Efficacy and safety of oncoplastic breast-conserving surgery versus conventional breast-conserving surgery: An updated meta-analysis
Bibliographic record
Abstract
INTRODUCTION: Breast cancer is the most common cancer among women. The surgical treatment of breast cancer has transitioned progressively from radical mastectomy to breast-conserving surgery. In this meta-analysis, we are aiming to compare oncoplastic breast-conserving surgery (OS) with conventional breast-conserving surgery (BCS) in terms of efficacy and safety. METHODS: We searched Medline, Web of Science, Embase, Cochrane databases, Clinicaltrial.gov, and CNKI until April 30, 2024. Data from cohort studies and randomized controlled trials (RCTs) were included. Outcomes included primary outcomes (re-excision, local recurrence, positive surgical margin, mastectomy), secondary outcomes and safety outcomes. The Cochrane Risk of Bias Assessment Tool and Newcastle-Ottawa Scale were used to evaluate the quality of outcomes. RESULTS: Our study included 52 studies containing 46,835 patients. Primary outcomes comprise re-excision, local recurrence, positive surgical margin, and mastectomy, there were significant differences favoring OS over BCS (RR 0.68 [0.56, 0.82], RR 0.62 [0.47, 0.82], RR 0.76 [0.59, 0.98], RR 0.66 [0.44, 0.98] respectively), indicating superior efficacy of OS. Additionally, OS demonstrated significant aesthetic benefits (RR 1.17 [1.03, 1.33] and RR 1.34 [1.18, 1.52]). While total complications were significantly fewer in the OS group (RR 0.70 [0.53, 0.94]), the differences in specific complications were not significant. Furthermore, subgroup analyses were conducted based on nationality, sample size, quality, and type. CONCLUSION: OS demonstrates either superior or at least comparable outcomes across various aspects when compared to BCS.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.018 | 0.035 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.017 | 0.061 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.000 | 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) | 0.005 | 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".