A newly developed scoring system from researchers at Rutgers Health and other institutions could help clinicians predict which patients with epilepsy are most likely to achieve seizure freedom following minimally invasive surgery. The model aims to provide clearer guidance for patients considering surgical treatment for drug-resistant epilepsy, potentially increasing the use of these surgical options.
Published in the Annals of Clinical and Translational Neurology, the study introduces a predictive model specifically designed for patients undergoing stereotactic laser amygdalohippocampotomy (SLAH). This procedure uses a laser to precisely target and disable small, seizure-causing areas in the brain’s temporal lobe. The model relies on clinical data from 101 patients who had undergone the SLAH procedure and examines eight clinical factors, such as MRI findings and a history of febrile seizures, to create a scoring system that can predict outcomes.
What makes this model unique is its simplicity and predictive strength. Instead of employing complex statistical methods, researchers developed an ordinal scoring system, with one point assigned for each of the eight positive clinical factors. This straightforward approach proved more effective than models based solely on MRI data or more intricate statistical analyses, offering clinicians a practical tool for assessing a patient's surgical prognosis. Patients who scored 6 or higher on the 8-point scale were found to have a 70% to 80% chance of achieving seizure freedom, which is comparable to outcomes seen with more invasive surgical methods.
Expanding Access to Personalized Epilepsy Care
This scoring system may significantly impact the way epilepsy surgery is considered, especially for patients hesitant about undergoing invasive procedures. Surgery for epilepsy is often underutilized, partially due to difficulties in predicting outcomes and patient concerns about potential side effects. SLAH, as a less invasive option, becomes more appealing when patients can receive clearer information on their likelihood of success.
Another important finding is that even patients who lack visible brain scars on MRI—previously a major factor in determining eligibility for surgery—may still be good candidates if they have other favorable clinical indicators. This development could broaden the pool of patients eligible for surgery, leading to improved access and outcomes for those with drug-resistant epilepsy.
While the model still requires further validation with larger patient datasets, this research represents an important step in personalizing epilepsy treatment. Future iterations of the scoring system might incorporate more detailed clinical data, such as seizure characteristics and neuropsychological profiles, to offer even more precise predictions. Ultimately, this model may help more patients find effective relief through minimally invasive surgical interventions.