Resective surgery is the most effective treatment option for patients with pharmacoresistant epilepsy, but surgical resection is not without risk. Up to 44% of patients demonstrate postoperative cognitive declines, most notably in memory and language, and up to 54% report postoperative problems with depression and/or anxiety. Existing models for predicting neuropsychological outcomes are inadequate and not optimized for use in individual patients. Further, no current models account for genetic biomarkers known to affect cognition in epilepsy. This makes it very difficult for clinicians to accurately counsel a given patient about his or her individual risk for cognitive and/or mood decline and likely changes in quality of life following this elective surgical procedure. Our center has demonstrated the utility of an Epilepsy Surgery Nomogram (ESN) in predicting seizure outcomes following epilepsy surgery. We are currently looking to improve the ESN by adding clinical, EEG, imaging, histopathological and genetic patient characteristics. Our preliminary data suggest that nomograms also have utility in predicting postoperative cognitive outcomes. So, in this project, we will expand our work to add a neuropsychological dimension. Specifically, we will develop and validate nomograms to predict neuropsychological outcomes at 6 months following temporal lobe epilepsy surgery considering only clinical variables as candidate predictors. We will then develop and validate nomograms to predict neuropsychological outcomes at 6 months following temporal lobe epilepsy surgery considering clinical and genetic variables as candidate predictors. These new tools will undoubtedly influence future clinical decision-making by helping to predict individual and comprehensive patient outcomes following an elective surgical procedure.
Resective surgery is the most effective treatment option for patients with pharmacoresistant epilepsy, but up to 44% of patients demonstrate postoperative cognitive declines, most notably in memory and language, and up to 54% report postoperative problems with depression and/or anxiety. Existing models for predicting neuropsychological outcomes are inadequate and not optimized for use in individual patients. In this project, we will expand our current work aimed at predicting postoperative seizure outcomes to add a neuropsychological dimension and develop a tool to also predict neuropsychological outcomes following temporal lobe resection.
