Joint NCCTG and NABTC prognostic factors analysis for high-grade recurrent glioma

被引:87
作者
Wu, Wenting [1 ]
Lamborn, Kathleen R. [2 ]
Buckner, Jan C. [1 ]
Novotny, Paul J. [1 ]
Chang, Susan M. [2 ]
O'Fallon, Judith R. [1 ]
Jaeckle, Kurt A. [3 ]
Prados, Michael D. [2 ]
机构
[1] Mayo Clin & Mayo Fdn, Rochester, MN 55905 USA
[2] Univ Calif San Francisco, Dept Neurol Surg, San Francisco, CA 94143 USA
[3] Mayo Clin Florida, Dept Neurol, Jacksonville, FL USA
关键词
brain tumors; high grade; prognostic factors; recurrent glioma; II CLINICAL-TRIALS;
D O I
10.1093/neuonc/nop019
中图分类号
R73 [肿瘤学];
学科分类号
100214 [肿瘤学];
摘要
The purpose of this study is to determine prognostic factors in patients with high-grade recurrent glioma for 3 outcome variables (overall survival, progression-free survival [PFS], and PFS rate 6 months after study registration [PFS6]). Data from 15 North Central Cancer Treatment Group (NCCTG) trials (n = 469, 1980-2004) and 12 North American Brain Tumor Consortium (NABTC) trials (n = 596, 19982002) were included. Eighteen prognostic variables were considered including type of treatment center (community/academic) and initial low-grade histology (yes/no). Recursive partitioning analysis (RPA), Cox proportional hazards, and logistic regression models with bootstrap resampling were used to identify prognostic variables. Longer survival was associated with last known grade (Grade) of III, younger age, ECOG performance score (PS) of 0, shorter time from initial diagnosis (DxTime), and no baseline steroid use. Factors associated with longer PFS were Grade III and shorter DxTime. For patients without temozolomide as part of the treatment regimen, the only factor associated with better PFS6 was Grade III, although DxTime was important in RPA and PS was important in logistic regression. Grade was the most important prognostic factor for all three endpoints regardless of the statistical method used. Other important variables for one or more endpoints included age, PS, and DxTime. Neither type of treatment center nor initial low-grade histology was identified as a major predictor for any endpoint.
引用
收藏
页码:164 / 172
页数:9
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