EPID-17. A SINGLE CENTER RESTROSPECTIVE REVIEW OF RECURRENT OR TREATMENT REFRACTORY PEDIATRIC MEDULLOBLASTOMA
Bibliographic record
Abstract
The outcome of pediatric refractory or relapsed brain tumours remains a concern for treating neurooncology teams with the most effective salvage therapy yet to be established. Upfront therapy for primary medulloblastoma (MB) is dependent on age, post-operative residual and evidence of metastasis at diagnosis. Children diagnosed with aggressive subtypes of MB that are refractory to upfront therapy or recur either in the resection cavity or as distant metastases have a very poor prognosis. Reports of phase I and II studies for these children exist, but these therapies bear significant treatment related morbidity and mortality. A retrospective review of children diagnosed with a pediatric MB from 2002–2017 from the McMaster Pediatric Brain Tumour Study Group (PBTSG) captured a number of pediatric recurrent MB. Subsequently the treatments received and outcomes were identified. Over the 15-year period, 30 children with a histological diagnosis of MB were treated. Ten children were recurrent or treatment refractory MB. The 5-year outcome survival (OS) for this group of patients as compared to no recurrence was 20% and 90% respectively. The mean follow-up for survivors of recurrent MB however was 3.2 years. In 4 of 10 recurrent MB, the disease had significantly progressed and palliated. For the remaining children, therapy offered included cyberknife, imatinib, etoposide, vinblastine, temsirolimus, imatinib, tipifarnib, temozolamide, and irinotecan either in isolation or in varying combinations. Congruent to the literature, recurrent MB in our single center cohort carried a poor prognosis despite administration of salvage therapy.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.007 | 0.007 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 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".