Breast Cancer Risk Perception Among Women Who Have Undergone Prophylactic Bilateral Mastectomy
Bibliographic record
Abstract
BACKGROUND: Prophylactic bilateral mastectomy is a preventive option for women who are at high risk of developing breast cancer. We compared the perceptions of breast cancer risk among women who had previously undergone prophylactic bilateral mastectomy with objective estimates of their breast cancer risk. METHODS: We asked 75 women in the Canadian province of Ontario who had undergone prophylactic bilateral mastectomy between 1991 and 2000 to provide a complete family history of the cancers that had occurred by the time of their surgery and to indicate their BRCA1 and BRCA2 gene mutation status. This information was used to generate estimates of each woman's risk for breast cancer by using the Gail model, the Claus model, and the BRCAPRO model. Sixty of the women also provided their own estimates of their lifetime risks of developing breast cancer before and after they had prophylactic mastectomy. Risk estimates were compared using Wilcoxon's signed-rank test and Pearson's product-moment correlation analysis. All statistical tests were two-sided. RESULTS: The women estimated that their lifetime risk of developing breast cancer before surgery was, on average, 76% (range = 20%-100%) and after surgery was 11.4% (range = 0%-60%). The mean estimated absolute risk reduction the women attributed to prophylactic mastectomy was 64.8%. The average computer-generated risk estimates were 59% for the 14 women who reported that they carried a BRCA1 or BRCA2 gene mutation and 17% for the other women (of whom 43 had a strong family history of breast cancer and 18 had a limited family history). Breast cancer risk was statistically significantly overestimated by all women except for the known BRCA1 and BRCA2 gene mutation carriers. CONCLUSION: Women who undergo prophylactic bilateral mastectomy have an exaggerated perception of their breast cancer risk before surgery. Formal genetic counseling and genetic testing may result in more accurate risk perceptions to guide women in choosing other preventive options.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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) | 0.002 | 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".