Everolimus plus exemestane as first-line therapy in HR+, HER2− advanced breast cancer in BOLERO-2
Bibliographic record
Abstract
The present exploratory analysis examined the efficacy, safety, and quality-of-life effects of everolimus (EVE) + exemestane (EXE) in the subgroup of patients in BOLERO-2 whose last treatment before study entry was in the (neo)adjuvant setting. In BOLERO-2, patients with hormone-receptor-positive (HR(+)), human epidermal growth factor receptor-2-negative (HER2(-)) advanced breast cancer recurring/progressing after a nonsteroidal aromatase inhibitor (NSAI) were randomly assigned (2:1) to receive EVE (10 mg/day) + EXE (25 mg/day) or placebo (PBO) + EXE. The primary endpoint was progression-free survival (PFS) by local assessment. Overall, 137 patients received first-line EVE + EXE (n = 100) or PBO + EXE (n = 37). Median PFS by local investigator assessment nearly tripled to 11.5 months with EVE + EXE from 4.1 months with PBO + EXE (hazard ratio = 0.39; 95 % CI 0.25-0.62), while maintaining quality of life. This was confirmed by central assessment (15.2 vs 4.2 months; hazard ratio = 0.32; 95 % CI 0.18-0.57). The marked PFS improvement in patients receiving EVE + EXE as first-line therapy for disease recurrence during or after (neo)adjuvant NSAI therapy supports the efficacy of this combination in the first-line setting. Furthermore, the results highlight the potential benefit of early introduction of EVE + EXE in the management of HR(+), HER2(-) advanced breast cancer in postmenopausal patients.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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 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".