The predictive value of longitudinal neuropsychologic assessment in the early detection of brain tumor recurrence

Abstract

Background: Neuropsychologic tests are widely used to predict the course of progressive neurologic diseases, and recent research has demonstrated the specificity of cognitive measures, even in relatively diffuse diseases. However, the cognitive effects of brain tumors of similar histology and location are known to be highly variable. The authors used the specificity of cognitive function principle to compare two models for the early detection of low-grade brain tumor recurrence prior to detection with clinically scheduled neuroimaging.

Methods: To test the feasibility of these prediction models, 34 patients with supratentorial, low-grade brain tumors prospectively were administered serial comprehensive neuropsychologic examinations; 11 patients developed recurrent tumors during the series and 23 patients did not. A general model based on tests sensitive to malignancy and white matter disease was compared with a tumor-specific model based on indices related to each patient's tumor locus. A Cox proportional hazards model was used to identify the predictor variables that significantly changed immediately prior to recurrence.

Results: Only the tumor-specific model achieved statistical significance (P < 0.02). A tumor-specific index decline of 1 standard deviation indicated a 5-fold increase in the probability of tumor recurrence.

Conclusions: Although this method needs to be tested with more frequent and regular observations and with a larger sample, these results provide evidence of the feasibility of the subject-specific model as a predictor of recurrence. The evidence of the predictive value of a tumor-specific model is consistent with studies that identify only limited, brain structure-specific cognitive decline from broad neuropsychologic batteries.