Conservation Surgery for Breast Cancer As the Preferred Choice: A Prospective Analysis
Bibliographic record
Abstract
PURPOSE: To describe the proportion of women who anticipate having breast-conserving surgery (BCS) versus modified radical mastectomy (MRM), the factors they considered when making treatment choices, the degree to which they perceived they had participated in and had control of the treatment decision, and to explore factors associated with type of planned surgery. PATIENTS AND METHODS: Prospective cohort study conducted among patients attending a tertiary care hospital in Alberta, Canada from 1992 to 1995. Participants had a first diagnosis of localized unilateral breast cancer, and were, in the opinions of their surgeons, candidates for either BCS or MRM. RESULTS: Of 157 participants, 71.3% anticipated having BCS and 28.7% anticipated MRM. Referents perceived to play an important role in decision making included self, doctor, and significant other. The two top-ranked items perceived to have influenced treatment choice were doctor's advice and possibility of complete cure. Most women (60%) participated in treatment choice to the degree that they preferred, but only 13.6% received their preferred amount of information. The type of planned surgery was predicted by surgeon, contribution of doctor to choice of treatment, importance of breasts to sexuality, self-efficacy, and concerns about cancer recurrence from a multivariable logistic regression model. CONCLUSION: Both patient and surgeon factors are important predictors of type of planned surgery. There is a gap between women's preferences and actual experiences with regard to information provided and patient participation in treatment choices, with women's desire for more information about their treatment being most prevalent.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".