Safety and Accuracy of Sentinel Lymph Node Biopsy Alone in Clinically Node-Positive Patients Undergoing Upfront Surgery for Invasive Breast Cancer: A Systematic Review
Bibliographic record
Abstract
Landmark trials (Z0011 and AMAROS) have demonstrated that axillary lymph node dissection (ALND) can be safely omitted in patients with breast cancer and 1-2 positive sentinel nodes. Extrapolating from these and other cardinal studies such as NSABP B-04, guidelines state that patients with 1-2 needle biopsy-proven positive lymph nodes undergoing upfront surgery can have sentinel lymph node biopsy (SLNB) alone. The purpose of this study is to systematically review the literature to identify studies examining the direct application of SLNB in such patients. EMBASE and Ovid MEDLINE were searched from inception to 3 May 2022. Studies including patients with nodal involvement confirmed on pre-operative biopsy and undergoing SLNB were identified. Studies with neoadjuvant chemotherapy were excluded. Search resulted in 2518 records, of which 68 full-text studies were reviewed, ultimately yielding only 2 studies meeting inclusion criteria. Both studies used targeted axillary surgery (TAS) with pre-operative localization of the biopsy-proven positive node in addition to standard SLNB techniques. In a non-randomized single-center prospective study, Lee et al. report no regional recurrences in patients undergoing TAS or ALND, and no difference in distant recurrence or mortality at 5 years. In the prospective multicenter TAXIS trial by Webber et al., the median number of positive nodes retrieved with TAS in patients undergoing upfront surgery was 2 (1, 4 IQR). Within the subset of patients who underwent subsequent ALND, 61 (70.9%) had additional positive nodes, with 26 (30.2%) patients having ≥4 additional positive nodes. Our review demonstrates that there is limited direct evidence for SLNB alone in clinically node-positive patients undergoing upfront surgery. Available data suggest a high proportion of patients with residual disease in this setting. While the totality of the data, mostly indirect evidence, suggests SLNB alone may be safe, we call on clinicians and researchers to prospectively collect data on this patient population to better inform decision-making.
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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 | 0.008 | 0.035 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.010 | 0.008 |
| Bibliometrics | 0.007 | 0.007 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| 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".