Distinct relapse pattern across molecular ependymoma types
Bibliographic record
Abstract
BACKGROUND: Ependymoma (EPN) is not a uniform disease but represents different disease types with biological and clinical heterogeneity. However, the pattern of when and where different types of EPN relapse is not yet comprehensively described. METHODS: We assembled 269 relapsed intracranial EPN from pediatric (n = 233) and adult (n = 36) patients from European and Northern American cohorts and correlated DNA methylation patterns and copy-number alterations with clinical information. RESULTS: The cohort comprised the following molecular EPN types: PF-EPN-A (n = 177), ST-EPN-ZFTA (n = 45), PF-EPN-B (n = 31), PF-EPN-SE (n = 12), and ST-EPN-YAP (n = 4). First relapses of PF-EPN-B (PF: posterior-fossa) and PF-EPN-SE (SE: subependymoma) occurred later than of PF-EPN-A, ST-EPN-YAP (ST: supratentorial), or ST-EPN-ZFTA (median time to relapse: 4.3 and 6.0 years vs. 1.9/1.0/2.4 years; P < .01). Metastatic or combined recurrences in PF-EPN-B and -A more often involved the spinal cord than in ST-EPN-ZFTA (72.7% and 40.0 vs. 12.5%; P < .01). No distant relapses were observed in ST-EPN-YAP (n = 4) or PF-EPN-SE (n = 12). Post-relapse survival (PRS) was poor for PF-EPN-A and ST-EPN-ZFTA (5-year PRS: 44.5% ± 4.4%/47.8% ± 9.1%), whereas PF-EPN-B and PF-EPN-SE displayed a 5-year PRS of 89.5% ± 7.1%/90.0% ± 9.5% (P = .03). However, 10-year PRS for PF-EPN-B dropped to 45.8% ± 17.3%. Neither between the radiation field and relapse pattern nor between the radiation field and spinal involvement at relapse an impact was identified. Notably, all patients with relapsed ST-EPN-YAP did not receive upfront radiotherapy but were successfully salvaged using irradiation at relapse. CONCLUSIONS: Relapse patterns of specific EPN types are different. Future clinical trials, treatment adaptions, duration of surveillance, and diagnostics should be planned to incorporate entity-specific relapse information.
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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) | 0.001 | 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".