Recursive partitioning analysis of prognostic variables in newly diagnosed anaplastic oligodendroglial tumors.

NEURO-ONCOLOGY(2014)

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摘要
Background. Anaplastic oligodendroglial tumors are rare, and median survival varies widely. Analysis of 1p19q deletion is performed commonly and is an important prognostic factor. However, age and other clinical variables also carry prognostic value, and it is unclear how to incorporate them into clinical decision making or to combine them for prognostication. Methods. We compiled a retrospective database of 1013 patients with newly diagnosed anaplastic oligodendrogliomas or oligoastrocytomas and performed a recursive partitioning analysis to generate independent prognostic classes among 587 patients with informative 1p19q status. Variables included for survival classification were age (continuous), history of prior low-grade glioma, 1p19q deletion status, histology (presence or absence of an astrocytic component), tumor lobe, tumor hemisphere, gender, extent of resection, postresection treatment, and performance status at diagnosis. Results. Recursive partitioning analysis identified 5 prognostic groups based on hazard similarity: class I (age <60 y, 1p19q codeleted), class II (age, <43 y, not codeleted), class III (age 43-59 y, not codeleted, frontal lobe tumor or age >= 60 y, codeleted), class IV (age 43-59 y, not codeleted, not frontal lobe tumor or age 60-69 y, not codeleted), and class V (age >= 70 y, not codeleted). Survival differences were highly significant (P<.0001), with medians ranging from 9.3 years (95% CI: 8.4-16.0) for class I to 0.6 years (95% CI: 0.5-0.9) for class V. Conclusions. These 5 distinct classification groups were defined using prognostic factors typically obtained during routine management of patients with anaplastic oligodendroglial tumors. Validation in a prospective clinical trial may better differentiate patients with respect to treatment outcome.
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关键词
1p19q deletion,anaplastic,anaplastic oligoastrocytoma,oligodendroglioma,prognosis,recursive partitioning analysis
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