Breast Cancer Treatment and Cognitive Function: The Current State of Evidence, Underlying Mechanisms and Potential Treatments
Bibliographic record
Abstract
Within the last decade, several studies have investigated whether adjuvant treatment of breast cancer affects cognitive function. A number of prospective studies have demonstrated inconsistent results regarding whether chemotherapy affects cognitive function. Approximately half of the studies demonstrated subtle cognitive decline in a wide range of domains among some breast cancer patients following chemotherapy, and half did not. Concomitant changes in brain structure and function have been identified in neuroimaging and neurophysiologic studies. Estrogenic therapy has been specifically associated with deterioration in verbal memory and processing speed. However, evidence is mostly based on smaller studies with cross-sectional data. Breast cancer patients who underwent both chemotherapy and estrogenic therapy showed the most deterioration and the most persistent decline in cognitive function. Since cognitive impairment is subtle, if evident at all, discrepant findings are due to hormonal, physiological, psychological or temporal confounding variables and differences in study design. Neuropsychological training has been demonstrated to improve cognitive dysfunction experienced by breast cancer patients after chemotherapy. Future research may examine the unique impact of endocrine therapy on cognitive function with prospective, controlled trials, as well as the role of further confounding variables (e.g., menopausal status, cytokine deregulation, cortisol and concurrent medication).
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".