Adjuvant Endocrine Therapy for Women With Hormone Receptor–Positive Breast Cancer: ASCO Clinical Practice Guideline Focused Update
Bibliographic record
Abstract
PURPOSE: To update the ASCO clinical practice guideline on adjuvant endocrine therapy based on emerging data about the optimal duration of aromatase inhibitor (AI) treatment. METHODS: ASCO conducted a systematic review of randomized clinical trials from 2012 to 2018. Guideline recommendations were based on the Panel's review of the evidence from six trials. RESULTS: The six included studies of AI treatment beyond 5 years of therapy demonstrated that extension of AI treatment was not associated with an overall survival advantage but was significantly associated with lower risks of breast cancer recurrence and contralateral breast cancer compared with placebo. Bone-related toxic effects were more common with extended AI treatment. RECOMMENDATIONS: The Panel recommends that women with node-positive breast cancer receive extended therapy, including an AI, for up to a total of 10 years of adjuvant endocrine treatment. Many women with node-negative breast cancer should consider extended therapy for up to a total of 10 years of adjuvant endocrine treatment based on considerations of recurrence risk using established prognostic factors. The Panel noted that the benefits in absolute risk of reduction were modest and that, for lower-risk node-negative or limited node-positive cancers, an individualized approach to treatment duration that is based on considerations of risk reduction and tolerability was appropriate. A substantial portion of the benefit for extended adjuvant AI therapy was derived from prevention of second breast cancers. Shared decision making between clinicians and patients is appropriate for decisions about extended adjuvant endocrine treatment, including discussions about the absolute benefits in the reduction of breast cancer recurrence, the prevention of second breast cancers, and the impact of adverse effects of treatment. Additional information can be found at www.asco.org/breast-cancer-guidelines .
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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 | 0.011 | 0.037 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.005 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.007 | 0.006 |
| Insufficient payload (model declined to judge) | 0.004 | 0.003 |
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".