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The impact of the molecular classification of glioblastoma on the interpretation of therapeutic clinical trial results
Author(s) -
Lauren Singer,
Alexander Feldman,
Robin Buerki,
Craig Horbinski,
Rimas V. Lukas,
Roger Stupp
Publication year - 2021
Publication title -
chinese clinical oncology
Language(s) - English
Resource type - Journals
eISSN - 2304-3873
pISSN - 2304-3865
DOI - 10.21037/cco-21-33
Subject(s) - medicine , clinical trial , context (archaeology) , identification (biology) , glioblastoma , medical diagnosis , glioma , medical physics , intensive care medicine , bioinformatics , pathology , cancer research , biology , paleontology , botany
In 2016, the World Health Organization (WHO) released the most recent update to the classification of central nervous system tumors. This update has led to the reshaping of tumor identification and subsequently changed current understanding of treatment options for patients. Moreover, the restructuring of the classification of central nervous system tumors to include molecular markers has led to the need to re-evaluate how to interpret pivotal trials. These trials originally enrolled patients purely based upon histologic diagnoses without the use of adjunctive, and frequently diagnostic molecular testing. With this new paradigm also comes the need to assess how one should incorporate molecular markers into current trials as well as shape future trials. First, we will discuss updates on the molecular classification of glioblastoma (GBM) (and its histologic mimics). This will be followed by a review of key pivotal trials which have defined our standard of care for glioblastoma within the context of molecular classification of their study populations. This will be followed by preliminary results of ongoing phase 3 cooperative group trials for high-grade gliomas that were initiated prior to routine molecular classification of tumors and how one could interpret these results in light of advances in molecular classification. Finally, we will end with suggestions for future clinical trial design with a focus on enrollment based upon molecular diagnostics.

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