Cognitive effects of hormonal therapy in early stage breast cancer patients: a prospective study
Bibliographic record
Abstract
OBJECTIVE: The primary purpose of this study was to evaluate the cognitive effects of adjuvant hormonal therapies in breast cancer patients. PARTICIPANTS AND METHODS: Post-menopausal breast cancer patients scheduled to receive tamoxifen (n=31) or anastrozole (n=14) completed neuropsychological testing around the time of commencement of treatment (T1), and again 5-6 months later (T2). A sample of healthy female volunteers (n=28) was tested at comparable intervals. A standardized regression-based approach was used to assess cognitive change. This method uses test/retest scores of the healthy control group to generate an equation that predicts T2 scores from T1 scores. The difference between the predicted and obtained T2 scores divided by the standard error of the estimate produces a deviation score that reflects the discrepancy from the T1-T2 difference scores that would be expected on the basis of practice and error alone. RESULTS: Analysis of individual deviation scores revealed that both the patients taking tamoxifen and those taking anastrozole were more likely than healthy controls to show reliable cognitive decline from T1 to T2 (39, 64, and 7%, respectively). Processing speed and verbal memory were the cognitive domains most affected. CONCLUSION: These data suggest that hormonal therapies exert a subtle negative influence on cognition in breast cancer patients. Further analyses indicated that this effect was not fully accounted for by demographic factors or fatigue. Methodological limitations of the current study are addressed, along with recommendations for future studies in this area.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".