Local control and survival after stereotactic radiosurgery for colorectal cancer brain metastases: an international multicenter analysis
Bibliographic record
Abstract
OBJECTIVE: The goal of this study was to characterize local tumor control (LC), overall survival (OS), and safety of stereotactic radiosurgery for colorectal brain metastasis (CRBM). METHODS: Ten international institutions participating in the International Radiosurgery Research Foundation provided data for this retrospective case series. This study included 187 patients with CRBM (281 tumors), with a median age of 62 years and 56.7% being male. Most patients (53.5%) had solitary tumors, although 10.7% had > 5 tumors. The median tumor volume was 2.7 cm3 (IQR 0.22-8.1 cm3), and the median margin dose was 20 Gy (IQR 18-22 Gy). RESULTS: The 3-year LC and OS rates were 72% and 20%, respectively. Symptomatic adverse radiation effects occurred in 1.6% of patients. In the multivariate analysis, age > 65 years and tumor volume > 4.0 cm3 were significant predictors of tumor progression (hazard ratio [HR] 2.6, 95% CI 1.4-4.9; p = 0.003 and HR 3.4, 95% CI 1.7-6.9; p < 0.001, respectively). Better performance status (Karnofsky Performance Scale score > 80) was associated with a reduced risk of tumor progression (HR 0.38, 95% CI 0.19-0.73; p = 0.004). Patient age > 62 years (HR 1.6, 95% CI 1.1-2.3; p = 0.03) and the presence of active extracranial disease (HR 1.7, 95% CI 1.1-2.4; p = 0.009) were significantly associated with worse OS. CONCLUSIONS: Stereotactic radiosurgery offers a high LC rate and a low rate of symptomatic adverse radiation effects for the majority of CRBMs. The OS and LC favored younger patients with high functional performance scores and inactive extracranial disease.
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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 | 0.001 |
| 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) | 0.001 | 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".