Taking control of cancer: Women’s choice for mastectomy.
Bibliographic record
Abstract
11 Background: Rates of both unilateral (UM) and contralateral prophylactic mastectomy (CPM) for early stage breast cancer (ESBC) have been increasing since 2003. Studies suggest that the increase is due to women playing an active role in decision-making. We do not know what factors are influencing the choice for more extensive surgery. Methods: To identify these factors we completed a multi-method study; conducting a systematic review of quantitative literature and qualitative interviews. Decision-making literature was identified from 5 databases and underwent thematic analysis. Purposive sampling identified women across the Toronto Area (Ontario, Canada), who were suitable candidates for breast conserving surgery (BCS) but underwent UM or CPM. Data saturation was achieved after 29 in-person interviews. Constant comparative analysis identified key concepts and themes. Results: ‘Taking control of cancer’ was the dominant theme. Literature illustrated that patients markedly overestimate risk of local recurrence, contralateral cancer and particularly, mortality. Similarly, interviews revealed that fear of breast cancer was expressed at diagnosis and drives the decision-making process. Despite surgeons discussing survival equivalence of BCS and UM, patients chose UM due to fear of recurrence and an overestimated survival advantage. Similarly, patients chose CPM to eliminate contralateral cancer and a misperceived survival benefit. Women were actively trying to Control Outcomes, as more surgery was believed to offer greater survival and therefore greater control. Conclusions: Both the literature and our interviews have illustrated that women seek UM and CPM for treatment of their ESBC to manage their fear of cancer mortality by undergoing more extensive surgery; this in turn drives mastectomy rates. It is important to understand this process so that we may improve our ability to communicate issues of importance to women and facilitate informed decision-making.
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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 | 0.006 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| 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".