Clinical practice guideline on the optimal radiotherapeutic management of brain metastases
Bibliographic record
Abstract
BACKGROUND: An evidence-based clinical practice guideline on the optimal radiotherapeutic management of single and multiple brain metastases was developed. METHODS: A systematic review and meta-analysis was performed. The Supportive Care Guidelines Group formulated clinical recommendations based on their interpretation of the evidence. External review of the report by Ontario practitioners was obtained through a mailed survey, and final approval was obtained from Cancer Care Ontario's Practice Guidelines Coordinating Committee (PGCC). RESULTS: One hundred and nine Ontario practitioners responded to the survey (return rate 44%). Ninety-six percent of respondents agreed with the interpretation of the evidence, and 92% agreed that the report should be approved. Minor revisions were made based on feedback from external reviewers and the PGCC. The PGCC approved the final practice guideline report. CONCLUSIONS: For adult patients with a clinical and radiographic diagnosis of brain metastases (single or multiple) we conclude that: surgical excision should be considered for patients with good performance status, minimal or no evidence of extracranial disease, and a surgically accessible single brain metastasis. Postoperative whole brain radiotherapy (WBRT) should be considered to reduce the risk of tumour recurrence for patients who have undergone resection of a single brain metastasis. Radiosurgery boost with WBRT may improve survival in select patients with unresectable single brain metastases. The whole brain should be irradiated for multiple brain metastases. Standard dose-fractionation schedules are 3000 cGy in 10 fractions or 2000 cGy in 5 fractions. Radiosensitizers are not recommended outside research studies. In select patients, radiosurgery may be considered as boost therapy with WBRT to improve local tumour control. Radiosurgery boost may improve survival in select patients. Chemotherapy as primary therapy or chemotherapy with WBRT remains experimental. Supportive care is an option but there is a lack of Level 1 evidence as to which subsets of patients should be managed with supportive care alone. Qualifying statements addressing factors to consider when applying these recommendations are provided in the full report. The rigorous development, external review and approval process has resulted in a practice guideline that is strongly endorsed by Ontario practitioners.
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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 | 0.042 | 0.105 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.006 | 0.010 |
| Bibliometrics | 0.008 | 0.009 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.011 | 0.003 |
| Research integrity | 0.014 | 0.010 |
| Insufficient payload (model declined to judge) | 0.006 | 0.004 |
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".