The effect of using adjuvant aromatase inhibitors on cognitive functions in postmenopausal women with hormone receptor-positive breast cancer
Bibliographic record
Abstract
Introduction: Breast cancer is the most frequently diagnosed cancer in women worldwide. Aromatase inhibitors (AIs) are effective treatment options for both early-stage and advanced hormone receptor-positive breast cancer. Because of AIs are used long term in adjuvant therapy, side effects are also very important. It is considered that AIs may affect cognitive functions by decreasing the level of estrogen in the brain. The purpose of our study is that evaluate the relationship between duration of treatment and cognitive functions in patients with breast cancer who use AIs in adjuvant therapy. Methods: Two-hundred patients diagnosed with breast cancer who were treated with AIs as adjuvant treatment were included. The patients were surveyed for demographic characteristics. Montreal Cognitive Assessment (MoCA) and Standardized Mini-Mental State Examination (SMMT) tests were performed to evaluate patients' cognitive functions. The total scores of the tests and the orientation, short-time memory, visuospatial functions, attention, language, executive functions which are the MoCA subscales were evaluated separately. Patients were grouped as 0-6, 6-12, 12-24, 24-36, 36, and more months according to the duration of AIs using time. Results: The total MoCA and SMMT scores were affected by factors such as age, education level, and employment status. There was no relationship between duration of treatment and cognitive functions in patients with breast cancer who use AIs in adjuvant therapy (P > 0.05). In addition, no statistically relationship was found in the evaluation of MoCA subscales (P > 0.05). Discussion: Prolonged adjuvant treatment with AIs does not affect cognitive functions in hormone receptor-positive breast cancer patients.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".