• World Neurosurg · May 2021

    Identifying Factors Associated with the Growth of Vestibular Schwannomas: a Systematic Review.

    • Helen Whitley, Narmatha T Benedict, Stephane Tringali, Nihal T Gurusinghe, Gareth Roberts, Maxime Fieux, and Andrew F Alalade.
    • First Faculty of Medicine, Charles University in Prague, Nove Mesto, Czech Republic.
    • World Neurosurg. 2021 May 1; 149: e766-e779.

    BackgroundSurveillance imaging is a valid management option for selected vestibular schwannomas (VS). An ideal protocol for radiologic monitoring would highlight growth-related risk factors and tailor management accordingly. This study aims to identify variables associated with the growth of sporadic VS to enhance surveillance imaging, enable early intervention, and optimize outcomes.MethodsThe review was conducted according to the PRISMA guidelines. A systematic review of 5 databases (PubMed, Ovid, Cochrane Library, Web of Science, and Google Scholar) was performed to identify negative and positive growth predictors of sporadic vestibular schwannomas. The search was limited to studies reported between January 2015 and January 2020. We conducted an individual patient data meta-analysis using a 1-stage multivariate mixed-effect logistic regression model.ResultsA total of 437 studies were identified, of which 25 met our criteria for full-text analysis. Articles that measured VS with comparable methods were determined eligible for meta-analysis inclusion. The selected articles were highly heterogeneous in their use of grading scales and assessment of tumor size. Our review showed that size at diagnosis (odds ratio, 1.15; 95% confidence interval, 1.11-1.18; P < 0.0001) and intracanalicular localization (odds ratio, 0.49; 95% confidence interval, 0.26-0.90; P = 0.023) were associated with VS growth.ConclusionsThe factors most frequently reported as being associated with growth within the literature were size of VS at diagnosis and localization of an intracanalicular component. Greater attention should be placed on these criteria within the surveillance imaging algorithm for VS.Copyright © 2021 Elsevier Inc. All rights reserved.

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