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Predictive factors for complications after surgical treatment for schwannomas of the extremities
Toshihide Hirai1, Hiroshi Kobayashi2, Toru Akiyama3
1Department of Orthopaedic Surgery, Faculty of Medicine, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo, 113-8655, Japan.
Background:
Schwannomas are well-encapsulated, benign neoplasms, and enucleation is a standard operation procedure. The incidence of neurological complications after surgical treatment for schwannomas of the extremities varies, and there is no consensus concerning predictive factors for complications. The aim of this study was to elucidate predictive factors for complications after surgical treatment of schwannomas that develop in the major nerves of the extremities.
Methods:
A total of 139 patients with 141 schwannomas arising in major nerves were retrospectively analyzed. Data regarding preoperative clinical features, the postoperative neurological complications, and clinical course of complications, with a median follow-up period of 2 months (range, 0.5-96), were obtained. Predictive factors for complications were statistically analyzed.
Results:
Postoperative complications occurred in 49 lesions (34.8%), including 42 with sensory disturbance and 8 with motor weakness. In univariate analysis, older age, tumors originating from the upper extremity, and major motor nerve involvement were associated with a higher complication rate (p = 0.03, p = 0.003, and p = 0.001, respectively). In multivariate analysis, major motor nerve involvement was an independent predictive factor for postoperative complications (p = 0.03). Almost all complications gradually improved, but 6 out of 8 patients with motor weakness did not show full recovery at the final follow-up.
Conclusions:
Schwannomas originating from major motor nerves can lead to a higher risk for postoperative complications.
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Prediction Intervals
However, the point estimate is most likely not the exact value of the population parameter, but close to it. After calculating point estimates, we construct interval estimates, called confidence intervals or prediction intervals. This prediction interval comprises a range of values unlike the point estimate and is a better predictor of the observed sample value, y.

