EPEN-31. SUBGROUP SPECIFIC LONG-TERM SURVIVAL AND NEUROCOGNITIVE OUTCOMES IN POSTERIOR FOSSA EPENDYMOMA (PFE)
Bibliographic record
Abstract
PFE comprises two groups, EPN_PFA and EPN_PFB with stark differences in outcome. However, the long-term outcomes of PFA ependymoma and the pattern of relapse have not been fully described. We aimed to identify predictors of survival and neurocognitive outcome in a large consecutive cohort of subgrouped PFE over three decades. Seventy-three PFE were identified, of which 89% were PFA. There were no relapses amongst PFB. Ten-year PFS of PFA was poor at 37 +/- 7%. Analysis of consecutive 10-year epochs revealed significant improvement in PFS/OS over time (2005–2014 compared to 1985–1994 and 1995–2004). This pertains to the GTR rate increased from 35% to 77% and use of upfront radiation increased from 65% to 96% over the observed period and confirmed in a multivariable model. The pattern of relapse changed over time, related to GTR PFA relapsing with metastasis. Analysis of longitudinal neuropsychological outcomes in a mixed linear model shows continuous declines in IQ over time with upfront conformal radiation, which are particularly pronounced in infants under the age of 3 (FSIQ -1.33 points/year). Data from a molecularly informed large prospective cohort of PFE clearly indicate improved survival over time, related to more aggressive surgery and upfront radiation. However for the first time in a subgrouped cohort, we show that this approach results in reduced neurocognitive outcomes over time. Our data suggest that all children with EPN_PFA should receive upfront radiation and be concomitantly prioritized for early neuropsychological testing and intervention.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 |
| 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 | 0.001 |
| 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".