Should oncoplastic breast conserving surgery be used for the treatment of early stage breast cancer? Using the GRADE approach for development of clinical recommendations
Bibliographic record
Abstract
INTRODUCTION: The potential advantages of oncoplastic breast conserving surgery (BCS) have not been validated in robust studies that constitute high levels of evidence, despite oncoplastic techniques being widely adopted around the globe. There is hence the need to define the precise role of oncoplastic BCS in the treatment of early breast cancer, with consensual recommendations for clinical practice. METHODS: A panel of world-renowned breast specialists was convened to evaluate evidence, express personal viewpoints and establish recommendations for the use of oncoplastic BCS as primary treatment of unifocal early stage breast cancers using the GRADE approach. RESULTS: According to the results of the systematic review of literature, the panelists were asked to comment on the recommendation for use of oncoplastic BCS for treatment of operable breast cancer that is suitable for breast conserving surgery, with the GRADE approach. Based on the voting outcome, the following recommendation emerged as a consensus statement: Oncoplastic breast conserving surgery should be recommended versus standard breast conserving surgery for the treatment of operable breast cancer in adult women who are suitable candidates for breast conserving surgery (with very low certainty of evidence). DISCUSSION: This review has revealed a low level of evidence for most of the important outcomes in oncoplastic surgery with lack of any randomized data and absence of standard tools for evaluation of clinical outcomes and especially patients' values. Despite areas of controversy, about one-third (36%) of panel members expressed a strong recommendation in support of oncoplastic BCS. Presumably, this reflects a synthesis of views on the relative complexity of these techniques, associated complications, impact on quality of life and costs.
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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 | 0.157 | 0.376 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.005 | 0.010 |
| Bibliometrics | 0.013 | 0.006 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.008 | 0.008 |
| Open science | 0.008 | 0.007 |
| Research integrity | 0.008 | 0.010 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".