Surveillance and survival among adolescents and young adults with cancer in Ontario, Canada
Bibliographic record
Abstract
Gains in survival rates among adolescents and young adults (AYA) are reported from the USA to be lower than in both younger and older patients. Limiting factors include low accrual to clinical trials related to the type of institutional care. This study aimed to determine the incidence of cancer in the 15-29 age group in Ontario, and the 5-year survival of these cases by disease class, age at diagnosis group and highest level of institutional complexity of care. The primary data source was Cancer Care Ontario (CCO). Diseases were classified according to an AYA-specific system. Age at diagnosis was grouped as 15-19, 20-24 and 25-29 years; and institutional site of care was categorized as pediatric oncology group of Ontario (POGO) centers, regional cancer centers (RCC-tertiary care centers associated with CCO), RCC affiliate and satellite institutions and other institutions having no specialized cancer services. More than 10,000 incident cases were identified during 1990-2001. Carcinomas and lymphomas each accounted for > 20% of the total. Overall 5-year survival rate was 83%; significantly higher for lymphomas at POGO centers and RCC than elsewhere. About 40% of eligible AYA cases were treated at a POGO center and 25% of those were accrued to clinical trials. The low proportion of adolescents referred to pediatric cancer centers may result in a survival disadvantage for this group. All AYA, especially with lymphomas, should be referred to specialized centers. Accrual of AYA to clinical trials must be improved substantially.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 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".