Investigating the Association Between Individual Income and Cancer Outcomes Among Canadians Diagnosed with Gastric Cancer
Bibliographic record
Abstract
Background: A growing body of research continues to document income-based disparities in cancer outcomes. The first objective of this study was to investigate the association between individual income and diagnosis with stage IV gastric cancer, and the second objective of this study was to investigate the association between individual income and death from any cause in the five years following diagnosis. Methods: In Canadians diagnosed with gastric cancer between 2010 and 2019, this thesis used the Statistics Canada Canadian Census Health and Environmental Cohorts to investigate the association between individual income and diagnosis with stage IV gastric cancer using logistic regression, and the association between individual income and death from any cause within five years using Cox proportional hazards regression. Effect modification was tested, and sensitivity analyses were performed. Results: 8,545 Canadians were diagnosed with gastric cancer during the study period and met the study inclusion criteria; 1,900 were diagnosed in provinces where greater than 75% of people had TNM stage data recorded in the Canadian Cancer Registry. In the cohort of 1,900 people, we observed no association between individual income quintile and presentation with stage IV diagnosis (p=0.32) and no difference in presentation with stage IV disease at diagnosis between patients in the lowest and highest income quintiles (OR: 0.87, 95% CI: 0.64-1.19). In the cohort of 8,545 people, we observed a significant association between individual income quintile and death from any cause in the five years following diagnosis (p=0.003), with patients within the lowest income quintile having 1.18 times the risk of death when compared to patients within the highest income quintile (HR: 1.18, 95%.CI: 1.08-1.29). No effect modification was detected, and sensitivity analyses were consistent with the primary analyses. Conclusion: While we observed no income-based difference in the odds of presenting with stage IV gastric cancer diagnosis, a higher proportion of Canadian gastric cancer patients with low incomes die from any cause in the five years following diagnosis relative to those with high incomes. Future research should investigate the mechanisms underlying the association observed in this study and the effect of immigration on Canadian gastric cancer outcomes.
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.
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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".