P.130 Clinical prognostic factors in adult intracranial ependymoma patients – A fifty year multi-institutional experience
Bibliographic record
Abstract
Background: Standard of care treatment for adult intracranial ependymoma patients includes maximal safe surgical resection, while the role for adjuvant radiotherapy remains unclear with existing data from small retrospective series’. Accordingly, we built a multi-institutional cohort to assess the prognostic value of adjuvant radiotherapy and other clinical factors in these patients. Methods: Patients managed for adult intracranial ependymomas from 1968 onwards within the University Health Network in Toronto, The University of Oklahoma Health Sciences Center, and The Ottawa Hospital were identified. Multivariate models assessing the prognostic value of clinical factors were built using variables with known prognostic value and/or significance in univariate Cox models. Results: Of 122 ependymomas, 71% were infratentorial, 78% grade two, 55% gross/near-totally resected (GTR/NTR), and 65% treated with adjuvant radiotherapy. Multivariate analyses identified GTR/NTR (vs. subtotal resection; HR=0.2, 95%CI=0.1–0.4, p<0.0001) and cranial (HR=0.5, 95%CI=0.2–1.1) or craniospinal (HR=0.2, 95%CI=0.04–0.5) radiotherapy receipt (p=0.01) as independent statistically significant predictors of more favourable PFS. Grade II pathology (vs. grade III; HR=0.2, 95%CI=0.05–0.6, p=0.006) and GTR/NTR (vs. subtotal resection; HR=0.1, 95%CI=0.03–0.3, p=0.0001) were independent statistically significant predictors of better OS. Conclusions: This work confirms the importance of maximal safe resection for adult intracranial ependymomas and establishes that adjuvant radiotherapy improves progression-free survival in these patients.
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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 | 0.001 |
| 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".