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

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 lack...

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Detalles Bibliográficos
Autores principales: Brar, Karanbir, Hachem, Laureen D., Badhiwala, Jetan H., Mau, Christine, Zacharia, Brad E., de Moraes, Fabio Ynoe, Pirouzmand, Farhad, Mansouri, Alireza
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7560299/
https://www.ncbi.nlm.nih.gov/pubmed/33117714
http://dx.doi.org/10.3389/fonc.2020.575658
Descripción
Sumario: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.