Comparison of Treatment, Cost, and Survival in Patients With Metastatic Colorectal Cancer in Western Washington, United States, and British Columbia, Canada
Bibliographic record
Abstract
PURPOSE: Few studies have directly compared health care utilization, costs, and outcomes between patients treated in the US multipayer health system and Canada’s single-payer system. Using cancer registry and claims data, we assessed treatment types, costs, and survival for patients with metastatic colorectal cancer (mCRC) in Western Washington State (WW) and British Columbia (BC). MATERIALS AND METHODS: Patients age ≥ 18 years diagnosed with mCRC in 2010 and later were identified from the BC Cancer database and a regional database linking WW SEER to claims from Medicare and two large commercial insurers. Demographics, treatment characteristics, costs of systemic therapy, and survival data were obtained from these databases and compared between the two regions. RESULTS: A total of 1,592 patients from BC and 901 from WW were included in the study. Median age was similar (BC, 66 years; WW, 63 years), but patients in BC were more likely to be male (57.1% v 51.2%; P ≤ .01) and to have de novo metastatic disease (61.0% v 38.3%; P ≤ .01). The use of radiation therapy was similar between regions (BC, 31.2%; WW, 33.9%; P = .18), but primary tumor resection was more common in BC (74.1% v 66.3%; P ≤ .01) as was hepatic metastasectomy (12.4% v 2.3%; P ≤ .01). Similar percentages of patients received systemic therapy (BC, 68.8%; WW, 67.1%; P = .40), but costs were significantly higher for first-line systemic therapy in WW ($6,226 v $15,792 per patient per month; P ≤ .01). Median overall survival was similar (BC, 16.9 months; WW, 18 months). CONCLUSION: Cost of systemic therapy for mCRC was significantly higher for patients in WW than in BC, but this did not translate to a difference in overall survival.
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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 | 0.000 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".