Up-Front Use of Aromatase Inhibitors As Adjuvant Therapy for Breast Cancer: The Emperor Has No Clothes
Bibliographic record
Abstract
nology assessment on adjuvant use of aromatase inhibitors (AIs) was updated to indicate that optimal adjuvant endocrine therapy for post-menopausal women with receptor-positive breast cancer should in-clude an AI, either as up-front therapy or as sequential therapy after tamoxifen.1 This recommendation was on the basis of improved disease-free survival (DFS) observed with AIs, given that no trial at that time had demonstrated improvement in overall survival. This recommendation and thepublicity relating to trials such as theArimi-dex, Tamoxifen, Alone or in Combination (ATAC) trial have had substantial impact worldwide on the endocrine treatment of early breast cancer.2 On the basis of the recent published update of the ATAC trial with a median 8 or more years of follow-up, and the report at the San Antonio Breast CancerMeeting inDecember 2007, advertisements proclaim that the long-term data demonstrate con-tinuing effectiveness for anastrozole over tamoxifen through treat-
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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 | 0.005 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.013 | 0.004 |
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".