Bibliographic record
Abstract
BACKGROUND: The morbidity and mortality associated with metastatic disease to brain make this problem a formidable challenge faced by health care providers and caregivers. The aim of this review is to summarize management for patients with brain metastases with a particular focus on symptom management. METHODS: A systematic review of the literature was performed. Outcomes of interest included survival, brain control (local in field and whole brain). In particular, symptom control (quality of life, neurological function and neurocognition) was examined. RESULTS: Steroids provide relief of symptoms due to intra-cerebral edema. The steroid of choice is dexamethasone. Anti-seizure medications should not be given as prophylaxis but instead be given for treatment of seizures. Depending on patient, tumour and treatment factors, management for brain metastases range from optimal supportive care including the use of steroids, whole brain radiotherapy (WBRT), radiosurgery, surgery alone or in combination. Surgery or radiosurgery improves survival for selected patients with single brain metastasis as compared to WBRT alone. Ongoing research topics include focal postoperative cavity radiation, focal fractionated regimens, molecular targeted therapies, chemoprevention of brain metastases and neurocognitive protection (such as neuro-protective drugs and radiation techniques such as hippocampal sparing). CONCLUSIONS: The management of brain metastases has evolved over the decades. Other than survival and brain control (local in-field and whole brain), the outcomes of quality of life and neurocognition are becoming increasingly important.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".