Leptomeningeal dissemination at diagnosis of pediatric low-gradeneuroepithelial tumors
Bibliographic record
Abstract
The goal of this study was to describe the demographic, histologic, and prognostic features of children with low-grade neuroepithelial tumors (LGN) of the CNS presenting with leptomeningeal metastases (LM) at diagnosis. We identified 528 newly diagnosed LGN children, 13 (3%) of whom had LM at diagnosis. LM was defined by neuroimaging, clinical evidence, and/or biopsy. The charts were reviewed and patients contacted to validate the demographic data, treatment, and clinical status. The distribution of LM patients by primary tumor site was diencephalon, 5; cerebrum, 2; spinal cord, 3; brainstem, 2; and cerebellum, 1. Six of 8 patients with LM had durable objective responses to chemotherapy. The 5-year progression-free survival of patients with LM at diagnosis was 17%, compared to 85% (95% CI, 80%-91%) for those with localized LGN who had a gross total resection and 51% (95% CI, 44%-52%) for those with localized LGN who had less aggressive surgery ( P < 0.0001). Only 1 of these 13 LM patients died. The 5-year overall survival of the localized LGN group with a gross total resection was 97% (95% CI, 92%-99.9%), and that of the localized LGN group with less aggressive surgery was 88% (95% CI, 84%-95%) ( P = 0.004). The 3% frequency of LM at diagnosis is likely an underestimate since patients with newly diagnosed LGN were not routinely staged. We suggest that staging be considered in the following circumstances: diencephalic primary site, unexplained hydrocephalus, clinical features suggestive of LM, and before adjuvant therapy is initiated. The prognosis for children with LM at diagnosis is favorable, and its identification alters therapeutic strategies.
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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 | 0.003 |
| 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 | 0.001 |
| 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".