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.

Download full-text PDF

Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7560299PMC
http://dx.doi.org/10.3389/fonc.2020.575658DOI Listing

Publication Analysis

Top Keywords

management diffuse
8
diffuse low-grade
8
low-grade glioma
4
glioma renaissance
4
renaissance robust
4
robust evidence
4
evidence surgical
4
surgical management
4
low-grade gliomas
4
gliomas dlggs
4

Similar Publications

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!