Survival after Stereotactic Radiosurgery in the Era of Targeted Therapy: Number of Metastases No Longer Matters
Bibliographic record
Abstract
Randomised control trial data support the use of stereotactic radiosurgery (SRS) in up to 4 brain metastases (BMs), with non-randomised prospective data complementing this for up to 10 BMs. There is debate in the neuro-oncology community as to the appropriateness of SRS in patients with >10 BMs. We present data from a large single-centre cohort, reporting survival in those with >10 BMs and in a >20 BMs subgroup. A total of 1181 patients receiving SRS for BMs were included. Data were collected prospectively from the time of SRS referral. Kaplan–Meier graphs and logrank tests were used to compare survival between groups. Multivariate analysis was performed using the Cox proportional hazards model to account for differences in group characteristics. Median survival with 1 BM (n = 379), 2–4 BMs (n = 438), 5–10 BMs (n = 236), and >10 BMs (n = 128) was 12.49, 10.22, 10.68, and 10.09 months, respectively. Using 2–4 BMs as the reference group, survival was not significantly different in those with >10 BMs in either our univariable (p = 0.6882) or multivariable analysis (p = 0.0564). In our subgroup analyses, median survival for those with >20 BMs was comparable to those with 2–4 BMs (10.09 vs. 10.22 months, p = 0.3558). This study contributes a large dataset to the existing literature on SRS for those with multi-metastases and supports growing evidence that those with >10 BMs should be considered for SRS.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".