Barriers, beliefs and practice patterns for breast cancer reconstruction: A provincial survey
Bibliographic record
Abstract
BACKGROUND: The purpose of this study was to characterize beliefs and practice patterns for breast cancer reconstruction among physicians who treat patients with breast cancer, in order to delineate current clinical practice. This survey was administered prior to Cancer Care Ontario guideline publication. METHOD: Survey questions addressed four domains: survival, delayed or obscured recurrence detection, delayed adjuvant therapy, and aesthetics. The survey was administered to 1160 Ontario plastic and general surgeons and radiation and medical oncologists. Data were compared to published guidelines. RESULTS: The overall response rate was 48%, with 57% of respondents treating breast cancer. Of those treating breast cancer, 75% are affiliated with an academic center. Immediate breast reconstruction (IBR) is not available to 28%. Autologous reconstruction is thought to interfere with recurrence detection by 23% (oncologists 30%, surgeons 19%, p = 0.04). For patients not expected to require radiation therapy, IBR is not supported by 30%. Autologous IBR is believed to delay delivery of adjuvant chemotherapy by 45% (oncologists 55%, surgeons 41%, p = 0.02). Up to 42% of respondents believe delays in adjuvant therapy delivery following IBR are due to insufficient health care resources (ie. coordinating an oncologic and reconstructive surgeon). Radiation therapy following reconstruction is believed to have negative aesthetic outcomes, and increase the need for revision surgery. CONCLUSIONS: Unfavourable beliefs about certain clinical actions do not align with recent provincial guideline recommendations. Insufficient healthcare resources are perceived to be a significant barrier to IBR and timely care.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".