Preferences of Women Evaluating Risks of Tamoxifen (POWER) study of preferences for tamoxifen for breast cancer risk reduction
Bibliographic record
Abstract
BACKGROUND: The objective of this study was to understand the attitudes and preferences of risk-eligible women regarding use of tamoxifen for breast cancer risk reduction. METHODS: A cross-sectional, mixed-methods interview study was conducted at a university medical center and at community sites. Participants were women who had an estimated 5-year breast cancer risk > or = 1.7% and no prior breast cancer. Interviews were conducted in English or Spanish. The interview included a 15-minute, standardized educational session on the potential benefits and harms of tamoxifen followed by close-ended and open-ended questions about participants' inclinations to take tamoxifen and factors important to their decision. A demographic questionnaire, a test on knowledge of potential benefits and harms of tamoxifen, and an interview evaluation were included. RESULTS: Two hundred fifty-five women completed interviews. Their estimated mean 5-year breast cancer risk was 2.8%; and their mean self-perceived 5-year risk was 32.7%. After the educational intervention, 45 women (17.6%) were inclined to take tamoxifen. Very high risk women (> 3.5%) were no more inclined to take it than women with lower risk (1.7-3.5%). In a multivariable analysis, lower income, confidence in the effectiveness of tamoxifen, and concern about fractures were associated with being inclined to take it; concern about pulmonary embolism, dyspareunia, cataracts, and low self-perceived breast cancer risk were associated negatively with taking tamoxifen. Participants expressed concerns about adverse effects. CONCLUSIONS: Less than 20% of women were interested in tamoxifen after education about potential benefits and harms, despite a very high self-perceived breast cancer risk. Candidate chemoprevention agents must have few potential adverse effects to achieve widespread acceptance.
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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 | 0.000 | 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) | 0.002 | 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".