Trends in the Aggressiveness of End-of-Life Cancer Care in the Universal Health Care System of Ontario, Canada
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
PURPOSE: To describe trends in the aggressiveness of end-of-life (EOL) cancer care in a universal health care system in Ontario, Canada, between 1993 and 2004, and to compare with findings reported in the United States. METHODS: A population-based, retrospective, cohort study that used administrative data linked to registry data. Aggressiveness of EOL care was defined as the occurrence of at least one of the following indicators: last dose of chemotherapy received within 14 days of death; more than one emergency department (ED) visit within 30 days of death; more than one hospitalization within 30 days of death; or at least one intensive care unit (ICU) admission within 30 days of death. RESULTS: Among 227,161 patients, 22.4% experienced at least one incident of potentially aggressive EOL cancer care. Multivariable analyses showed that with each successive year, patients were significantly more likely to encounter some aggressive intervention (odds ratio, 1.01; 95% CI, 1.01 to 1.02). Multiple emergency department (ED) visits, ICU admissions, and chemotherapy use increased significantly over time, whereas multiple hospital admissions declined (P < .05). Patients were more likely to receive aggressive EOL care if they were men, were younger, lived in rural regions, had a higher level of comorbidity, or had breast, lung, or hematologic malignancies. Chemotherapy and ICU utilization were lower in Ontario than in the United States. CONCLUSION: Aggressiveness of cancer care near the EOL is increasing over time in Ontario, Canada, although overall rates were lower than in the United States. Health system characteristics and patient or physician cultural factors may play a role in the observed differences.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it