SOCIAL DETERMINANTS OF HEALTH IN UTERINE CANCER PATIENTS IN ONTARIO: ASSOCIATION WITH DISEASE PRESENTATION AND OUTCOME
Bibliographic record
Abstract
Objective: Delay in diagnosis and treatment of endometrial cancer may be associated with disease progression and impact management and outcomes. Social and cultural barriers influence recognition of symptoms and self-advocacy in seeking and complying with care. Associations between social determinants of health (SDH) and disease presentation, treatment and outcomes has been shown in some healthcare systems. Our objective was to investigate these in Ontario’s universal access system. Methods: Endometrial cancer patients in Ontario diagnosed 2009-2017 were identified, and clinical, social and demographic information extracted from administrative databases. SDH were quantified using previously validated marginalization quintiles (material deprivation, residential instability and ethnic concentration). Associations between SDH, disease stage, treatment and outcome were explored using chi-square, log-rank and logistic regression. Results: 19530 patients were identified. 73% of cancers were confined to the uterus. Stage distribution differed across marginalization quintiles (p<0.001) with advanced disease found more frequently in highly marginalized patients (highest vs lowest quintile): OR=1.28 (95% CI 1.14-1.45) for deprivation, OR=1.2 (95% CI 1.06-1.35) for residential instability and OR=1.3 (95% CI 1.15-1.46) for ethnic concentration (<0.0001)). Highly marginalized patients also had less timely surgery (p<0.0001). Overall survival was shorter in patients in high deprivation and residential instability quintiles (log rank p-value<0.0001) but not in high ethnic concentration quintiles, with HR=1.4 for deprivation (p<0.0001) and HR=1.53 for instability (p<0.0001) for the highest marginalization quintile. Survival differences persisted in more uniform cohorts of early (stage I) disease and endometrioid tumors and on multivariable analysis. Conclusions: Marginalized populations diagnosed with uterine cancer present at more advanced stages, wait longer for surgery and have shorter overall survival. Associations of SDH with uterine cancer presentation and management in Ontario could shed light on the impact of these factors on disease trajectory, drive policies for patient advocacy and redistribution of resources and promote health equity in this population.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".