Impact of socio‐economic status on breast cancer screening in women with diabetes: a population‐based study
Bibliographic record
Abstract
AIMS: There is evidence to suggest that mammography rates are decreased in women with diabetes and in women of lower socio-economic status. Given the strong association between low socio-economic status and diabetes, we explored the extent to which differences in socio-economic status explain lower mammography rates in women with diabetes. METHODS: A population-based retrospective cohort study in Ontario, Canada, of women aged 50 to 69 years with diabetes between 1999 and 2010 age matched 1:2 to women without diabetes. Main outcome measure is the likelihood of at least one screening mammogram in women with diabetes within a 36-month period, starting as of either 1 January 1999, their 50th birthday, or 2 years after diabetes diagnosis--whichever came last. Outcomes were compared with those in women without diabetes during the same period as their matched counterparts, adjusting for socio-economic status based on neighbourhood income and other demographic and clinical variables. RESULTS: Of 504,288 women studied (188,759 with diabetes, 315,529 with no diabetes), 63.8% had a screening mammogram. Women with diabetes were significantly less likely to have a mammogram after adjustment for socio-economic status and other factors (odds ratio 0.79, 95% CI 0.78-0.80). Diabetes was associated with lower mammogram use even in women from the highest socio-economic status quintile (odds ratio 0.79, 95% CI 0.75-0.83). CONCLUSIONS: The presence of diabetes was an independent barrier to breast cancer screening, which was not explained by differences in socio-economic status. Interventions that target patient, provider, and health system factors are needed to improve cancer screening in this population.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.001 | 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 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".