meta-analysis; multiple imputation; oligodendroglioma; oncology

Mesh:

Year:  2017        PMID: 29192869     DOI: 10.3171/2017.7.PEDS17133

Source DB:  PubMed          Journal:  J Neurosurg Pediatr        ISSN: 1933-0707            Impact factor:   2.375


  2 in total

1.  Prognosis of Oligodendroglioma Patients Stratified by Age: A SEER Population-Based Analysis.

Authors:  Kai Jin; Shu-Yuan Zhang; Li-Wen Li; Yang-Fan Zou; Bin Wu; Liang Xia; Cai-Xing Sun
Journal:  Int J Gen Med       Date:  2021-12-09

2.  Radiological assessment schedule for 1p/19q-codeleted gliomas during the surveillance period using parametric modeling.

Authors:  Ho Kang; Jongjin Lee; So Young Ji; Seung Won Choi; Kyung-Min Kim; Joo Ho Lee; Soon-Tae Lee; Jae Kyung Won; Tae Min Kim; Seung Hong Choi; Sung-Hye Park; Kyung-Sub Moon; Chae-Yong Kim; Heon Yoo; Do-Hyun Nam; Jeong Hoon Kim; Yongdai Kim; Chul-Kee Park
Journal:  Neurooncol Adv       Date:  2021-05-20
  2 in total

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