The medical and functional burden of surviving childhood ependymoma: A population‐based study in Ontario, Canada
Bibliographic record
Abstract
BACKGROUND: Few studies have characterized the burden of late effects among childhood ependymoma survivors. To address this gap, we examined these sequelae using real-world health services data in a population-based ependymoma survivor cohort. METHODS: All individuals younger than 18 years diagnosed with an ependymoma in Ontario, Canada between 1987 and 2015 who had survived at least 5 years from their latest pediatric cancer event (index date) were matched 1:5 with population controls. Following linkage with provincial health services data, the cumulative incidences of multiple medical and functional outcomes between survivors and controls were compared. RESULTS: Among 96 survivors, 77.1% had been irradiated and 9.4% had received cisplatin. At 10 years post-index, survivors were at significantly higher risk of all-cause mortality (7.1%, 95% confidence interval [CI]: 1.0-13.3 vs. 0.3%, 95% CI: 0.0-1.0; p = .0002), non-obstetric hospitalization (45.1%, 95% CI: 32.6-56.7 vs. 10.6%, 95% CI: 7.6-14.1; p < .0001), stroke (6.5%, 95% CI: 2.3-13.7 vs. 0%; p < .0001), severe hearing loss requiring an amplification device (7.5%, 95% CI: 2.7-15.7 vs. 0%; p < .0001), receiving homecare service (27.6%, 95% CI: 18.5-37.5 vs. 7.7%, 95% CI: 5.3-10.7; p < .0001), and submitting a disability support prescription claim (24.0%, 95% CI: 14.8-34.3 vs. 5.4%, 95% CI: 3.5-7.8; p < .0001) compared to controls. CONCLUSIONS: Pediatric ependymoma survivors are highly vulnerable to severe late sequelae, including death, stroke, severe hearing loss, and disability. Urgent efforts are needed to improve risk-stratification approaches that mitigate exposure to toxic therapies for children with lower risk disease. Interventions to prevent or decrease the risk of developing late sequelae are critical to optimizing survivor long-term health.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".