STEREOTACTIC RADIOSURGERY FOR BRAIN METASTASES FROM GASTROINTESTINAL PRIMARIES: ANALYSIS OF OUTCOMES
Bibliographic record
Abstract
Abstract AIMS Brain metastases from gastrointestinal primaries are uncommon with poor reported outcomes following SRS. We evaluated clinical outcomes for patients diagnosed with metastatic brain tumours from a gastrointestinal primary treated with stereotactic radiosurgery (SRS). METHOD A single institutional retrospective review of patients treated with LINAC-based SRS at our institution between 2017 and 2022. Median survival was calculated from the time of SRS. RESULTS A total of 24 patients were treated with primary malignancy locations as follows: 10 colon, 7 rectum and 7 oesophageal. Median survival was 6.4 months for the overall cohort and 4.5 months for colon, 6.1 months for rectum and 14 months for oesophagus. 44% and 14% of patients had undergone surgical resection with colorectal cancer (CRC) and oesophageal cancer respectively. Median survival in CRC patients receiving SRS post-operatively was 6.8 months compared with 11.5 months for patients with non-gastrointestinal primaries. Time from diagnosis of the primary malignancy to diagnosis of brain metastases showed an inverse correlation with survival: 48 months colon, 21 months rectum and 13 months oesophagus. Compared to oesophageal patients, CRC patients were more likely to have extra-cranial disease at the time of SRS (57% vs. 18%). CONCLUSIONS Survival after SRS to brain metastases from gastrointestinal primaries is poor, but we demonstrate important differences in outcome depending on the location of the primary malignancy. Oesophageal cancer patients had the best survival with colon cancer patients having the worst. Although our findings are likely to influenced by patient selection bias, these differences are worthy of further investigation.
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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 | 0.003 |
| 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 | 0.001 | 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".