Targeted therapies in adolescent and young adult patients with central nervous system tumors
Bibliographic record
Abstract
Adolescents and young adults (AYA: ages 15-39 years) are a unique population at risk of both pediatric-type and adult-type central nervous system (CNS) tumors. Targeted therapies are now available for a growing subset of CNS tumors represented within AYA. Gliomas represent 25% of all primary brain tumors in AYA, with up to 30% of these harboring a pediatric-type molecular alteration in the mitogen-activated protein kinase (MAPK) pathway. MAPK-pathway inhibitors are often utilized in AYA patients with a pediatric low-grade glioma (pLGG), however specific clinical trials spanning the entire AYA age range for this molecular alteration are absent. Isocitrate dehydrogenase (IDH) mutations are the most common molecular alteration found in AYA glioma. The IDH-mutant inhibitor vorasidenib has been demonstrated to prolong progression-free survival in grade 2 IDH-mutant glioma; however, there is a lack of evidence in patients younger than 18. Meningioma is the most common primary CNS tumor in adults and represents 15% of primary CNS tumors in the AYA population. Recent molecular characterization of meningioma has led to several targeted therapeutic clinical trials in the relapsed/refractory setting. Medulloblastoma is the most common embryonal CNS tumor in AYA patients and is primarily driven by a mutation in the sonic hedgehog (SHH) pathway. The SHH pathway is targetable with Smoothened (SMO) inhibitors which has been utilized in the relapsed/refractory setting for both pediatric and adult patients, with mixed responses. Clinical trials incorporating SMO inhibition upfront treatment have been hampered by low accrual numbers and lack of sponsor support. Craniopharyngioma is a rare CNS tumor in the AYA population, and BRAFV600E mutations in papillary craniopharyngioma represent a targetable alteration. Solutions to improving the care of AYA should include appropriate representation in clinical trials and specialized care by experienced clinicians.
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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".