Brain Tumors in Adolescents and Young Adults: A Review
Bibliographic record
Abstract
Brain tumors account for the majority of cancer-related deaths in adolescents and young adults (AYAs), defined as individuals aged 15 to 39. AYAs constitute a distinct population in which both pediatric- and adult-type central nervous system (CNS) tumors can be observed. Clinical manifestations vary depending on tumor location and often include headaches, seizures, focal neurological deficits, and signs of increased intracranial pressure. With the publication of the updated World Health Organization CNS tumor classification in 2021, diagnoses have been redefined to emphasize key molecular alterations. Gliomas represent the majority of malignant brain tumors in this age group. Glioneuronal and neuronal tumors are associated with longstanding refractory epilepsy. The classification of ependymomas and medulloblastomas has been refined, enabling better identification of low-risk tumors that could benefit from treatment de-escalation strategies. Owing to their midline location, germ cell tumors often present with oculomotor and visual alterations as well as endocrinopathies. The management of CNS tumors in AYA is often extrapolated from pediatric and adult guidelines, and generally consists of a combination of surgical resection, radiation therapy, and systemic therapy. Ongoing research is investigating multiple agents targeting molecular alterations, including isocitrate dehydrogenase inhibitors, SHH pathway inhibitors, and BRAF inhibitors. AYA patients with CNS tumors should be managed by multidisciplinary teams and counselled regarding fertility preservation, psychosocial comorbidities, and risks of long-term comorbidities. There is a need for further efforts to design clinical trials targeting CNS tumors in the AYA population.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".