19 SURVIVAL AND RECURRENCE OUTCOMES FOR PRIMARY MENINGEAL MELANOCYTIC NEOPLASMS OF THE CENTRAL NERVOUS SYSTEM IN A MULTICENTER COHORT
Bibliographic record
Abstract
Abstract BACKGROUND Primary melanocytic neoplasms of the central nervous system (PMN-CNS) are rare lesions of variable aggressiveness originating from leptomeningeal melanocytes. They present as either circumscribed or diffuse lesions within the CNS. Given the limited number of reported cases, survival and recurrence outcomes are poorly understood. METHODS A retrospective chart review of all local adult (≥18 years) cases of PMN-CNS across four centres in Canada, the United States and Germany (1993-present). RESULTS Forty-eight cases were identified, with median age at diagnosis of 58 years (IQR: 38-68), 52% female. Tumour locations included cerebrum (30, 63%), spine (10, 21%), multifocal (6, 13%) and diffuse (1, 2%). Twelve (25%) tumours had confirmed GNAQ/GNA11, five (10%) NRAS, two (4%) BRAF V600E and one (2%) BRAF V600K mutations. BAP1 deletions were identified in two (4%) cases. Operative outcomes were: gross total resection (22, 46%), subtotal resection (18, 38%) and biopsy-only (5, 10%). Surgery was followed by adjuvant radiotherapy in 31 (65%) cases and adjuvant chemotherapy and/or immunotherapy in 26 (54%) cases, with various combinations of nivolumab/ipilimumab, pembrolizumab, temozolomide, dabrafenib, trametinib, encorafenib and binimetinib. Radiographic recurrence was observed in 24 (50%) cases at a median of 14 (95% CI: 11, —) months postoperatively. Median overall survival time was 26 months (95% CI: 18, —). CONCLUSIONS There is substantial heterogeneity in the molecular and clinical characteristics of PMN-CNS. As the largest multicenter cohort study of this tumour class, our findings will help to define the natural history of the disease, assist in prognostication and guide treatment.
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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 | 0.001 | 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".