Changes in Weight and Body Composition Among Women With Breast Cancer During and After Adjuvant Treatment
Bibliographic record
Abstract
BACKGROUND: Antineoplastic adjuvant treatment for breast cancer can cause changes in women's weight and body composition and influence their general health and survival. OBJECTIVE: The aim of this study is to investigate the extent and patterns of change in weight and body composition after current standard adjuvant antineoplastic treatment for breast cancer. METHODS: Data on weight and body composition from 95 women with breast cancer Stage I to III were obtained during 18 months on a bioelectric impedance analyzer. Changes and odds ratio (OR) were calculated by a linear mixed model and logistic regression. RESULTS: At 18 months, there was an increase in weight of 0.9 kg (95% confidence interval [CI], 0.3-1.5; P = .003) and an average positive association of 0.35 kg/cm increased waist circumference (95% CI, 0.29-0.42 kg; P < .0001). Relative weight changes ranged from -12.7% to 20.5%. Weight gains related to increased body fat were observed mainly in premenopausal women receiving chemotherapy (1.4 kg; 95% CI, 0.4-2.4; P = .007). For menopausal status, OR was 2.9 (95% CI, 1.14-7.1; P = .025), and for chemotherapy, OR was 2.6 (95% CI, 1.03-6.41; P = .043). The OR for weight loss in Stage III breast cancer was 12.5 (95% CI, 1.21-128.84; P = .034) and 4.3 (CI, 1.07-17.24; P = .40) for comorbidity. CONCLUSIONS: Results demonstrate that weight changes in a pooled sample are overestimated. However, premenopausal women receiving anthracycline-based chemotherapy show a tendency toward a body composition with increasing fat mass. IMPLICATIONS FOR PRACTICE: A scheduled assessment of changes in weight and body composition is relevant at 18 months after treatment. To compare future studies, common measuring and cutoff points are needed.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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".