Patients with primary malignant brain tumors may experience mental health disturbances that can significantly affect their daily life. This study aims to identify risk factors and generate predictive models for postoperative mental health disturbances (PMHDs) in adult glioma patients in accordance with different clinical periods; additionally, survival analyses will be performed.
This longitudinal cohort study included 2,243 adult patients (age at diagnosis ≥ 18 years) with nonrecurrent glioma who were pathologically diagnosed and had undergone initial surgical resection. Six indicators of distress, sadness, fear, irritability, mood and enjoyment of life, ranging from 0-10, were selected to assess PMHDs in glioma patients in the third month after surgery, mainly referring to the M.D. Anderson Symptom Inventory Brain Tumor Module (MDASI-BT). Factor analysis (FA) was applied on these indicators to divide participants into PMHD and control groups based on composite factor scores. Survival analyses were performed, and separate logistic regression models were formulated for preoperative and postoperative factors predicting PMHDs.
A total of 2,243 adult glioma patients were included in this study. Based on factor analysis results, 300 glioma patients had PMHDs in the third postoperative month, and the remaining 1,943 were controls. Candidate predictors for PMHDs in the preoperative model were associated with age, clinical symptoms (intracranial space-occupying lesion, muscle weakness and memory deterioration), and tumor location (corpus callosum, basal ganglia and brainstem), whereas age, clinical symptoms (nausea and memory deterioration), tumor location (basal ganglia and brainstem), hospitalization days, WHO grade 4, postoperative chemotherapy or radiotherapy and postoperative Karnofsky Performance Scale (KPS) served as important factors in the postoperative model. In addition, the median overall survival (OS) time for glioma patients with PMHDs was 19 months, compared to 13 months for glioblastoma, IDH-wild type (GBM) patients with PMHDs.
The risk factors for PMHDs were identified. These findings may provide new insights into predicting the probability of PMHD occurrence in glioma patients in addition to aiding effective early intervention and improving prognosis based on different clinical stages.