Does perceived risk predict breast cancer screening use? Findings from a prospective cohort study of female relatives from the Ontario site of the Breast Cancer Family Registry
Bibliographic record
Abstract
While the relationship between perceived risk and breast cancer screening use has been studied extensively, most studies are cross-sectional. We prospectively examined this relationship among 913 women, aged 25-72 with varying levels of familial breast cancer risk from the Ontario site of the Breast Cancer Family Registry. Associations between perceived lifetime breast cancer risk and subsequent use of mammography, clinical breast examination (CBE) and genetic testing were assessed using logistic regression. Overall, perceived risk did not predict subsequent use of mammography, CBE or genetic testing. Among women at moderate/high familial risk, those reporting a perceived risk greater than 50% were significantly less likely to have a CBE (odds ratio (OR) = 0.52, 95% confidence interval (CI): 0.30-0.91, p = 0.04), and non-significantly less likely to have a mammogram (OR = 0.70, 95% CI: 0.40-1.20, p = 0.70) or genetic test (OR = 0.61, 95% CI: 0.34-1.10, p = 0.09) compared to women reporting a perceived risk of 50%. In contrast, among women at low familial risk, those reporting a perceived risk greater than 50% were non-significantly more likely to have a mammogram (OR = 1.13, 95% CI: 0.59-2.16, p = 0.78), CBE (OR = 1.11, 95% CI: 0.63-1.95, p = 0.74) or genetic test (OR = 1.29, 95% CI: 0.50-3.33, p = 0.35) compared to women reporting a perceived risk of 50%. Perceived risk did not significantly predict screening use overall, however this relationship may be moderated by level of familial risk. Results may inform risk education and management strategies for women with varying levels of familial breast cancer risk.
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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 | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".