A Randomized Placebo Controlled Phase II Trial Evaluating Exemestane with or without Enzalutamide in Patients with Hormone Receptor–Positive Breast Cancer
Bibliographic record
Abstract
Abstract Purpose: To determine whether the androgen receptor (AR) inhibitor, enzalutamide, improves effectiveness of endocrine therapy (ET) in hormone receptor–positive (HR+) breast cancer. Patients and Methods: In this phase II trial, patients with HR+/HER2 normal advanced/metastatic breast cancer were randomized 1:1 to exemestane 25 mg with placebo or exemestane 50 mg with enzalutamide 160 mg daily (NCT02007512). Two parallel cohorts enrolled patients with 0 (cohort 1) or 1 (cohort 2) prior ET for advanced disease. Progression-free survival (PFS) was the primary endpoint in the intent-to-treat (ITT) population of each cohort. Biomarkers were evaluated in an exploratory analysis. Results: Overall, 247 patients were randomized (cohort 1, n = 127 and cohort 2, n = 120). PFS was not improved in either cohort of the ITT population [HR, 0.82 (95% confidence interval (CI), 0.54–1.26); P = 0.3631 for cohort 1 and HR, 1.02 (95% CI, 0.66–1.59); P = 0.9212 for cohort 2]. In cohort 1, high levels of AR mRNA were associated with greater benefit of enzalutamide (Pinteraction = 0.0048). This effect was particularly apparent in patients with both high levels of AR mRNA and low levels of ESR1 mRNA [HR, 0.24 (95% CI, 0.10–0.60); P = 0.0011]. The most common any grade adverse events in the enzalutamide arms were nausea (39%) in cohort 1 and fatigue (37%) in cohort 2. Conclusions: Enzalutamide with exemestane was well tolerated. While PFS was not improved by the addition of enzalutamide to exemestane in an unselected population, ET-naïve patients with high AR mRNA levels, particularly in combination with low ESR1 mRNA levels, may benefit from enzalutamide with exemestane.
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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 | 0.004 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".