Management of Diffuse Low-Grade Glioma: The Renaissance of Robust Evidence

Karanbir Brar, Laureen D. Hachem, Jetan H. Badhiwala, Christine Mau, Brad Zacharia, Fabio Ynoe de Moraes, Farhad Pirouzmand, Alireza Mansouri

Research output: Contribution to journalArticlepeer-review

Abstract

The surgical management of diffuse low-grade gliomas (DLGGs) has undergone a paradigm shift toward striving for maximal safe resection when feasible. While extensive observational data supports this transition, unbiased evidence in the form of high quality randomized-controlled trials (RCTs) is lacking. Furthermore, despite a high volume of molecular, genetic, and imaging data, the field of neuro-oncology lacks personalized care algorithms for individuals with DLGGs based on a robust foundation of evidence. In this manuscript, we (1) discuss the logistical and philosophical challenges hindering the development of surgical RCTs for DLGGs, (2) highlight the potential impact of well-designed international prospective observational registries, (3) discuss ways in which cutting-edge computational techniques can be harnessed to generate maximal insight from high volumes of multi-faceted data, and (4) outline a comprehensive plan of action that will enable a multi-disciplinary approach to future DLGG management, integrating advances in clinical medicine, basic molecular research and large-scale data mining.

Original languageEnglish (US)
Article number575658
JournalFrontiers in Oncology
Volume10
DOIs
StatePublished - Oct 1 2020

All Science Journal Classification (ASJC) codes

  • Oncology
  • Cancer Research

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