The impact of socioeconomic status on stage at presentation, receipt of diagnostic imaging, receipt of treatment and overall survival in colorectal cancer patients
Bibliographic record
Abstract
Socioeconomic factors influence patterns of care in colorectal cancer. Our study investigates the impact of socioeconomic status (SES) on stage at presentation, receipt of diagnostic imaging, receipt of treatment and overall survival (OS) in a universal healthcare system. The Ontario Cancer Registry (OCR) was accessed to identify a cohort of patients diagnosed with colorectal adenocarcinoma from 2007 to 2016 in Ontario, Canada. SES was measured using median neighborhood income divided into quintiles (Q1-Q5; Q1 = lowest income). Logistic regression analyses were used to evaluate stage, imaging and treatment. Cox proportional hazards models were used to evaluate OS. All endpoints were adjusted for demographics and comorbidities with OS models also adjusting for stage, imaging and treatment. In total, 39 802 colon and 13 164 rectal patients were identified. Lower SES was associated with advanced stage at presentation in both cohorts (Q1 vs Q5: Colon odds ratio [OR] = 1.08, P = .046, rectal OR = 1.25, P < .0001). Lower SES colon patients were less likely to receive adjuvant oxaliplatin (Q1 vs Q5: OR = 0.78, P < .001) and all palliative chemotherapies studied including oxaliplatin (Q1 vs Q5: OR = 0.60, P < 0.0001), irinotecan (Q1 vs Q5: OR = 0.65, P < .0001), bevacizumab (Q1 vs Q5: OR = 0.70, P < .001), cetuximab (Q1 vs Q5: OR = 0.40, P = .0053) and panitumumab (Q1 vs Q5: OR = 0.54, P = .0036). In rectal patients, lower SES was associated with decreased receipt of rectal cancer resection for stages I-III (Q1 vs Q5: OR = 0.78, P < .001), adjuvant oxaliplatin (Q1 vs Q5: OR = 0.72, P = .0020) and palliative chemotherapies including oxaliplatin (Q1 vs Q5: OR = 0.59, P < .001), irinotecan (Q1 vs Q5: OR = 0.53, P < .001) and bevacizumab (Q1 vs Q5: OR = 0.71, P = .046). All survival models identified poorer OS for lower SES patients (total colorectal; Q1 vs Q5: Hazard ratio [HR] = 1.25, P < .0001). These findings suggest disparities persist even within universal healthcare.
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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 | 0.003 |
| 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) | 0.001 | 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".