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Molecular-Based Recursive Partitioning Analysis Model For Glioblastoma In The Temozolomide Era: A Correlative Analysis Based On Nrg Oncology Rtog 0525., Erica Hlavin Bell, Stephanie L Pugh, Joseph P. Mcelroy, Mark R. Gilbert, Minesh Mehta, Alexander C Klimowicz, Anthony Magliocco, Markus Bredel, Pierre Robe, Anca L. Grosu, Roger Stupp, Walter Curran, Aline P. Becker, Andrea L. Salavaggione, Jill S. Barnholtz-Sloan, Kenneth Aldape, Deborah T. Blumenthal, Paul D. Brown, Jon Glass, Luis Souhami, R. Jeffrey Lee, David Brachman, John Flickinger, Minhee Won, Arnab Chakravarti

Department of Neurosurgery Faculty Papers

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 …