Impact of locus of care on outcomes in adolescents and young adults with osteosarcoma and Ewing sarcoma treated at pediatric versus adult cancer centers: An IMPACT cohort study
Bibliographic record
Abstract
BACKGROUND: Location of cancer care (LOC; pediatric vs. adult center) impacts outcomes in adolescents and young adults (AYA) with some cancer types. Data on the impact of LOC on survival in AYA with osteosarcoma (OSS) and Ewing sarcoma (EWS) are limited OBJECTIVES: To compare differences in demographics, disease/treatment characteristics, and survival in a population-based cohort of AYA with OSS or EWS treated at pediatric versus adult centers METHODS: The Initiative to Maximize Progress in Adolescent Cancer Therapy (IMPACT) cohort captured demographic, disease, and treatment data for all AYA (15-21 years old) diagnosed with OSS and EWS in Ontario, Canada between 1992 and 2012. Patients were linked to provincial administrative health care databases. Outcomes were compared between patients treated in pediatric versus adult centers. RESULTS: One hundred thirty-seven AYA were diagnosed with OSS (LOC: 47 pediatric, 90 adult) and 84 with EWS (38 pediatric, 46 adult). AYA treated at pediatric centers were more likely to be enrolled in a clinical trial (OSS 55% vs. 1%, p < .001; EWS 53% vs. 2%, p < .001) and received higher cumulative chemotherapy doses. Five-year event-free survival (EFS ± standard error) in OSS and EWS were 47% ± 4% and 43% ± 5%, respectively. In multivariable analysis, the impact of LOC (pediatric vs. adult center) on EFS in OSS (adjusted hazard ratio [HR] 1.15, 95% confidence interval [CI]: 0.58-2.27, p = .69) and EWS (adjusted HR 1.82, 95% CI: 0.97-3.43, p = .06) was not statistically significant. CONCLUSION: Despite disparities in trial participation and chemotherapy doses, outcomes did not differ by LOC suggesting that AYA with bone tumors can be treated at either pediatric or adult centers.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".