Breast-Conserving Surgery Versus Modified Radical Mastectomy in the Management of Non-metastatic Inflammatory Breast Cancer: A Systematic Review and Meta-Analysis
Bibliographic record
Abstract
Inflammatory breast cancer (IBC) is an uncommon yet particularly aggressive subtype of breast carcinoma. The most effective surgical strategy after multimodality therapy continues to be debated, specifically regarding whether breast-conserving surgery (BCS) provides outcomes equivalent to modified radical mastectomy (MRM). This systematic review and meta-analysis assessed survival outcomes between these two surgical options in non-metastatic IBC. Searches of PubMed, SCOPUS, CENTRAL, Web of Science, and Google Scholar up to April 2019 were searched under Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) and Meta-Analysis of Observational Studies in Epidemiology (MOOSE) guidance. Eligible studies included adults with non-metastatic IBC receiving either BCS or MRM after neoadjuvant chemotherapy (NAC). The data were analyzed with a random-effects model. Six studies with 11,252 patients were included. The combined analysis of overall survival (OS) favored mastectomy (RR = 0.88, 95% CI: 0.79-0.98; p = 0.02) without heterogeneity (I² = 0%). Hazard ratio analysis (HR = 0.89, 95% CI: 0.74-1.07; p = 0.22) and breast-cancer-specific survival (BCSS; HR = 0.89, 95% CI: 0.73-1.09; p = 0.27) showed no significant difference. Overall, MRM remains the preferred surgical approach, though BCS can be considered in highly selected cases showing an excellent response to neoadjuvant therapy. Further randomized trials are necessary to refine selection criteria and validate long-term oncologic safety. The findings support MRM as the standard, with BCS viable for selected patients achieving excellent neoadjuvant response.
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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 | 0.010 | 0.023 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.019 | 0.040 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| 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".