PTHP-04. Integrated clinical and molecular landscape of 269 disseminated pediatric low-grade glioma
Bibliographic record
Abstract
Abstract Pediatric-type low-grade gliomas (PLGG) are the most common central nervous system (CNS) tumor in children. Many are indolent and have excellent outcomes, however some inexplicably spread throughout the CNS leading to increased morbidity and mortality. Previous studies have been limited by small numbers, inconsistent clinical data, and limited molecular characterization, which highlights the need for a comprehensive study. To better understand this rare and difficult-to-treat entity, as well as the underlying processes driving dissemination in CNS tumors, we assembled a large international cohort (n=269 from 39 sites in 13 countries) of patients with disseminated PLGG with detailed clinical and molecular characterization, including DNA sequencing and methylome profiling. We identified three subgroups of patients based on the temporal and spatial distribution of dissemination—primary disseminated tumors with a dominant mass, secondary disseminated tumors, and diffuse tumors without a dominant mass. We observed a striking enrichment for suprasellar primary location compared to our reference cohort of 1000 non-disseminated PLGG. Tumors with diffuse spread (without a primary tumor mass) and primary/secondary disseminated tumors occurring in infants had the worst clinical outcomes. The genetics overlapped substantially with that of non-disseminated PLGG, suggesting that non-genetic mechanisms are an important contributor to dissemination. While recurrent genetic alterations contributing to dissemination were not present in most cases, a subset of tumors that underwent high-grade transformation did have additional high-risk genetic and/or epigenetic features, indicating the mechanisms driving malignancy and dissemination are profoundly different. Therapeutically, targeted MAPK-pathway inhibition was more effective than conventional chemotherapy as either first or second-line treatment. In sum, this cohort increases our clinical and biological understanding of this rare disease, provides insights for improving patient care, and directs future clinical trials and basic science research.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".