Accuracy and Outcomes of Sentinel Lymph Node Biopsy in Male with Breast Cancer: A Narrative Review and Expert Opinion
Bibliographic record
Abstract
Male breast cancer (MBC) is a rare disease, accounting for less than 1% of all breast cancer cases. Sentinel lymph node biopsy (SLNB) has emerged as a less invasive alternative to axillary lymph node dissection (ALND) for axillary staging in breast cancer, offering reduced morbidity and comparable accuracy. However, the application of SLNB in MBC remains underexplored, with limited male-specific data and treatment protocols often extrapolated from female breast cancer studies. Available evidence suggests that SLNB in men demonstrates high diagnostic accuracy, with low false-negative rates and a high sentinel lymph node identification rate. Despite this, there is ongoing debate about its long-term impact on clinical outcomes, particularly for patients with sentinel node metastasis, where ALND may still provide superior survival outcomes in some cases. Predictive tools are being developed to identify better patients who may benefit from SLNB alone, potentially reducing the need for more invasive procedures. As the role of SLNB continues to evolve in MBC management, further prospective research is needed to refine its application and assess its long-term oncologic outcomes.
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 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) | 0.004 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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".