Patterns of Care and Costs for Older Patients With Colorectal Cancer at the End of Life: Descriptive Study of the United States and Canada
Bibliographic record
Abstract
PURPOSE: End-of-life (EOL) cancer care is costly, with challenges regarding intensity and place of care. We described EOL care and costs for patients with colorectal cancer (CRC) in the United States and the province of Ontario, Canada, to inform better care delivery. METHODS: Patients diagnosed with CRC from 2007 to 2013, who died of any cancer from 2007 to 2013 at age ≥ 66 years, were selected from the US SEER cancer registries linked to Medicare claims (n = 16,565) and the Ontario Cancer Registry linked to administrative health data (n = 6,587). We estimated total and resource-specific costs (2015 US dollars) from public payer perspectives over the last 360 days of life by 30-day periods, by stage at diagnosis (0-II, III, IV). RESULTS: In all months, especially 30 days before death, higher percentages of SEER-Medicare than Ontario patients received chemotherapy (15.7% v 8.0%), and imaging tests (39.4% v 31.1%). A higher percentage of Ontario patients were hospitalized (62.5% v 51.0%), but 43.2% of hospitalized SEER-Medicare patients had intensive care unit (ICU) admissions versus 17.9% of hospitalized Ontario patients. Cost differences between cohorts were greater for patients with stage IV disease. In the last 30 days, mean total costs for patients with stage IV disease were $15,881 (SEER-Medicare) and $12,034 (Ontario) versus $19,354 and $17,312 for stage 0-II. Hospitalization costs were higher for SEER-Medicare patients ($11,180 v $9,434), with lower daily hospital costs in Ontario ($1,067 v $2,004). CONCLUSION: These findings suggest opportunities for reducing chemotherapy and ICU use in the United States and hospitalizations in Ontario.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.007 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".