Information for decision making by post-menopausal women with hormone receptor positive early-stage breast cancer considering adjuvant endocrine therapy
Bibliographic record
Abstract
PURPOSE: To identify the information that post-menopausal women with hormone-receptor positive, early-stage breast cancer want, to help them decide among six treatment options for adjuvant-endocrine therapy. METHODS: We surveyed women with early-stage breast cancer who were eligible for adjuvant endocrine-therapy 3-18 months earlier. Participants rated the importance of getting each of 95 questions answered before this decision is made (options: essential/desired/not important/avoid). For questions rated essential or desired, participants identified the purpose(s) for having the question answered: to help them understand, make the decision, plan, or other. Participants indicated the role they played in their actual decision and the role they would prefer if the decision was made today. They also indicated whether they felt they had had a choice of endocrine therapy treatments. RESULTS: 188 of 343 questionnaires were returned (response rate 55%). Mean age was 67 yr (range 38-88 yr); 76% were married, and 39% had secondary school education or less. On average, respondents rated 18 questions (range 0-94) essential for decision making. Each question was rated essential for decision making by ≥ 7% of participants but only 1 question by >50%. Regarding roles, 89% of respondents had participated in their actual decision and would want to again; an additional 9% had not participated in their actual decision but would want to at the time of the survey. The percentage of respondents who felt they had no choice of endocrine therapy treatments varied between centres, 25% vs 41% and 49%. CONCLUSIONS: Most patients want to participate in the decision but they vary widely in the amount and which specific details they want to help them make the decision. IMPLICATION: The wide variation in questions considered important means the support should be tailored to the needs of the individual patient.
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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 | 0.000 | 0.000 |
| 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".