Regional Variation in the Management of Metastatic Gastric Cancer in Ontario
Bibliographic record
Abstract
BACKGROUND: Geographic variation in cancer care is common when clear clinical management guidelines do not exist. In the present study, we sought to describe health care resource consumption by patients with metastatic gastric cancer (gc) and to investigate the possibility of regional variation. METHODS: In this population-based cohort study of patients with stage iv gastric adenocarcinoma diagnosed between 1 April 2005 and 31 March 2008, chart review and administrative health care data were linked to study resource utilization outcomes (for example, clinical investigations, treatments) in the province of Ontario. The study took a health care system perspective with a 2-year time frame. Chi-square tests were used to compare proportions of resource utilization, and analysis of variance compared mean per-patient resource consumption between geographic regions. RESULTS: A cohort of 1433 patients received 4690 endoscopic investigations, 12,033 computed tomography exams, 12,774 radiography exams, and 5059 ultrasonography exams. Nearly all patients were seen by a general practitioner (98%) and a specialist (99%), and were hospitalized (95%) or visited the emergency department (87%). Fewer than half received chemotherapy (43%), gastrectomy (37%), or radiotherapy (28%). The mean number of clinical investigations, physician visits, hospitalizations, and instances of patient accessing the emergency department or receiving radiotherapy or stent placement varied significantly by region. CONCLUSIONS: Variations in health care resource utilization for metastatic gc patients are observed across the regions of Ontario. Whether those differences reflect differential access to resources, patient preference, or physician preference is not known. The observed variation might reflect a lack of guidelines based on high-quality evidence and could partly be ameliorated with regionalization of gc care to high-volume centres.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".