Appraising Adjuvant Endocrine Therapy in Hormone Receptor Positive HER2-Negative Breast Cancer—A Literature Review
Bibliographic record
Abstract
BACKGROUND: Approximately 75% of breast cancer (BC) is associated with luminal differentiation expressing endocrine receptors (ER). For ER+ HER2- tumors, adjuvant endocrine therapy (ET) is the cornerstone treatment. Although relapse events steadily continue, the ET benefits translate to dramatically lengthen life expectancy with bearable side-effects. This review of ER+ HER2- female BC outlines suitable adjuvant treatment strategies to help guide clinical decision making around appropriate therapy. METHODS: A literature search was conducted in Embase, Medline, and the Cochrane Libraries, using ER+ HER-, ET BC keywords. RESULTS: In low-risk patients: five years of ET is the standard option. While Tamoxifen remains the preferred selection for premenopausal women, AI is the choice for postmenopausal patients. In the high-risk category: ET plus/minus OFS with two years of Abemaciclib is recommended. Although extended ET for a total of ten years is an alternative, the optimal AI duration is undetermined; nevertheless an additional two to three years beyond the initial five years may be sufficient. In this postmenopausal group, bisphosphonate is endorsed. CONCLUSIONS: Classifying the risk category assists in deciding the treatment route and its optimal duration. Tailoring the breadth of ET hinges on a wide array of factors to be appraised for each individualized case, including weighing its benefits and harms.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 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".