Molecular-Based Recursive Partitioning Analysis Model for Glioblastoma in the Temozolomide Era: A Correlative Analysis Based on NRG Oncology RTOG 0525.

ABSTRACT:

Importance

There is a need for a more refined, molecularly based classification model for glioblastoma (GBM) in the temozolomide era.

Objective

To refine the existing clinically based recursive partitioning analysis (RPA) model by incorporating molecular variables.

Design, setting, and participants

NRG Oncology RTOG 0525 specimens (n = 452) were analyzed for protein biomarkers representing key pathways in GBM by a quantitative molecular microscopy-based approach with semiquantitative immunohistochemical validation. Prognostic significance of each protein was examined by single-marker and multimarker Cox regression analyses. To reclassify the prognostic risk groups, significant protein biomarkers on single-marker analysis were incorporated into an RPA model consisting

SUBMITTER: Bell EH 

PROVIDER: S-EPMC5464982 | biostudies-literature | 2017 Jun

REPOSITORIES: biostudies-literature