The Attitudes of Women with BRCA1 and BRCA2 Mutations toward Clinical Breast Examinations and Breast Self-Examinations
Bibliographic record
Abstract
AIMS: In screening studies of women with BRCA mutations, magnetic resonance imaging (MRI) plus mammography has >90% sensitivity for detecting breast cancer, with negligible benefit from the addition of breast self-examination (BSE) or clinical breast examination (CBE). Yet CBE is still frequently recommended, and BSE is encouraged for these women. We sought to determine the attitudes of high-risk women toward CBE and BSE. METHODS: Between November 2005 and May 2006, 137 women with BRCA mutations participating in a screening study consisting of annual MRI and mammography plus semiannual CBE were asked to complete a mailed Likert-type questionnaire. RESULTS: Of the 94 (67%) respondents, mean age 47 (range 28-67), 94% strongly agreed or agreed that CBE was an important way to detect breast cancer, and almost all believed it provided an important connection to the healthcare team. Only 10% said it increased anxiety. Of the 71 (77%) who performed BSE at least occasionally, 53 thought that regular BSE gave them a sense of control over their own health. Of the 21(23%) who did not practice BSE at all, only 3 did not believe that BSE was helpful, and it made 9 more worried about breast cancer CONCLUSIONS: Although CBE adds little to cancer detection rates in women with BRCA mutations screened with MRI, the majority of these women considered CBE to be reassuring and an important means of connecting with the healthcare team. Compliance with BSE was only moderate, but it gave a significant proportion of women a greater sense of control.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".