Role of Patient and Disease Factors in Adjuvant Systemic Therapy Decision Making for Early-Stage, Operable Breast Cancer: American Society of Clinical Oncology Endorsement of Cancer Care Ontario Guideline Recommendations
Bibliographic record
Abstract
PURPOSE: An American Society of Clinical Oncology (ASCO) panel considered the Cancer Care Ontario (CCO) recommendations on the role of patient and disease factors in selecting adjuvant therapy for women with early-stage breast cancer for endorsement. METHODS: ASCO staff reviewed the CCO guideline for methodologic rigor, and an ASCO panel of content experts reviewed the content of the recommendations. CCO RECOMMENDATIONS: For making decisions regarding adjuvant therapy, nodal status, tumor size, estrogen receptor (ER), progesterone receptor (PgR), human epidermal growth factor receptor 2 (HER2) status, tumor grade, and lymphovascular invasion are relevant; Oncotype DX score and Adjuvant! Online may be used as risk stratification tools; and age, menopausal status, and medical comorbidities should be considered. Chemotherapy should be considered for patients with positive lymph nodes, ER-negative disease, HER2-positive disease, Adjuvant! Online mortality greater than 10%, grade 3 lymph node-negative tumors (T > 5 mm), triple-negative (ER-negative, PgR-negative, HER2-negative) tumors, lymphovascular invasion positivity, or estimated distant relapse risk of greater than 15% at 10 years based on Oncotype DX recurrence score (RS). Chemotherapy may not be beneficial or required for small node-negative tumors (T < 5 mm) without high-risk features or for patients with HER2-negative, strongly ER-positive, and PgR-positive cancer with micrometastatic nodal disease, T less than 5 mm, or Oncotype DX RS with an estimated distant relapse risk of less than 15% at 10 years. ASCO PANEL CONCLUSION: The ASCO panel endorses the recommendations with minor suggested revisions and highlights three areas that warrant further consideration: tumor histology and adjuvant therapy recommendations, risk stratification tools and proposed Oncotype DX RS thresholds to guide decisions about chemotherapy, and patient factors in decision making.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| 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".