THE CLINICAL AND MOLECULAR LANDSCAPE OF GLIOMAS IN ADOLESCENTS AND YOUNG ADULTS
Bibliographic record
Abstract
Abstract Molecular alterations in gliomas in adolescents and young adults (AYA) have not been comprehensively described to date. To determine the impact of mutation, we performed a population based study of gliomas in AYA. METHODS: Patients diagnosed from 2000-2019 with glioma between 15-39.9 years were eligible. Comprehensive molecular analysis was performed. Therapeutic and outcome data was collected. For comparison, analysis included patients aged 0-39.9 years. RESULTS: A total of 876 AYA gliomas were included. Genetic alterations were found in 95% of available tumours. Pediatric-type mutations were found in 33% of AYA tumours. The most common paediatric alterations included BRAF p.V600E (11%) and FGFR alterations (7%) while BRAF fusions (4%), H3 p.K27M (4%) and H3.3 p.G34R (1%) were rare. IDH mutation was found in 57% of tumours. Molecular GBM accounted for 7%. Paediatric-type alterations had different outcomes in AYA than children. Ten-year OS of 100%, 90% and 95% was seen for BRAF fused, BRAF-V600E and FGFR-altered AYA low grade glioma (LGG), compared to 14% and 25% for BRAF- V600E and FGFR-altered high grade glioma (HGG) respectively. BRAF and FGFR mutant tumours had higher proportion of HGG versus LGG in AYA compared to children (OR 2.6, 95% CI 1.2-5.6) while outcome was improved in LGG in AYA compared to children with a 10 year PFS of 76.8% vs 51.6% respectively (p=0.0009) suggesting a transition phase occurring during adolescence and early adulthood. CONCLUSIONS: AYA gliomas are enriched for paediatric-type alterations with distinct outcomes. Routine analysis is required given the role for targeted inhibitors.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".