Health-related quality of life and psychological functioning in patients with primary malignant brain tumors: a systematic review of clinical, demographic and mental health factors
Bibliographic record
Abstract
BACKGROUND: The impact of primary malignant brain tumors on patient quality of life and psychological functioning is poorly understood, limiting the development of an evidence base for supportive interventions. We conducted a thorough systematic review and quality appraisal of the relevant literature to identify correlates of health-related quality of life (HRQoL) and psychological functioning (depression, anxiety and distress) in adults with primary malignant brain tumors. METHOD: = 2407). Methodological quality of included studies was assessed using an adapted version of the Newcastle-Ottawa Scale. RESULTS: The overall methodological quality of the literature was moderate. Factors relating consistently with HRQoL and/or psychological functioning were cognitive impairment, corticosteroid use, current or previous mental health difficulties, fatigue, functional impairment, performance status and motor impairment. CONCLUSIONS: Practitioners should remain alert to the presence of these factors as they may indicate patients at greater risk of poor HRQoL and psychological functioning. Attention should be directed towards improving patients' psychological functioning and maximizing functional independence to promote HRQoL. We outline several areas of future research with emphasis on improved methodological rigor.
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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 | 0.005 | 0.025 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.006 |
| Bibliometrics | 0.007 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".