Patient opinions on contralateral prophylactic mastectomy: A patient-driven discussion in need of tuning?
Bibliographic record
Abstract
BACKGROUND: Rates of contralateral prophylactic mastectomy (CPM) are increasing among women with unilateral breast cancer despite low rates of contralateral recurrence and lack of survival benefit. We aimed to investigate the decisional needs and supports required to ensure adequate and quality decision-making by patients with breast cancer facing the decision regarding CPM. METHODS: In this qualitative study, we used semistructured interviews developed with the use of the Ottawa Decision Support Framework to investigate the decisional needs and supports of women (aged > 18 yr) with nonhereditary breast cancer who had previously discussed CPM with their care provider. Patients were recruited from 2 academic cancer centres in Toronto, Ontario. Interviews were conducted between June 2016 and October 2017. We analyzed responses to the open-ended questions iteratively and inductively to establish major themes within the results. RESULTS: Ten patients were recruited. Eight patients reported having initiated the discussion about CPM. Although most patients reported feeling supported, 6 mentioned some degree of decisional conflict. Cancer risk reduction was the most commonly reported perceived benefit of CPM (9 patients), followed by improved psychologic well-being (7). Most patients (8) did not mention the lack of survival benefit of CPM as a disadvantage of the procedure. Patients indicated that information resources (in 8 cases) and improved counselling from their health care team (in 7) would assist in decision-making. CONCLUSION: Our findings illustrate the disconnect between true and perceived risks (i.e., surgical risk) and benefits (potential recurrence and survival benefit) of CPM, which is not being managed adequately despite support from the health care team. A decision aid may address unmet patient need by providing a reliable resource regarding the benefits and risks of this procedure, while helping patients understand their values and realign their expectations.
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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 | 0.022 | 0.038 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.010 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.004 | 0.006 |
| Insufficient payload (model declined to judge) | 0.003 | 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".