Impact of Baseline and On-Treatment Glycemia on Everolimus-Exemestane Efficacy in Patients with Hormone Receptor–Positive Advanced Breast Cancer (EVERMET)
Bibliographic record
Abstract
Abstract Purpose: The mTOR complex C1 (mTORC1) inhibitor everolimus in combination with the aromatase inhibitor exemestane is an effective treatment for patients with hormone receptor—positive (HR+), HER2-negative (HER2−), advanced breast cancer (HR+/HER2− aBC). However, everolimus can cause hyperglycemia and hyperinsulinemia, which could reactivate the PI3K/protein kinase B (AKT)/mTORC1 pathway and induce tumor resistance to everolimus. Experimental Design: We conducted a multicenter, retrospective, Italian study to investigate the impact of baseline and on-treatment (i.e., during first 3 months of therapy) blood glucose levels on progression-free survival (PFS) in patients with HR+/HER2− aBC treated with everolimus-exemestane. Results: We evaluated 809 patients with HR+/HER2− aBC treated with everolimus-exemestane as any line of therapy for advanced disease. When evaluated as dichotomous variables, baseline and on-treatment glycemia were not significantly associated with PFS. However, when blood glucose concentration was evaluated as a continuous variable, a multivariable model accounting for clinically relevant patient- and tumor-related variables revealed that both baseline and on-treatment glycemia are associated with PFS, and this association is largely attributable to their interaction. In particular, patients who are normoglycemic at baseline and experience on-treatment diabetes have lower PFS compared with patients who are already hyperglycemic at baseline and experience diabetes during everolimus-exemestane therapy (median PFS, 6.34 vs. 10.32 months; HR, 1.76; 95% confidence interval, 1.15–2.69; P = 0.008). Conclusions: The impact of on-treatment glycemia on the efficacy of everolimus-exemestane therapy in patients with HR+/HER2− aBC depends on baseline glycemia. This study lays the foundations for investigating novel therapeutic approaches to target the glucose/insulin axis in combination with PI3K/AKT/mTORC1 inhibitors in patients with HR+/HER2− aBC.
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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) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".