Reducing income-related inequities in colorectal cancer screening: lessons learned from a retrospective analysis of organised programme and non-programme screening delivery in Winnipeg, Manitoba
Bibliographic record
Abstract
OBJECTIVE: We examined organised colorectal cancer (CRC) screening programme and non-programme faecal occult blood test (FOBT) use from 2008 to 2012 for individuals living in Winnipeg, Manitoba, by area-level income. SETTING: Winnipeg, Manitoba, a region with universal healthcare and an organised CRC screening programme. PARTICIPANTS: Individuals who had a non-programme FOBT were identified from the Provincial Medical Claims database. Individuals who had a programme FOBT were identified from the provincial screening registry. Census data were used to determine average household income based on area of residence. STATISTICAL ANALYSIS: Trends in age-standardised FOBT rates were examined using Joinpoint Regression. Logistic regression was performed to explore the association between programme and non-programme FOBT use and income quintile. RESULTS: FOBT use (non-programme and programme) increased from 32.2% in 2008 to 41.6% in 2012. Individuals living in the highest income areas (Q5) were more likely to have a non-programme FOBT compared with those living in other areas. Individuals living in areas with the lowest average income level (Q1) were less likely to have had programme FOBT than those living in areas with the highest average income level (OR 0.80, 95% CI 0.77 to 0.82). There was no difference in programme FOBT use for individuals living in areas with the second lowest income level (Q2) compared with those living in areas with the highest. Individuals living in areas with a moderate-income level (Q3 and Q4) were more likely to have had a programme FOBT compared with those living in an area with the highest income level (OR 1.12, 95% CI 1.09 to 1.15 for Q3 and OR 1.10, 95% CI 1.07 to 1.13 for Q4). CONCLUSIONS: Inequities by income observed for non-programme FOBTs were largely eliminated when programme FOBTs were examined. Targeted interventions within organised screening programmes in very low-income areas are needed.
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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 | 0.003 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| 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".