Growth of untreated vestibular schwannoma: a prospective study

Clinical article

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Small vestibular schwannomas (VSs) are often conservatively managed and treated only upon growth. Growth is usually reported in mm/year, but describing the growth of a 3D structure by a single diameter has been questioned. As a result, VS growth dynamics should be further investigated. In addition, baseline clinical parameters that could predict growth would be helpful. In this prospective study the authors aimed to describe growth dynamics in a cohort of conservatively managed VSs. They also compared different growth models and evaluated the ability of baseline parameters to predict future growth.


Between 2000 and 2006, 178 consecutive patients with unilateral de novo small-sized VSs identified among the Norwegian population of 4.8 million persons were referred to a tertiary care center and were included in a study protocol of conservative management. Tumor size was defined by MR imaging–based volume estimates and was recorded along with clinical data at regular visits. Mixed-effects models were used to analyze the relationships between observations. Three growth models were compared using statistical diagnostic tests: a mm/year–based model, a cm3/year–based model, and a volume doubling time (VDT)-based model. A receiver operating characteristic curve analysis was used to determine a cutoff for the VDT-based model for distinguishing growing and nongrowing tumors.


A mean growth rate corresponding to a VDT of 4.40 years (95% CI 3.49–5.95) was found. Other growth models in this study revealed mean growth rates of 0.66 mm/year (95% CI 0.47–0.86) and 0.19 cm3/year (95% CI 0.12–0.26). Volume doubling time was found to be the most realistic growth model. All baseline variables had p values > 0.09 for predicting growth.


Based on the actual measurements, VDT was the most correct way to describe VS growth. The authors found that a cutoff of 5.22 years provided the best value to distinguish growing from nongrowing tumors. None of the investigated baseline predictors were usable as predictors of growth.

Abbreviations used in this paper:ROC = receiver operating characteristic; VDT = volume doubling time; VS = vestibular schwannoma.

Article Information

Address correspondence to: Jobin K. Varughese, M.D., Institute of Surgical Sciences, University of Bergen, Haukeland University Hospital, N-5021 Bergen, Norway. email:

Please include this information when citing this paper: published online January 20, 2012; DOI: 10.3171/2011.12.JNS111662.

© AANS, except where prohibited by US copyright law.



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    Graphs demonstrating fitted values for 3 growth models: mm/year–based model (A), cm3/year–based model (B), and VDT-based model (C). A growth model is more realistic the more it adheres to the modeling assumptions. The more ideal the growth model, the more the plot type should show a uniform spread for all values. The fan shapes of A and B show that the mm/year–based model supports this requirement poorly and that the cm3/year–based model supports it even worse.

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    Graphs demonstrating 3 growth models: mm/year–based model (A), cm3/year–based model (B), and VDT-based model (C). A growth model is more realistic the more it adheres to the modeling assumptions. The more ideal the growth model, the more the plot type should show a straight line. The cm3/year–based model in B shows the least straight line and thus supports the assumption the worst.

  • View in gallery

    Histogram showing the distribution of VDTs. Note that the smallest tumors show the most rapid VDTs. V = mean volume at the time of diagnosis for the tumors in that respective bar, in cm3.

  • View in gallery

    Graph showing the ROC curve for determining an appropriate VDT cutoff for distinguishing between growth and no growth (as classified by the mm/year–based model). A VDT cutoff of 5.22 years has a sensitivity of 0.81 and a specificity of 0.84.

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    Graph depicting relative changes in tumor volume. The ratio between the final and initial tumor volume for each patient (y axis) is related to the duration of the follow-up (x axis). Dotted lines indicate where a data point would be expected after a certain period if it had a given VDT; this allows us to visually interpret treatment statistics and growth rates along a time axis. Note that the VDT estimates are sensitive to the interval between MR imaging studies, that is, the sampling density. The vertical axis is logarithmic. + = treated tumors; ο = untreated tumors; × = patients lost to follow-up.



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