SIOP Ependymoma I: Final results, long-term follow-up, and molecular analysis of the trial cohort—A BIOMECA Consortium Study
Bibliographic record
Abstract
BACKGROUND: SIOP Ependymoma I was a non-randomised trial assessing event free and overall survival (EFS/OS) of non-metastatic intracranial ependymoma in children aged 3-21 years treated with a staged management strategy. A further aim was to assess the response rate (RR) of subtotally resected (STR) ependymoma to vincristine, etoposide, and cyclophosphamide (VEC). We report final results with 12-year follow-up and post hoc analyses of recently described biomarkers. METHODS: Seventy-four participants were eligible. Children with gross total resection (GTR) received radiotherapy, whilst those with STR received VEC before radiotherapy. DNA methylation, 1q, hTERT, ReLA, Tenascin-C, H3K27me3, and pAKT status were evaluated. RESULTS: Five- and ten-year EFS was 49.5% and 46.7%, OS was 69.3% and 60.5%. GTR was achieved in 33/74 (44.6%) and associated with improved EFS (P = .003, HR = 2.6, 95% confidence interval (CI) 1.4-5.1). Grade 3 tumours were associated with worse OS (P = .005, HR = 2.8, 95%CI 1.3-5.8). 1q gain and hTERT expression were associated with poorer EFS (P = .003, HR = 2.70, 95%CI 1.49-6.10 and P = .014, HR = 5.8, 95%CI 1.2-28) and H3K27me3 loss with worse OS (P = .003, HR = 4.6, 95%CI 1.5-13.2). Methylation profiles showed expected patterns. 12 participants with STR did not receive chemotherapy; a protocol violation. However, best chemotherapy RR was 65.5% (19/29, 95%CI 45.7-82.1), exceeding the prespecified 45%. CONCLUSIONS: Participants with totally resected ependymoma had the best outcomes. RR of STR to VEC exceeded the pre-specified efficacy criterion. However, cases of inaccurate stratification highlighted the need for rapid central review. 1q gain, H3K27me3 loss, and hTERT expression were all associated with poorer survival outcomes.
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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 | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".