Treatment of Medulloblastoma in the Adolescent and Young Adult Population: A Systematic Review
Bibliographic record
Abstract
Medulloblastoma is the most frequent high-grade tumor of the central nervous system in children but accounts for less than 1% of these tumors in adults. Adolescent and young adult (AYA) patients are between both age groups, and different approaches are used to treat medulloblastoma in this population. We performed a systematic review of studies published between 2007 and 2023 that reported treatment approaches and survival data of AYA patients with medulloblastoma, defined as 15 to 39 years of age at diagnosis. Due to the heterogeneity of data, a meta-analysis was not possible. Except for the omission of chemotherapy after radiotherapy in a few adult studies, the treatment backbone is very similar between studies starting enrolment during childhood and older adolescence or adulthood. Despite indications for a higher rate of early treatment termination due to toxicity in adults, survival data remain comparable between studies starting enrolment earlier or later in life. However, molecular subtyping was missing in most studies, so the survival data must be interpreted cautiously. Nevertheless, pediatric-inspired strategies in the AYA population are feasible, but individual dose adjustments may be necessary during treatment and should be considered upfront. Collaborative studies investigating the best treatment approach for medulloblastoma in the AYA population are needed in the future.
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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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.004 |
| Bibliometrics | 0.003 | 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 | 0.000 |
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".