Cognitive Decline in Glioblastoma (GB) Patients with Different Treatment Modalities and Insights on Untreated Cases
Bibliographic record
Abstract
BACKGROUND: Cognitive decline is common in patients with Glioblastoma (GB), occurring in both treated and untreated cases. It frequently presents as impairments in memory, attention, language, or other cognitive functions. In addition, these cognitive deficits can affect quality of life, functional independence, and overall survival, and they are associated with psychiatric conditions such as anxiety and depression. METHODS: This narrative review evaluates cognitive deficits in GB patients, both with and without treatment. It also explores the impact of tumor features such as size, location, and histology, along with patient characteristics such as age and education, and discusses the effects of standard therapies, such as surgery, chemotherapy, and radiotherapy, on cognitive outcomes. RESULTS: Cognitive impairment in GB is influenced by tumor- and patient-specific factors, as well as treatment modalities. Initially, combination therapies such as surgery, radiotherapy, and chemotherapy may improve cognitive domains by reducing tumor burden, relieving cerebral edema, and reducing mass effects, subsequently bringing indirect effects of improved mental health and mood. While certain treatments like radiotherapy and chemotherapy carry risks of delayed neurotoxicity, studies indicate that, on balance, treated patients generally show better preservation or improvement in cognitive function than those who go untreated. However, excessive treatment aggressiveness and cumulative neurotoxic effects may diminish cognitive benefits. CONCLUSION: Cognitive function is an independent factor in GB, which could affect survival in GB patients, therefore making routine cognitive assessments essential for prognosis, treatment planning, and rehabilitation. Neuroprotective agents, cognitive rehabilitation, and personalized, multidisciplinary strategies can help optimize both survival and cognitive preservation.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".