Long-term Outcomes and Complications in Pediatric Ewing Sarcoma
Bibliographic record
Abstract
OBJECTIVES: The objective of this study was to determine treatment outcomes and long-term complications in pediatric patients with Ewing Sarcoma treated at the British Columbia Cancer Agency (BCCA). METHODS: A retrospective chart review of 101 pediatric patients (<19 y old) with Ewing Sarcoma diagnosed between 1960 and 2005 was performed. The Kaplan-Meier survival analysis and Cox regression multivariate analysis were used to assess prognostic factors for overall survival (OS) and event-free survival (EFS). RESULTS: The median age at diagnosis was 11 years and the median follow-up for nondeceased patients was 13.5 years. The most common primary tumor locations were lower extremity (33%), pelvis (24%), and thorax (18%). Fifty percent of patients received surgery, 79% radiotherapy and 94% chemotherapy. The 5-year OS and EFS for patients with localized disease was 85% and 73% and for metastatic disease was 27% (P<0.0001) and 28% (P<0.0001), respectively. Metastatic disease was an independent predictor of lower OS (hazard ratio [HR], 9.5; 95% confidence interval [CI],4.7-19.4; P<0.0001) and EFS (HR, 4.9; 95% CI, 2.7-8.8; P<0.0001). Extremity tumor location was an independent predictor for improved OS (HR, 0.4; 95% CI, 0.2-0.9; P=0.03). The majority (77%) of long-term survivors (≥5 y) had long-term complications; the most common were musculoskeletal abnormalities (50%) and cardiac toxicity (28%). The actuarial second neoplasm risk was 5% at 10 years. CONCLUSIONS: Ewing sarcoma patients with localized disease had excellent treatment outcomes at the BCCA. However, the majority of patients had chronic complications from treatment. This study validates the need for long-term follow-up of Ewing Sarcoma survivors for management of late effects.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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".