Single-Center Real World Study of Everolimus and Exemestane in HR+/HER2− Metastatic Breast Cancer Following CDK4/6 Inhibitor Therapy
Bibliographic record
Abstract
BACKGROUND: Hormone receptor-positive (HR+), HER2- negative metastatic breast cancer (MBC) is the most common subtype of advanced breast cancer. Resistance to endocrine therapy often develops, particularly after CDK4/6 inhibitors. Everolimus, an mTOR inhibitor, may restore hormone sensitivity, but real-world data after CDK4/6 and chemotherapy are limited. METHODS: This retrospective, single-center study included 70 patients with HR+/HER2- MBC who progressed on CDK4/6 inhibitors and at least one line of chemotherapy. All received daily oral everolimus (10 mg) plus exemestane (25 mg). Tumor response was assessed via RECIST v1.1, and survival outcomes were estimated using the Kaplan-Meier method. RESULTS: Median progression-free survival was 6.6 months and overall survival was 22.6 months. The disease control rate was 88.6%, with 57.1% showing partial response. Fatigue (20%), skin toxicity (8.6%), and stomatitis (5.7%) were the most common adverse events. No grade 3-4 toxicities or discontinuations occurred. No clinical or pathological variables significantly influenced survival. CONCLUSIONS: Everolimus plus exemestane provided meaningful clinical benefit and manageable toxicity in heavily pretreated HR+/HER2- MBC patients. This regimen remains a valid later-line option, particularly in settings with limited access to newer targeted therapies or genomic testing.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".