A patient currently considering epilepsy surgery receives counseling about his/her expected chances of seizure-freedom based on generic overall rates of success in large surgical cohorts. Answering the question of how ?a patient like me? will do after surgery essentially depends on the physician's interpretation of complex pre-surgical testing: in fact, there is no objective, reproducible, and validated method to comprehensively combine the results of the pre-surgical work-up into an individualized outcome prediction. This uncertainty delays the initiation of surgical work-ups in patients who may benefit from epilepsy surgery, and may lead to redundant, risky, and futile testing in others who may actually not be good surgical candidates. This is a multi- center project building on an already developed statistical model, adding information from the fundamental components of any pre-surgical evaluation, including EEG, brain imaging, and clinical characteristics to develop an enhanced online tool called the ?Epilepsy Surgery Nomogram? (ESN) allowing a tailored outcome prediction. Using the ESN, the physician treating a patient's epilepsy will be better able to assess the chances of seizure-freedom following epilepsy surgery, and will have a tool to assist decision-making by providing personalized and customized counseling. The goal will be to improve the care of patients with epilepsy by:1)- identifying surgical candidates earlier, and 2)- identifying complex cases needing a dedicated comprehensive epilepsy center more efficiently.

Public Health Relevance

Epilepsy surgery is the treatment of choice for drug-resistant focal epilepsy, but currently remains underutilized due to multiple factors, including an inability to predict individualized outcomes. Although multiple isolated seizure outcome predictors have been identified, the ability to synthesize a wealth of pre-surgical testing data into an individualized and comprehensive outcome prediction remains essentially subjective. We recently published an epilepsy surgery nomogram or ESN (statistical tool) developed and validated on a retrospective cohort of close to 1,500 patients allowing the synthesis of six clinical characteristics to predict seizure-freedom at two and five years after resective epilepsy surgery. In this grant application, we will enhance this nomogram by adding data from the main pillars of a presurgical evaluation: electroencephalography (EEG), magnetic resonance imaging (MRI), and positron emission tomography (PET). We will develop and compare different versions of the ?enhanced? nomogram: one version that relies on easily ascertainable, qualitatively determined datapoints (qualitative ESN) and other versions that use sophisticated quantitative measures obtained from post-processing of the EEG, MRI, surgical pathology, genetics, and PET (quantitative ESN). The ESN will be developed from a retrospective cohort of 450 patients from Cleveland Clinic, Mayo Clinic, and University of Campinas, and prospectively validated in a cohort of 250 patients from the same centers. When completed, this project will generate the first objective, validated, user-friendly, and scalable tool to predict individualized postoperative seizure outcomes. Achieving this goal will improve individual patient counseling and benefit public health by providing an objective tool to stratify disease severity by ?expected outcomes?, helping with streamlining care and resource allocation.

National Institute of Health (NIH)
National Institute of Neurological Disorders and Stroke (NINDS)
Research Project (R01)
Project #
Application #
Study Section
Acute Neural Injury and Epilepsy Study Section (ANIE)
Program Officer
Whittemore, Vicky R
Project Start
Project End
Budget Start
Budget End
Support Year
Fiscal Year
Total Cost
Indirect Cost
Cleveland Clinic Lerner
Internal Medicine/Medicine
Schools of Medicine
United States
Zip Code