Impact of Social Determinants on Melanoma Outcomes in Canada: A Single‐Centre Retrospective Study
Bibliographic record
Abstract
INTRODUCTION: Socioeconomic status (SES) and distance to nearest hospital are known social determinants impacting melanoma survival; however, few studies have investigated the effect in a universal healthcare setting, like Canada. MATERIALS AND METHODS: This retrospective study at The Ottawa Hospital (1999-2023) investigated SES and distance lived from the hospital on overall survival, recurrence time, and stage at presentation in melanoma surgical patients. Income quintiles (InQs) were determined using postal codes linked to 2016 census data, and logistic regressions were conducted for the highest and lowest InQs. RESULTS: Of 959 patients, 277 were in the highest InQ group (mean age: 64; 57% males) and 114 were in the lowest (mean age: 60; 48% males). Higher InQ was significantly associated with lower odds of stage II-IV disease at presentation (p = 0.004, odds ratio: 0.865, 95% CI 0.784 to 0.954), but not with overall survival, recurrence time, or stage III-IV disease. Distance had no significant impact on outcomes. Female sex was protective against recurrence time (p = 0.020, hazard ratio: 0.705), stage II-IV (p = 0.049, odds ratio: 0.766, 95% CI: 0.587, 0.999), and III-IV (p = 0.009, odds ratio: 0.670, 95% CI: 0.496, 0.904) disease. CONCLUSION: Higher SES reduced stage II-IV risk without affecting survival, stage III-IV risk, or recurrence time. Distance to nearest hospital had no significant effect. Females had longer time to recurrence and lower odds of advanced disease. Future research should explore potential educational and primary care barriers that may contribute to advanced stages in lower InQ 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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.000 |
| 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".