A prospective study of effects of whole brain radiotherapy on cognitive function and quality of life in patients with brain metastases from lung cancer
Bibliographic record
Abstract
Objective To evaluate the effects of whole brain radiotherapy (WBRT) on cognitive function and quality of life (QOL) in patients with brain metastases from lung cancer. Methods A total of 41 patients with brain metastases from lung cancer who were admitted to our hospital and treated with WBRT in 2015 were enrolled as subjects. Montreal Cognitive Assessment (MoCA) and Mini-Mental State Examination (MMSE) were used for cognitive evaluation. The Alzheimer′s Disease Cooperative Study Activity of Daily Living (ADCS-ADL) scale was used for evaluation of QOL. Comparison of cognitive function and QOL before and after WBRT was made by the independent sample t-test. Results The incidence rates of cognitive dysfunction based on MoCA and MMSE were 96.55% and 48.28% before WBRT, and 94.29% and 31.43% after WBRT, respectively. There were no significant changes in MoCA score, MMSE score, or ADCS-ADL score after WBRT (18.24±0.95 vs. 19.37±0.70, P=0.341; 23.51±0.88 vs. 24.54±0.71, P=0.375; 57.44±2.59 vs. 59.37±2.27, P=0.583). Conclusions WBRT has no significant impacts on cognitive function and QOL in patients with brain metastases from lung cancer. MoCA is more sensitive than MMSE in detection of cognitive dysfunction in patients with brain metastases. Key words: Brain metastases, lung neoplasms/whole brain radiotherapy; Cognitive function; Quality of life; Scale
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".