The role of emerging and investigational therapies for metastatic brain tumors: a systematic review and evidence-based clinical practice guideline of selected topics
Bibliographic record
Abstract
QUESTION: What evidence is available regarding the emerging and investigational therapies for the treatment of metastatic brain tumors? TARGET POPULATION: These recommendations apply to adults with brain metastases. RECOMMENDATIONS: New radiation sensitizers Level 2 A subgroup analysis of a large prospective randomized controlled trial (RCT) suggested a prolongation of time to neurological progression with the early use of motexafin-gadolinium (MGd). Nonetheless this was not borne out in the overall study population and therefore an unequivocal recommendation to use the currently available radiation sensitizers, motexafin-gadolinium and efaproxiral (RSR 13) cannot be provided. Interstitial modalities There is no evidence to support the routine use of new or existing interstitial radiation, interstitial chemotherapy and or other interstitial modalities outside of approved clinical trials. New chemotherapeutic agents Level 2 Treatment of melanoma brain metastases with whole brain radiation therapy and temozolomide is reasonable based on one class II study. Level 3 Depending on individual circumstances there may be patients who benefit from the use of temozolomide or fotemustine in the therapy of their brain metastases. Molecular targeted agents Level 3 The use of epidermal growth factor receptor inhibitors may be of use in the management of brain metastases from non-small cell lung carcinoma.
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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 | 0.014 | 0.042 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.005 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.004 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".