OTHR-21. DEVELOPING A NEURO-ONCOLOGY PROGRAM FOR ADOLESCENTS AND YOUNG ADULTS IN CANADA – THE CANON EXPERIENCE
Bibliographic record
Abstract
Abstract BACKGROUND Brain tumors are the leading cause of cancer-related death in adolescents and young adults (AYA). These tumors possess both pediatric-type and adult-type qualities, with up to 30% of gliomas harboring pediatric-type alterations. Specialized expertise and significant collaboration between pediatric and adult providers is needed to guide therapy for AYAs. To address this, we have developed the Canadian Adolescent and Young Adult Neuro-Oncology Network (CANON). METHODS In April 2021, we established a national virtual AYA tumor board integrating comprehensive molecular analysis of available tumors. Rounds included representatives from both pediatric and adult neuro-oncology, radiation oncology, neurosurgery, neuropathology and neuroradiology. We collected clinical data and recommendations from rounds. RESULTS In the first 2 years of rounds through CANON, 156 cases have been reviewed. Gliomas (108) accounted for most cases followed by medulloblastoma (18) and ependymoma (7). Sequencing was available in 47% of cases. Of those with molecular data available, the majority (36) had a pediatric-type alteration, followed by IDH mutation (10). Additional molecular analysis was recommended in 29% of cases presented. Of those with sequencing data available, 35% had a potentially targetable alteration identified. Despite this, only 8% were eligible for a clinical trial based on their diagnosis and age. Recurrent clinical questions included access to molecular analysis, use of “off-label” targeted agents, lack of clinical trial options for AYA patients and the practice variation in treatment of AYA tumors typically seen in childhood such as medulloblastoma and germ cell tumor. DISCUSSION Dedicated AYA rounds have highlighted many inequities in care of these patients, highlighting a need for inclusion of AYAs in clinical trials and further study of tumor biology and clinical outcomes of this cohort. AYAs with pediatric-type tumors would also benefit from management by dedicated physicians with expertise in these complex tumors.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.015 | 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".