Organized breast screening improves reattendance compared to physician referral: a case control study
Bibliographic record
Abstract
BACKGROUND: The Ontario Breast Screening Program (OBSP) is a population-based breast screening programme, not requiring physician referral. OBSP invites women by mail to book their next screens. However, women who do not participate in the OBSP, may be referred by physicians to non-OBSP mammography facilities, which do not remind women to book their next screen. METHODS: We identified women without breast cancer prior to June 30, 2011, having bilateral mammography (M) during a baseline period at age 50 - 69 at OBSP or non-OBSP facilities, and during a re-exposure period, at the same facility type. We used a case-control design to study the association of facility type and having M during an outcome period. Cases were women failing to receive the outcome M. Controls were matched by age, census tract, and socioeconomic status. Exposure was baseline facility type. Covariates were comorbidity, residential mobility, and primary care physician (PCP) characteristics. Conditional logistic regression analysis was performed. RESULTS: Cases were less likely to have been screened at OBSP facilities. Failure to receive the outcome M was associated with having moved after re-exposure M (OR = 1.61, 95% confidence interval (CI) 1.52, 1.71), having a male PCP (OR = 1.05, 95% CI 1.02, 1.05), or a higher Charlson score (OR = 1.06 per unit increase, 95% CI 1.03, 1.09). Having re-exposure M at an OBSP facility (OR = 0.18, 95% CI 0.18, 0.19)., having a Canadian trained PCP (OR = 0.83, 95% CI 0.8, 0.87), and having a PCP one year after the re-exposure M (OR = 0.81, 95% CI 0.68, 0.97) were protective against failure to receive the outcome M. CONCLUSIONS: The OBSP, not requiring physician referral, and inviting women by mail to book their next screen, is associated with a lower probability of failure to reattend for subsequent screening than screening by PCP referral to non-OBSP facilities.
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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 | 0.005 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".