Predicting the stability and growth of acoustic neuromas.

Abstract

Acoustic neuroma (AN) growth can be predicted using information gathered at the time the AN is initially diagnosed. Knowledge of AN growth is essential for treatment planning. Previous studies have not been able to identify predictors of AN growth. A multivariate statistical analysis was carried out using two independent sets of secondary data from the natural histories of ANs. Logit, probit, and censored regression techniques were used to test alternative hypotheses of AN growth between the initial and second measurements, as well as between subsequent measurements. In one data set, AN growth between the first and second measurements varied significantly and inversely with age. It was much greater if the AN was on the left side and if there were more symptoms. It did not depend on initial tumor size or the measurement interval. In the other data set, AN growth was also greater for left-sided tumors and depended on symptoms. However, it varied inversely with tumor size and directly with the measurement interval. There was also some evidence that tumors that were more stable between the initial two measurements were more likely to remain stable between the second and third measurements. However, this did not apply to AN growth between the third and fourth measurements. AN growth is predictable but the prediction model is not apparently independent of the policy for selecting ANs for conservative management.