Association of neighborhood socioeconomic status and ethnic diversity with receipt of adjuvant chemotherapy in stage III colon cancer: A population-based cohort study
Bibliographic record
Abstract
Background Adjuvant chemotherapy reduces cancer recurrence and improves survival in eligible patients. Barriers to care may contribute to inequities in outcomes. We examined the association between neighborhood socioeconomic status (SES) and ethnic diversity with receipt of adjuvant chemotherapy in stage III colon cancer patients. Methods A population-based retrospective cohort study was conducted on adults undergoing surgery for stage III colon cancer (2007–2020). SES and ethnic diversity, defined by quintiles from census data, were the primary exposures. Outcomes were receipt of medical oncology consultation and adjuvant chemotherapy within 3 months post-surgery. Logistic regression measured the association between each exposure and outcomes, adjusting for confounders. A sub-group analysis was performed on patients who received a medical oncology consultation. Results Of 14,511 patients, 10,973 (76.5%) received medical oncology consultation and 8,814 (61.4%) adjuvant chemotherapy. SES and ethnic diversity were not associated with medical oncology consultation after adjusting for age, sex, surgical approach, and comorbidities. However, the lowest SES quintile and highest ethnic diversity quintile were associated with lower odds of adjuvant chemotherapy (OR 0.70; 95% CI 0.62-0.80 and OR 0.72; 95% CI 0.64-0.82, respectively). These associations persisted at 6 months post-surgery. Among patients who had a medical oncology consultation, both the lowest SES and highest ethnic diversity quintiles were associated with lower odds of adjuvant chemotherapy. Conclusion Lower SES and higher ethnic diversity were independently associated with lower odds of adjuvant chemotherapy but not medical oncology consultation, highlighting disparities in outcomes for marginalized patients within a universal healthcare system. SYNOPSIS We examined the association between neighborhood socioeconomic status (SES) and ethnic diversity with receipt of adjuvant chemotherapy in stage III colon cancer patients in Ontario. Those from the lowest SES or most diverse neighborhoods had 30% and 28% lower odds of receiving chemotherapy, highlighting disparities within a universal healthcare system.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".