28 A systematic review in quality of life of patients with meningiomas: Effort towards developing a disease-specific questionnaire
Bibliographic record
Abstract
BACKGROUND: Meningiomas are the most common primary benign brain tumors in adults. Given the extended life expectancy of most meningiomas, consideration of quality of life (QOL) is important when selecting the optimal management strategy. There is currently a dearth of meningioma-specific QOL tools in the literature. OBJECTIVE: In this systematic review, we analyze the prevailing themes and propose toward building a meningioma-specific QOL assessment tool. METHODS: A systematic search was conducted, and only original studies based on adult patients were considered. QOL tools used in the various studies were analyzed for identification of prevailing themes in the qualitative analysis. The quality of the studies was also assessed. RESULTS: Sixteen articles met all inclusion criteria. Fifteen different QOL assessment tools assessed social and physical functioning, psychological, and emotional well-being. Patient perceptions and support networks had a major impact on QOL scores. Surgery negatively affected social functioning in younger patients, while radiation therapy had a variable impact. Any intervention appeared to have a greater negative impact on physical functioning compared to observation. CONCLUSION: Younger patients with meningiomas appear to be more vulnerable within social and physical functioning domains. All of these findings must be interpreted with great caution due to great clinical heterogeneity, limited generalizability, and risk of bias. For meningioma patients, the ideal QOL questionnaire would present outcomes that can be easily measured, presented, and compared across studies. Existing scales can be the foundation upon which a comprehensive, standard, and simple meningioma-specific survey can be prospectively developed and validated.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.029 | 0.086 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.010 |
| Bibliometrics | 0.017 | 0.015 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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 source (direct Gemma or distilled Codex), 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".