Comparison of Two Diverse Populations, British Columbia, Canada, and Ardabil, Iran, Indicates Several Variables Associated with Gastric and Esophageal Cancer Survival
Bibliographic record
Abstract
BACKGROUND: Geographic variation and temporal trends in the epidemiology of esophageal and gastric cancers vary according to both tumor morphology and organ subsite. This study compares 1-year survival of gastric and esophageal cancers between two distinct populations: British Columbia (BC), Canada, and Ardabil, Iran. METHODS: Data for invasive primary esophageal and gastric cancer patients were obtained from the population-based cancer registries for BC and Ardabil. The relative survival rate was calculated using WHO Statistical Information System (WHOSIS) life-tables for each country. Chi-square and Fisher's exact tests were used to compare survival differences between BC and Ardabil. T-tests, chi-square tests, and Fisher's exact test were used to compare patient characteristics and tumor factors between the populations. RESULTS: The overall 1-year age-standardized relative survivals for gastric cancer were 48% and 21% in BC and Ardabil, respectively (p < 0.01). The overall 1-year age-standardized relative survival for esophageal cancer was 33% and 17% in BC and Ardabil, respectively (p < 0.05). Overall and separately for each gender, age group, tumor location, and histology, there was greater 1-year survival of the gastric cancer patients in BC compared to Ardabil. For esophageal cancer; patients under age 65, patients with tumors in the middle or upper third of esophagus, and patients with squamous cell carcinoma had significantly better survival in BC than in Ardabil. CONCLUSION: Findings of this study point to differences in disease characteristics and patient factors, not solely differences in healthcare systems, as being responsible for the survival difference in these populations.
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.002 | 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".