Advancements in predicting outcomes in patients with glioma: a surgical perspective
Peer reviewed, Journal article
Published version
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https://hdl.handle.net/11250/2739252Utgivelsesdato
2020Metadata
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Originalversjon
Expert Review of Anticancer Therapy. 2020, 20 (3), 167-177. 10.1080/14737140.2020.1735367Sammendrag
Introduction: Diffuse glioma is a challenging neurosurgical entity. Although surgery does not provide a cure, it may greatly influence survival, brain function, and quality of life. Surgical treatment is by nature highly personalized and outcome prediction is very complex. To engage and succeed in this balancing act it is important to make best use of the information available to the neurosurgeon.
Areas covered: This narrative review provides an update on advancements in predicting outcomes in patients with glioma that are relevant to neurosurgeons.
Expert opinion: The classical ‘gut feeling’ is notoriously unreliable and better prediction strategies for patients with glioma are warranted. There are numerous tools readily available for the neurosurgeon in predicting tumor biology and survival. Predicting extent of resection, functional outcome, and quality of life remains difficult. Although machine-learning approaches are currently not readily available in daily clinical practice, there are several ongoing efforts with the use of big data sets that are likely to create new prediction models and refine the existing models.