Prognostic significance of residual nodal disease after neoadjuvant endocrine therapy for hormone receptor-positive breast cancer
Bibliographic record
Abstract
Axillary management after NET has not been well studied and the significance of residual axillary node disease after NET remains uncertain. We used the National Cancer Data Base to examine the prognostic significance of residual nodal disease after NET. From 2010-2016, 4,496 patients received NET for cT1-3N0-1M0 hormone receptor-positive, HER2-negative breast cancer. Among cN0 patients treated with NET, final node status was ypN0 in 65%, isolated tumor cells (ITCs) in 3%, ypN1mi in 6%, and ypN1 in 26%. In cN1 patients, nodal pathologic complete response was uncommon (10%), and residual nodal disease included ITCs in 1%, ypN1mi in 3%, and ypN1 in 86%. There were no differences in 5-year overall survival (OS) between patients with pathologic node-negative disease, ITCs, or micrometastases after NET. When compared to a matched cohort of upfront surgery patients, there were also no differences in 5-year OS between NET and upfront surgery patients for any residual nodal disease category. These findings suggest NET patient outcomes mirror those of upfront surgery patients and present an opportunity to consider de-escalation of axillary management strategies in NET patients.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 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".