Practices and Resources Devoted to the Care of Adolescents and Young Adults with Cancer in Canada: A Survey of Pediatric and Adult Cancer Treatment Centers
Bibliographic record
Abstract
PURPOSE: Adolescents and young adults (AYAs) with cancer are a population of patients facing disparities of care affecting quality of life and other health outcomes. Our objective was to document the current environment, resources, and services available to and challenges in the care of these patients in Canada. METHODS: A questionnaire was developed with separate versions for pediatric and adult cancer centers. We invited one individual from every healthcare center providing cancer care in Canada to complete the questionnaire on behalf of his or her center. The survey included questions about referral patterns, diagnosis, treatment options, the nature of the challenges faced when treating AYAs with cancer, collaborative initiatives between pediatric and adult oncologists, and the presence of dedicated AYA resources and staff. RESULTS: We identified a lack of resources, staff, and collaborative activities dedicated to AYAs with cancer throughout Canada, both in pediatric and adult centers. Adult medical oncologists reported experiencing different challenges in treating AYAs with cancer compared to pediatric practitioners. CONCLUSIONS: Efforts to enhance AYA oncology care, including better resources and staffing and improved collaboration between pediatric and adult centers, are required.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".