IMPACT: Prevalence and Predictors of High-Intensity End-of-Life Care Among Adolescents and Young Adults with Cancer in Ontario
Bibliographic record
Abstract
Adolescents and young adults (AYA) with cancer may experience disproportionate rates of high-intensity (HI) end-of-life (EOL) care. We conducted a population-based linkage study examining a decedent cohort of all Ontario AYA aged 15-21 years diagnosed with six primary cancers between 1992-2012. The primary composite outcome (HI-EOL care) included any of: intravenous chemotherapy ≤14 days from death; >1 emergency department visit; >1 hospitalization; or any intensive care unit (ICU) admission ≤30 days from death. Secondary outcomes included hospital deaths and measures of most invasive (MI)-EOL care. The outcome prevalence trends were examined, as were the predictors using regression models. Of 483 patients, 292 (60.5%) experienced HI-EOL care. AYA with hematological malignancies and relapsed disease experienced the highest and lowest odds of all outcomes, respectively. The prevalence of MI-EOL care may be increasing, especially for pediatric patients. This work is the first to identify LOC-based disparities in AYA EOL care.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".