Refining the postmenopausal breast cancer treatment paradigm: the FACE trial
Bibliographic record
Abstract
It is clear that letrozole and anastrozole provide significant benefits for patients with breast cancer. However, possible differences in efficacy have been suggested by varying degrees of aromatase inhibition and effectiveness in the neoadjuvant and first-line settings. Analyses of aromatase inhibitor-treated patient subgroups within the Arimidex, Tamoxifen, Alone or in Combination trial and Breast International Group 1-98 trial, and the National Cancer Institute of Canada Clinical Trials Group's MA.17 study, have also suggested some differences in efficacy. The question is how best to maximize these differences to benefit specific patient subgroups, such as postmenopausal women with node-positive disease. Nodal status is one of the strongest prognostic factors for breast cancer recurrence and several studies have shown that patients with node-positive disease are at higher risk for early relapse. It is thought that patients at increased risk for early relapse may be better treated with an aromatase inhibitor upfront, but the guidelines are unclear as to which aromatase inhibitor should be used. To answer this important question quickly, the Femara Anastrozole Clinical Evaluation (FACE) trial is recruiting node-positive patients and randomizing them to receive either early adjuvant letrozole or early adjuvant anastrozole. The trial has been designed to differentiate between the two drugs in the shortest possible time frame by using patients at increased risk of early recurrence of breast cancer, so that the required number of events to initiate analysis will be obtained more quickly. In total, 4000 patients who have recently undergone surgery for node-positive primary breast cancer (and who have no clinical or radiological evidence of recurrent disease or metastasis) are being enrolled around the world. The FACE trial will not only provide an efficacy evaluation between these two aromatase inhibitors but also provide a valuable head-to-head comparison of the safety profiles of adjuvant letrozole and anastrozole. The data will be transferred to an independent academic organization, the Istituto Nazionale Tumori (Michelangelo Foundation, Milan, Italy), which will verify and analyze the data, removing any perception of bias. An Independent Data Monitoring Committee will then decide when and how the trial data are to be released. The results are expected to further refine the treatment paradigm for breast cancer in postmenopausal patients with node-positive disease.
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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 | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".