2025 American Academy of Neurology Abstract Website

Shatha Alqurashi¹, Toka Banjar¹, Feras Alharbi¹, Ahmed Alkhiri¹, Manar Betar¹, Aisha Halawani², Hani Mufti³, Mohamed Eldigire⁴, Danya Aljafari⁵, Seraj Makkawi¹
¹College of Medicine, King Saud Bin Abdulaziz University for Health Sciences, Jeddah, Saudi Arabia, ²Department of Medical Imaging, Ministry of the National Guard-Health Affairs, Jeddah 22384, Saudi Arabia, ³Division of Cardiac Surgery, Department of Cardiac Sciences, King Faisal Cardiac Center, King Abdulaziz Medical City, Ministry of National Guard Health Affairs, Jeddah, Saudi Arabia, ⁴College of Basic Sciences and Health Professions, King Saud bin Abdulaziz University for Health Sciences, Jeddah, Saudi Arabia, ⁵Neuroscience Department, King Faisal Specialist Hospital and Research Center, Jeddah, Saudi Arabia

Objective:

This study was conducted to achieve the following: (1) to determine the incidence of seizure in patients with brain metastases (BM), (2) to identify risk factors of seizures according to primary tumor type, BM lesion location, and BM radiographic features, treatment administered post-diagnosis of BM, and (3) to identify patients with high seizure risk who might benefit from prophylactic antiseizure medications.

Background:

Limited data exists evaluating the incidence and risk factors for seizures in patients with brain metastases (BM). This study investigated seizure incidence patterns in relation to primary cancer type, metastasis characteristics, and clinical variables. Additionally, a predictive model was developed to identify patients with elevated seizure risk.

Design/Methods:

A single-center retrospective analysis was conducted at King Abdulaziz Medical City, Saudi Arabia, studying patients with BM between July 2016 and January 2023. Univariate and multivariate regression analyses evaluated potential risk factors, and a predictive model was developed. The model’s performance was evaluated using the Under the Receiver Operator Curve (AUC-ROC), Akaike's Information Criterion (AIC), and Bayesian information criterion (BIC).

Results:

Among 272 patients, epilepsy was diagnosed in 80 (29.4%). Univariate analysis showed female sex (OR 2.4 [95% CI, 1.29-4.47],p<0.005) and cortical involvement (OR 22.39 [95% CI, 8.93- 56.13],p<0.001) significantly increased seizure risk. Multivariate analysis identified female sex (OR 2.28 [95% CI, 1.14-4.72],p<0.022), cortical lesions (OR 22.19 [95% CI, 9.42-61.7],p<0.001), and leptomeningeal metastases (OR 8.64 [95% CI, 3.45-24.86],p<0.001) as significant predictors. The developed predictive model assigned scores based on these factors, with scores exceeding 20 indicating 40% increased seizure risk (observed risk 49%). The model achieved an AUC-ROC of 80.51%.

Conclusions:

Female sex, cortical involvement, and leptomeningeal metastases were identified as significant seizure predictors in BM patients. The derived model can help identify high-risk patients potentially benefiting from prophylactic anti-seizure medications. Further validation in larger cohorts is needed.