Extent of Resection in Meningioma: Predictive Factors and Clinical Implications. View Full Text


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

2019-12

AUTHORS

Jean-Michel Lemée, Marco V Corniola, Michele Da Broi, Holger Joswig, David Scheie, Karl Schaller, Eirik Helseth, Torstein R Meling

ABSTRACT

Meningiomas present as intracranial extra-axial lesions with dural attachment, which are primarily managed surgically. The extent of resection (EOR) may vary depending on patient- and tumor-related factors. The aim of this study is to identify preoperative predictive factors of EOR and to propose an estimation of the predicted gross total resection (GTR) based of patient- and tumor-characteristics. 1469 patients from a retrospectively (1990 to 2002) and prospectively managed (2003 to 2010) databank of Oslo University Hospital, Norway, totalling 11,414 patient-years of follow-up were included. Patients had a mean age at surgery of 64 ± 20.1 years with a female-to-male ratio was 2.4:1 and a mean KPS of 81.2 ± 12.1. Skull-base meningiomas represented 47% of all cases. WHO grades were I in 92.3%, II in 5.2%, and III in 2.2%. Bone infiltration was described in 18.7% of cases. 39.3% of patients had Simpson I resection, 34.3% had Simpson II, 5.4% had Simpson III, 20.6% had Simpson IV, and 0.5% had Simpson V. The risk factors for incomplete resection were: symptomatic presentation (OR 0.56 [0.43-0.72]), skull-base location (OR 0.79 [0.70-0.88]), and bone invasion (OR 0.85 [0.73-0.99]). Using a recursive partitioning analysis, we propose a classification-tree for the prediction of GTR rate based on preoperatively determinable patient- and tumor characteristics. The identification of preoperative predictors of poor GTR rate may aid clinicians managing meningioma patients. In selected cases were the predicted GTR rate is low, staged treatment with surgical debulking followed by adjuvant therapy may be favored in order to minimize postoperative morbidity and mortality. More... »

PAGES

5944

Identifiers

URI

http://scigraph.springernature.com/pub.10.1038/s41598-019-42451-z

DOI

http://dx.doi.org/10.1038/s41598-019-42451-z

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1113378326

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/30976047


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