Income differences in time to colon cancer diagnosis
Bibliographic record
Abstract
INTRODUCTION: People with low income have worse outcomes throughout the cancer care continuum; however, little is known about income and the diagnostic interval. We described diagnostic pathways by neighborhood income and investigated the association between income and the diagnostic interval. METHODS: This was a retrospective cohort study of colon cancer patients diagnosed 2007-2019 in Ontario using routinely collected data. The diagnostic interval was defined as the number of days from the first colon cancer encounter to diagnosis. Asymptomatic pathways were defined as first encounter with a colonoscopy or guaiac fecal occult blood test not occurring in the emergency department and were examined separately from symptomatic pathways. Quantile regression was used to determine the association between neighborhood income quintile and the conditional 50th and 90th percentile diagnostic interval controlling for age, sex, rural residence, and year of diagnosis. RESULTS: A total of 64,303 colon cancer patients were included. Patients residing in the lowest income neighborhoods were more likely to be diagnosed through symptomatic pathways and in the emergency department. Living in low-income neighborhoods was associated with longer 50th and 90th-percentile symptomatic diagnostic intervals compared to patients living in the highest income neighborhoods. For example, the 90th percentile diagnostic interval was 15 days (95% CI 6-23) longer in patients living in the lowest income neighborhoods compared to the highest. CONCLUSION: These findings reveal income inequities during the diagnostic phase of colon cancer. Future work should determine pathways to reducing inequalities along the diagnostic interval and evaluate screening and diagnostic assessment programs from an equity perspective.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.007 | 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 teacher head, 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".