Perioperative Drug Management of Systemic Therapies in Breast Cancer: A Literature Review and Treatment Recommendations
Bibliographic record
Abstract
Breast cancer accounts for about 30% of all new female cancers each year, and its incidence is increasing 0.6% per year. An enhanced understanding of the molecular mechanisms of carcinogenesis has led to the development of constantly evolving strategies for local and systemic therapies. Perioperative chemotherapy, immunotherapy, and endocrine therapy play pivotal roles in the overall treatment plan. Guidelines on the appropriate use of these drugs in patients undergoing extirpative breast surgery and/or breast reconstruction are lacking. Clear indications for the management of systemic therapies relative to the timing of surgery is crucial to ensure consistent treatment outcomes and to minimize complications. Our purpose is to propose evidence-based recommendations to optimize the perioperative management of systemic therapies in patients undergoing breast cancer surgery and breast reconstructive surgery. In this review, we outline the basic tenets of breast cancer therapies, provide an overview on wound-healing principles, delineate relevant pharmacodynamic concepts, summarize literature and pharmacologic data from various preclinical studies and clinical trials, and propose treatment recommendations. Synopsis: This review proposes evidence-based recommendations regarding systemic therapies management for outcome optimization in the perioperative period in breast cancer patients.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".