Adjuvant radiotherapy in the treatment of pediatric myxopapillary ependymomas
Bibliographic record
Abstract
OBJECTIVES: Assess the role of radiotherapy (RT) in the management of primary and recurrent myxopapillary ependymoma (MPE). MATERIALS AND METHODS: We conducted a retrospective review of patients with MPE treated at the Montreal Children's Hospital/McGill University Health Centre between 1985 and 2008. RESULTS: Seven children under the age of 18 were diagnosed and treated for MPE. All patients were treated with surgery to the primary site. Three patients underwent subtotal resection (STR) and received adjuvant post-operative RT. Only one patient who had spinal drop metastases received post-operative RT to the lumbosacral region following complete resection of the primary tumor. After a median follow up of 78 months (range 24-180 months), all patients were alive with controlled disease. The single patient treated with gross total resection (GTR) and adjuvant local radiation remained recurrence free. One of the three patients treated with STR and adjuvant RT had disease progression that was controlled with re-resection and further RT. Two of the three patients treated with surgery alone developed local and disseminated recurrent spinal disease that was controlled by salvage RT. CONCLUSION: Our data support the evolving literature which suggests that GTR alone provides suboptimal disease control in MPE. In our patients, RT resulted in control of residual, metastatic and/or recurrent disease. Routine adjuvant RT may improve outcomes in pediatric MPE.
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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 | 0.000 | 0.000 |
| 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) | 0.001 | 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".