Reassessing the role of axillary lymph-node dissection in patients with early-stage breast cancer.
Bibliographic record
Abstract
INTRODUCTION: There is considerable controversy regarding the value of axillary lymph-node dissection in the adjuvant systemic therapy of patients with early-stage breast cancer. Our objective was to assess the impact of nodal status in assigning adjuvant chemotherapy to these patients. METHODS: We carried out a review of all patients with stage I or II breast cancer treated at 3 university-affiliated hospitals in Saskatoon between Jan. 1, 1998, and Dec. 31, 2000. Data collected included: patient age, sex, tumour size, hormone receptor status, nuclear grade and presence of lymphovascular invasion. Patients were categorized as being at low, high or intermediate risk for recurrence based on Canadian consensus guidelines and at low or high risk according to criteria established by the United States National Institutes of Health (NIH). The influence of nodal status on subsequent treatment was determined assuming that all patients younger than 70 years at high risk of recurrence would receive chemotherapy. RESULTS: We identified 327 women with stage I or II breast cancer in whom all prognostic factors were available for analysis. Applying the Canadian criteria to determine the need for adjuvant chemotherapy, 68% of women would receive chemotherapy regardless of lymph-node status. Applying the NIH criteria, 82.5% of women younger than 70 years would receive adjuvant chemotherapy regardless of nodal status. CONCLUSIONS: Nodal status has little influence on subsequent management. Adoption of a selective approach to axillary lymph-node dissection could avoid the potential morbidities of this procedure in many patients with early-stage breast cancer.
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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 | 0.003 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".