P.139 Pediatric posterior fossa ependymoma recurrence in a molecularly defined cohort – Clinical, demographic, and surgical factors associated with outcome
Bibliographic record
Abstract
Background: Pediatric posterior fossa ependymoma contributes to morbidity and mortality in children. Following gross total resection and adjuvant radiotherapy, there is a known risk of local recurrence that portends a dismal prognosis. We sought to characterize survival in a molecularly defined cohort with an emphasis on recurrence patterns that influence outcome. Methods: This study was approved by the Ethics Board of the Hospital for Sick Children. We performed a twenty-year single-center retrospective study to identify clinical, demographic and treatment characteristics of patients with pathologically diagnosed posterior fossa ependymoma. Results: There were 60 patients identified that underwent primary resection. Recurrence rate in the cohort was 48% with 29 cases of recurrent ependymoma occurring at a mean time of 24 months after index surgery. No mortalities were observed among patients undergoing primary resection without recurrent disease. Median cohort survival was 12.3 years in the primary cohort and and 6.32 years among patients recurrent ependymoma. Recurrent disease was significantly associated with worse overall survival after multivariate analysis (HR = 0.024). Conclusions: We highlight overall survival and factors influencing mortality in pediatric posterior fossa ependymoma. Recurrent disease confers a worse prognosis. We describe for the first time survival trends following local and distant recurrences managed through multiple resections.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.003 | 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".