Fatigue, Menopausal Symptoms, and Cognitive Function in Women After Adjuvant Chemotherapy for Breast Cancer: 1- and 2-Year Follow-Up of a Prospective Controlled Study
Bibliographic record
Abstract
PURPOSE: We previously evaluated fatigue, menopausal symptoms, and cognitive dysfunction in patients receiving adjuvant therapy for breast cancer and matched healthy women. Here we report assessment of these women 1 and 2 years later. PATIENTS AND METHODS: Patients without relapse and controls were evaluated by the Functional Assessment of Cancer Treatment-General Quality of Life questionnaire, with subscales for fatigue and endocrine symptoms, and by the High Sensitivity Cognitive Screen. RESULTS: There were 104, 91, and 83 patients and 102, 81, and 81 controls assessed at baseline and at 1 and 2 years, respectively. Median Functional Assessment of Cancer Treatment-Fatigue scores (range, 0 to 52) for patients improved from 31 (on chemotherapy) to 43 and 45 at 1 and 2 years, respectively, but were stable in controls (46 to 48). Median Functional Assessment of Cancer Treatment-Endocrine Symptoms scores (range, 0 to 72) for patients improved from 57 (on chemotherapy) to 59 and 61 at 1 and 2 years, respectively, and were stable in controls (64 to 65). Differences between patients and controls remained significant for these scales. The incidence of moderate-severe cognitive dysfunction by the High Sensitivity Cognitive Screen decreased in patients from 16% (on chemotherapy) to 4.4% and 3.8% and in controls from 5% to 3.6% and 0% at 1 and 2 years, respectively. There were minimal differences between estrogen receptor-positive patients who started hormonal therapy (mainly tamoxifen) after chemotherapy and estrogen receptor-negative patients who did not. Differences in quality of life between patients and controls were significant only at baseline. CONCLUSION: Fatigue, menopausal symptoms, and cognitive dysfunction are important adverse effects of chemotherapy that improve in most patients. Hormonal treatment has minimal impact on them.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".