P.152 Local control and survival in brain metastases treated with cavity directed gamma knife radiosurgery: a single center retrospective study
Bibliographic record
Abstract
Background: This local study aims to address gaps in understanding factors influencing local control in patients with brain metastases treated with adjuvant Gamma Knife Radiosurgery Methods: A retrospective analysis used a local, prospectively kept Gamma Knife database. Sixty-three patients treated with GK SRS were included. Variables included demographics, tumor characteristics, SRS parameters, and outcomes such as local control, recurrence, survival, and adverse effects. Results: At 12 months, local control was 66.7%, decreasing to 57.1% at 24 months. Distant progression occurred in 58.7%, leptomeningeal disease in 15.9%, and adverse radiation effects in 20.6%. The 12-month survival rate was 63.5%, dropping to 38.1% at 24 months. None of the examined factors significantly influenced local control. Local progression within the first year of treatment was associated with a 5.0-fold increased risk of death at 24 months, while distant intracranial progression showed a 6.0-fold increased risk at 12 months and an 8.2-fold increased risk at 24 months. Conclusions: While the parameters we examined were not linked to local control, intracranial progression significantly impacted survival. This real-world cohort provides valuable insights into the challenges of managing brain metastases. Further work is needed to refine the current treatment strategies for intracranial progression and ultimately improve survival outcomes.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.002 | 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".