P.109 Increased survival when combining BRAF inhibitors and stereotactic radiosurgery in patients with melanoma brain metastases
Bibliographic record
Abstract
Background: The purpose of the study was to evaluate the impact of BRAF inhibitors on survival outcomes in patients receiving stereotactic radiosurgery (SRS) for melanoma brain metastases. Methods: We prospectively collected treatment outcomes for 80 patients with melanoma brain metastases who underwent SRS. Thirty-five patients harbored the BRAF mutation (BRAF-M) and 45 patients did not (BRAF-WT). Results: The median overall survival from first SRS procedure was 11.2 months if treated with a BRAF inhibitor and 4.5 months for BRAF-WT. Actuarial survival rates for BRAF-M patients on an inhibitor were 54% and 41% at 6 and 12 months after radiosurgery, in contrast to 28% and 19% for BRAF-WT. Overall survival was extended for patients on a BRAF inhibitor if initiated at or after the first SRS. The local control rate did not differ based on BRAF status and was over 90%. Patients with higher KPS, fewer treated metastases, controlled systemic disease, RPA class 1 and BRAF-M patients had extended overall survival. Conclusions: Patients with BRAF-M treated with both SRS and BRAF inhibitors, at or after SRS, have increased overall survival. As patients live longer due to more effective systemic and local therapies, close surveillance and early management of intracranial disease with SRS will become 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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.002 | 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".