23 Long-term survivors of brain metastases
Bibliographic record
Abstract
Purpose: We identified key clinicopathologic features of brain metastasis (BM) patients who are long-term survivors (LTS). Methods: We screened a prospective database of 1892 patients (treated 2006-2017), identified 92 (5%) who lived > 3 years following BM diagnosis, and performed per patient analyses. Results: Median age at diagnosis of BM was 57 years (range 19-77), 77% were women. The most common tumors were lung (50%), breast (26%), thyroid (7%) and skin (5%). 42% had tumors with drug-targetable oncoproteins (e.g. EGFR mutant) and 15% expressed hormonal receptors. ECOG was <2 in 70%. 47% had stage IV disease at diagnosis (75% with brain as the first site). 55% had controlled extracranial disease at the time of BM diagnosis. Median BM diameter was 1.5 cm (range 0.2-7) and 62% had a single lesion. Treatment was with surgery, radiosurgery, whole brain radiation (WBRT), or systemic therapy alone in 38%, 62%, 52%, and 4%, respectively. 53% received targeted- or immuno-therapy. Median follow up was 63 months (range 36-113). 61% failed intracranially at a median 24 months (range 1-99). 5 and 10- year survival (from BM diagnosis) was 82%, and 34%, respectively. Neither upfront WBRT nor other variables tested correlated with improved survival. In patients who died, an MRI was available within 3 months from death in 57%; of those 55% had no active intracranial disease, suggesting that the majority of deaths were non-neurologic. Conclusion: In general, LTS of BM had a limited number of BM, inactive extracranial disease, and drug targetable mutations.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.003 | 0.001 |
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".