What question did this study set out to answer?

The aim is to identify factors affecting glioma-related epilepsy and predictors for controlling seizures after surgery.

February 5, 2026Open Access

Clinical analysis of influencing factors and prognosis of epilepsy associated with glioma

YYYaohua YangHuanggang Central Hospital QMQun MuHuanggang Central Hospital JWJinglong WangHuanggang Central Hospital

Key Points

The aim is to identify factors affecting glioma-related epilepsy and predictors for controlling seizures after surgery.
Conducted a retrospective analysis on 159 glioma patients from January 2022 to July 2023.
Patients categorized into GRE (81) and non-epilepsy groups (78) based on seizure history.
Used univariate and multivariate logistic regression to assess clinical and imaging variables.
Key risk factors for GRE included larger tumor size, cystic degeneration, and severe peritumoral edema.
Low-grade gliomas were associated with higher epilepsy incidence, while high-grade tumors showed reduced risk.
Molecular markers linked to GRE included low Ki-67 expression and glial fibrillary acidic protein positivity.

Abstract

This study aimed to identify risk factors associated with glioma-related epilepsy (GRE) and to explore predictors of postoperative seizure control through analysis of imaging, pathological, and molecular profiles. A retrospective analysis was conducted on 159 patients diagnosed with glioma via surgery or biopsy in the neurosurgery department of our hospital between January 2022 and July 2023. Based on preoperative seizure history, patients were categorized into a GRE group (n = 81) and a non-epilepsy group (n = 78). The GRE group was further stratified into well-controlled and poorly-controlled subgroups according to postoperative seizure outcomes. Univariate and multivariate logistic regression analyses were applied to assess the influence of clinical, imaging, pathological, and immunohistochemical variables on both seizure incidence and postoperative control. Key risk factors for GRE included larger tumor size (OR = 1.45, P = .02), cystic degeneration (OR = 2.10, P = .01), severe peritumoral edema (OR = 2.50, P = .01), calcification (OR = 1.65, P = .04), and hippocampal involvement (OR = 1.78, P = .03). Low-grade gliomas (WHO grade I) were associated with a higher incidence of epilepsy (OR = 2.20, P = .001), whereas high-grade (WHO grade III) tumors correlated with a reduced risk (OR = 0.50, P = .01). Molecular markers such as low Ki-67 expression (OR = 1.75, P = .03) and glial fibrillary acidic protein positivity (OR = 1.80, P = .04) were also linked to GRE. Postoperative seizure control was adversely influenced by tumor size (OR = 1.30, 95% CI: 1.05–1.75, P = .04), lower karnofsky performance status (OR = 0.88, 95% CI: 0.80–0.95, P = .02), poor preoperative seizure control (OR = 2.75, 95% CI: 1.80–4.50, P = .01), severe edema (OR = 2.50, 95% CI: 1.50–4.15, P = .01), and higher seizure frequency (OR = 1.55, 95% CI: 1.20–2.10, P = .01). These results highlight the relevance of specific tumor and clinical features in predicting both the onset and postoperative management of epilepsy in glioma patients. This study confirms that tumor size, pathological subtype, and imaging characteristics are significantly associated with the development of epilepsy and postoperative outcomes in glioma patients. Recognition of these factors aids in formulating personalized treatment and management approaches to enhance prognosis and quality of life.

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