Factors correlating with survival following adjuvant or definitive radiosurgery for large brain metastases
Bibliographic record
Abstract
BACKGROUND: We sought to identify variates correlating with overall survival (OS) in patients treated with surgery (S) plus adjuvant stereotactic radiosurgery (SRS) versus definitive SRS for large (>4 cc) brain metastases (BrM). METHODS: We used univariate (UVA) and multivariate analyses (MVA) to identify survival correlates among eligible patients identified from a prospective registry and compared definitive SRS to S+ adjuvant SRS cohorts using propensity score-matched analysis (PSMA). Secondary outcomes were measured using the cumulative incidence (CI) method. RESULTS: We identified 364 patients; 127 and 237 were treated with S+SRS and definitive SRS, respectively. On UVA, SRS alone [HR1.73 (1.35,2.22) P < .001), BrM quantity [HR 1.13 (1.06-1.22) (P < .001)]; performance status (PS) [HR 2.78 (1.73-4.46) (P < .001)]; extracranial disease (ECD) [HR 1.82 (1.37,2.40) (P < .001)]; and receipt of systemic treatment after BrM therapy, [HR 0.58 (0.46-073) (P < .001)] correlated with OS. On MVA, SRS alone [HR 1.81 (1.19,2.74) (P < .0054)], SRS target volume [HR 1.03 (1.01,1.06) (P < .0042)], and receipt of systemic treatment [HR 0.68 (0.50,0.93) (P < .015)] correlated with OS. When PSMA was used to balance ECD, BrM quantity, PS, and SRS target volume, SRS alone remained correlated with worsened OS [HR 1.62 (1.20-2.19) (P = 0.0015)]. CI of local failure requiring resection at 12 months was 3% versus 7% for S+SRS and SRS cohorts, respectively [(HR 2.04 (0.89-4.69) (P = .091)]. CI of pachymeningeal failure at 12 months was 16% versus 0% for S+SRS and SRS. CONCLUSION: SRS target volume, receipt of systemic therapies, and treatment with S+SRS instead of definitive SRS correlated with improved survival in patients with large BrM.
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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 | 0.000 | 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) | 0.001 | 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".