Prevalence and predictors of high-intensity end-of-life care among adolescents and young adults with cancer in Ontario: a population-based study using the IMPACT cohort.
Bibliographic record
Abstract
10559 Background: End-of-life (EOL) care in adolescents and young adults (AYA) with cancer is poorly characterized, though this group may be at risk of elevated rates of high-intensity (HI) care and consequently, increased EOL suffering. Few population-based studies exist, and are limited by incomplete clinical information. AYA care patterns can vary by locus of care (LOC – pediatric v. adult), but LOC disparities in AYA EOL care are unstudied. Methods: We conducted a retrospective decedent population-based cohort study of all Ontario AYA diagnosed between 15-21 years of age with 6 prevalent primary cancers between 1992-2012, who died ≤5 years from diagnosis. Chart-abstracted clinical data were linked to health services data. The primary composite outcome (HI-EOL care) included any of: intravenous chemotherapy ≤14 days from death; > 1 emergency department visit ≤30 days from death; or > 1 hospitalization or intensive care unit (ICU) admission ≤30 days from death. Secondary outcomes included measures of the most invasive (MI) EOL care: mechanical ventilation ≤14 days from death, and death in the ICU. Factors associated with HI-EOL were examined. Results: Of 483 patients, 292 (60.5%) experienced HI-EOL care, 98 (20.3%) were mechanically ventilated ≤14 days from death, and 110 (22.8%) died in the ICU. Patients with hematological malignancies (v. solid tumors) were at greatest risk of HI-EOL care (OR, 2.3; 95CI, 1.5-3.5, p < 0.01), mechanical ventilation (OR, 5.4; 95CI, 3.0-9.7, p < 0.01), and death in an ICU (OR, 4.9; 95CI, 2.8-8.5, p < 0.01). AYA who died in a pediatric center were substantially more likely to experience MI-EOL measures compared to those dying in adult centers (mechanical ventilation, OR 3.2, 95CI 1.3-7.6, p = 0.01). Assessment of interactions showed LOC-based disparities widening over the study period (ICU death in pediatric v. adult centres: early period OR 0.9, 95CI 0.3-2.9, p = 0.91; late period OR 3.3, 95CI 1.2-9.2, p = 0.02; interaction term p = 0.04). AYA living in rural areas were also at higher risk of experiencing mechanical ventilation (OR, 2.0; 95CI, 1.0-3.8, p = 0.04) and death in ICU (OR, 2.1; 95CI, 1.1-4.0, p = 0.02). Conclusions: AYA with cancer experience high rates of HI-EOL care, with patients in pediatric centers and those living in rural areas at highest risk of MI-EOL care. Our study is the first to identify LOC-based disparities in AYA EOL care. Future studies should explore mechanisms underlying these disparities, including potential differences in palliative care services.
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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 | 0.001 |
| 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 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".