Zhang, X.; Wu, W.; Wang, Y.; Lian, X.; Ma, W. Individualized Management of Postoperative Radiotherapy for Patients with Diffuse Low-Grade Gliomas. Preprints2024, 2024081011. https://doi.org/10.20944/preprints202408.1011.v1
APA Style
Zhang, X., Wu, W., Wang, Y., Lian, X., & Ma, W. (2024). Individualized Management of Postoperative Radiotherapy for Patients with Diffuse Low-Grade Gliomas. Preprints. https://doi.org/10.20944/preprints202408.1011.v1
Chicago/Turabian Style
Zhang, X., Xin Lian and Wenbin Ma. 2024 "Individualized Management of Postoperative Radiotherapy for Patients with Diffuse Low-Grade Gliomas" Preprints. https://doi.org/10.20944/preprints202408.1011.v1
Abstract
This review explores the nuanced decision-making surrounding postoperative radiotherapy for diffuse low-grade glioma (DLGG) patients, emphasizing the need for personalized treatment to balance the benefits of tumor control with the risks of long-term side effects. Radiotherapy is a cornerstone of DLGG treatment, offering significant improvements in progression-free survival, but its potential for cognitive decline and vascular lesions necessitates careful consideration of individual patient factors. The review delves into the complexities of radiotherapy timing, revealing that while early radiotherapy enhances progression-free survival, it does not significantly impact overall survival and may lead to earlier onset of cognitive decline. Conversely, delayed radiotherapy may mitigate cognitive decline but may result in shorter progression-free survival and the onset of neurological symptoms. The review advocates for a patient-centered approach, emphasizing the importance of weighing individual risks and benefits, and highlights the potential of artificial intelligence in predicting cognitive decline and the need to revisit previous research findings in light of the 2021 WHO (World Health Organization) classification update, underscoring the evolving nature of DLGG treatment and the ongoing quest for optimal therapeutic strategies.
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
