Breast Reconstruction in De Novo Metastatic Breast Cancer: A Systematic Review
Bibliographic record
Abstract
Background: Breast reconstruction in de novo metastatic breast cancer (dnMBC) patients is a viable option. There remains no consensus on recommendations. We summarize postreconstruction clinical outcomes in dnMBC patients to identify surgical candidates. Methods: A systematic review was conducted across PubMed/MEDLINE, Scopus, and Web of Science from January 1, 1990, to November 1, 2024. The study methods were in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. Data on patient demographics, disease characteristics, oncological treatment, surgical details, and clinical outcomes were collected. Results: A total of 7 studies (2635 breast cancer survivors) were identified. The average (SD) age was 47.5 (2.35) years, and most participants were White (n = 2080, 79.3%). Across studies, 39.0% (n = 761) of patients underwent implant-based reconstruction, 38.8% (n = 757) autologous reconstruction, 5.99% (n = 117) combined reconstruction, and 16.4% (n = 320) were not specified. Most cancers were invasive ductal carcinoma (81.3%) with estrogen-positive (73.1%) or progesterone-positive (48.4%) receptors and human epidermal growth factor receptor 2-positive (33.7%) status. Primary tumors most often metastasized to bone (44.4%) or lymph nodes (38.5%). Overall survival and breast cancer-specific survival rates were prolonged among reconstructed patients without increased predilection for complications or delay in tumor treatment. Conclusions: Reconstruction in dnMBC patients is an appropriate option, especially among younger patients with oligometastatic disease. Future studies are encouraged to investigate the impact on well-being and prolonged survival rates, which primarily seem to be limited to those with low disease burden and hormone receptor-positive tumor subtypes.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.012 | 0.002 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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; both teacher heads agree on what is shown here.
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".