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dc.contributor.authorJakola, Asgeir S
dc.contributor.authorSagberg, Lisa Millgård
dc.contributor.authorGulati, Sasha
dc.contributor.authorSolheim, Ole
dc.identifier.citationExpert Review of Anticancer Therapy. 2020, 20 (3), 167-177.en_US
dc.description.abstractIntroduction: 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.en_US
dc.publisherInforma UK Limiteden_US
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 Internasjonal*
dc.titleAdvancements in predicting outcomes in patients with glioma: a surgical perspectiveen_US
dc.typePeer revieweden_US
dc.typeJournal articleen_US
dc.source.journalExpert Review of Anticancer Therapyen_US
dc.description.localcode© 2020 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group. This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives License (, which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited, and is not altered, transformed, or built upon in any way.en_US

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Attribution-NonCommercial-NoDerivatives 4.0 Internasjonal
Except where otherwise noted, this item's license is described as Attribution-NonCommercial-NoDerivatives 4.0 Internasjonal