Summary of aromatase inhibitor clinical trials in postmenopausal women with early breast cancer
Bibliographic record
Abstract
Five years of adjuvant therapy with tamoxifen was considered the gold-standard treatment for postmenopausal women with estrogen receptor-positive breast cancer for many years. Data from a core group of clinical trials investigating the safety and efficacy of aromatase inhibitors (AIs) have challenged this perception. These studies were designed to evaluate the safety and efficacy of AIs in the following clinical settings: 1) as initial adjuvant therapy (the Arimidex, Tamoxifen, Alone or in Combination trial, Breast International Group Trial 1-98), 2) in a "switched setting" after 2 to 3 years of treatment with tamoxifen (Arimidex-Nolvadex 95, the Austrian Breast and Colorectal Cancer Study Group 8 [ABCSG 8] trial, the Italian Tamoxifen Anastrozole study, the Intergroup Exemestane Study), and 3) in extended settings (National Cancer Institute of Canada Trial MA.17, ABCSG 6a, National Surgical Adjuvant Breast and Bowel Project 33). The efficacy data from these studies suggested that AIs have added substantial benefit in terms of disease outcome. AIs were tolerated well, and patients who received them experienced fewer thrombolic events and less endometrial cancer, hot flashes, night sweats, and vaginal bleeding compared with patients who receive tamoxifen. However, patients who received tamoxifen had less skeletal events and accelerated bone resorption compared with women who received AIs. AIs should be considered when planning a patient's endocrine therapy, taking into account the differences in tolerability and end-organ effects of the classes of endocrine therapy. Outstanding issues to optimize AI therapy include identifying the optimal duration, agent, and patients for these therapies.
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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 | 0.015 | 0.012 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.005 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
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".