Exploring Reasons for Overuse of Contralateral Prophylactic Mastectomy in Canada
Bibliographic record
Abstract
Background: Contralateral prophylactic mastectomy (CPM) in women with known unilateral breast cancer (BCA) has been increasing despite the lack of supportive evidence. The purpose of the present study was to identify the determinants of CPM in women with unilateral BCA. Methods: This qualitative descriptive study used semi-structured interviews informed by the Theoretical Domains Framework. We interviewed 74 key informants (surgical oncologists, plastic surgeons, medical oncologists, radiation oncologists, nurses, women with BCA) across Canada. Interviews were analyzed using thematic analysis and an analysis for shared and discipline-specific beliefs. Results: In total, 58 factors influencing the use of CPM were identified: 26 factors shared by various health care professional groups, 15 discipline-specific factors (identified by a single health care professional group), and 17 factors shared by women with unilateral BCA. Health care professionals identified more factors discouraging the use of CPM (n = 26) than encouraging its use (n = 15); women with BCA identified more factors encouraging use of CPM (n = 12) than discouraging its use (n = 5). The factor most commonly identified by health care professionals that encouraged CPM was lack of awareness of existing evidence or guidelines for the appropriate use of CPM (n = 44, 75%). For women with BCA, the factor most likely influencing their decision for CPM was wanting a better esthetic outcome (n = 14, 93%). Conclusions: Multiple factors discouraging and encouraging the use of CPM in unilateral BCA were identified. Those factors identify potential individual, team, organization, and system targets for behaviour change interventions to reduce CPM.
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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 | 0.002 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.005 | 0.003 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".