A systematic review of vascularised lymph node transfer in combination with autologous free flap breast reconstruction for breast cancer-related lymphedema
Bibliographic record
Abstract
Background: Breast cancer-related lymphedema (BRCL) has a significant disease burden on breast cancer survivors. However, there is no consensus on the treatment of BRCL. Lymphovascular microsurgery and vascularized lymph node transfer (VLNT) have emerged as promising treatments to alleviate the symptoms of BRCL. The objective of this systematic review is to provide an up-to-date evidence for the effectiveness and safety of using VLNT in conjunction with free-flap breast reconstruction to manage BCRL. Methods: Two independent authors conducted a search strategy across Embase, Medline, and Web of Science. All articles within the last 30 years were included in this review. Case reports with fewer than 10 cases were excluded. The Newcastle-Ottawa Scale was used to assess the risk of bias. Primary outcomes included patients who stopped or reduced their reliance on compression therapy, arm circumference, and the difference in arm volume. Secondary outcomes included complication profiles and Quality of Life (QOL) scores. This review was registered under PROSPERO (ID: CRD420251017699). Results: A total of 15 out of 880 studies were included in this review. Most surgical procedures utilised lymph nodes from the superficial circumflex iliac or inferior epigastric systems, with the thoracodorsal vessels serving as the common recipient vessels. Patients demonstrated improvements in limb volume and arm circumference (range 11–20.6% in 4/15 studies), as well as a reduction in dependence on compression garments (6/15 studies). QOL measures also improved, with notable decreases in pain, heaviness, and infection rates (4/15 studies). One study reported an improvement in the incidence of cellulitis from 6.7±1.7 to 8.6±1.4 (P=0.01). Nevertheless, reverse lymphatic mapping was a key component to minimise donor-site morbidity. The combined VLNT and free-tissue transfer approach consolidates breast reconstruction and lymphedema treatment into a single surgery, potentially improving functional and aesthetic outcomes while reducing healthcare burden. Although early and mid-term outcomes are encouraging, long-term data to assess effectiveness remain limited. Conclusions: VLNT with autologous breast reconstruction represents an integrative surgical strategy for managing BCRL. Careful patient selection, reverse lymphatic mapping, and further studies are crucial for optimising outcomes and establishing long-term efficacy.
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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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| 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".