Cognitive Function, Fatigue, and Menopausal Symptoms in Women Receiving Adjuvant Chemotherapy for Breast Cancer
Bibliographic record
Abstract
PURPOSE: There is evidence that cognitive dysfunction, fatigue, and menopausal symptoms may occur in women receiving adjuvant chemotherapy for breast cancer. Here, we determine their incidence and severity, and interrelationships between them and quality of life. PATIENTS AND METHODS: In this study, 110 women receiving adjuvant chemotherapy each nominated a female relative, friend, or neighbor (matched by age) as a control; 100 eligible matched pairs were evaluated. Patients and controls completed the following assessments: the High-Sensitivity Cognitive Screen, and the Functional Assessment of Cancer Therapy-General (FACT-G) quality of life scale with subscales for fatigue (FACT-F) and endocrine symptoms (FACT-ES). They also performed tests of attention and reaction time. RESULTS: Patients and controls were well matched for age and level of education. There was a higher incidence of moderate or severe cognitive impairment in the patient group (16% v 4%; P =.008). Patients experienced much more fatigue than controls (median FACT-F scores, 31 v 46; P <.0001) and more menopausal symptoms (median FACT-ES scores, 58 v 64; P <.0001). Self-reported quality of life of the patients was poorer than for controls, especially in physical and functional domains (median FACT-G scores, 77 v 93; P <.0001). There was strong correlation between fatigue, menopausal symptoms, and quality of life (P <.0001 for each pair), but none were significantly associated with the presence of cognitive dysfunction. CONCLUSION: Adjuvant chemotherapy causes cognitive dysfunction, fatigue, and menopausal symptoms in women with breast cancer. Priority should be given to the study of strategies that might reduce these toxic effects.
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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 | 0.000 | 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 | 0.000 | 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".