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Record W4414098708 · doi:10.3390/curroncol32090503

Single-Center Real World Study of Everolimus and Exemestane in HR+/HER2− Metastatic Breast Cancer Following CDK4/6 Inhibitor Therapy

2025· article· en· W4414098708 on OpenAlexvenueno aff
Yunus Emre Altıntaş, Oğuzcan Kınıkoğlu, Deniz Işık, Aziz Batu, Ayberk Bayramgil, Büşra Niğdelioğlu, Uğur Özkerim, Sıla Öksüz, Heves Sürmeli, Nedim Turan, Hatice Odabaş

Bibliographic record

VenueCurrent Oncology · 2025
Typearticle
Languageen
FieldMedicine
TopicAdvanced Breast Cancer Therapies
Canadian institutionsnot available
Fundersnot available
KeywordsExemestaneEverolimusMetastatic breast cancerRegimenAromatase inhibitorBreast cancerTargeted therapyClinical trial

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.414
Threshold uncertainty score0.840

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.085
GPT teacher head0.429
Teacher spread0.344 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations1
Published2025
Admission routes1
Has abstractyes

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