Investigating Changes in Weight and Body Composition Among Women in Adjuvant Treatment for Breast Cancer
Bibliographic record
Abstract
BACKGROUND: Despite several investigations, findings on weight changes during and after adjuvant treatment for breast cancer are diverse and point in several directions. OBJECTIVE: The aims of this study were to investigate changes in weight and body composition associated with contemporary anticancer medication and to examine factors that might influence the assessment and diversity of the findings. METHODS: This article used the method of a scoping review to map the body of literature. From searching the databases PubMed, CINAHL, and EMBASE using MeSH terms, CINAHL terms, and Emtree, as well as free text, 19 articles were selected for further investigation. RESULTS: The scoping review illustrates how findings in weight and body composition changes fluctuate over time as illustrated in 4 measure points: short term, 1 year, 18 months/2 years, and long term. The studies displayed differences regarding study designs, sample sizes, treatment regimens, measure points and techniques, and cutoff values for assessing weight changes, which make it difficult to synthesize findings and provide strong evidence for use in clinical practice. CONCLUSION: Synthesizing findings over time illustrates the need for attention on younger premenopausal women given chemotherapy. Weight need to be monitored for at least 2 years as short-term changes may be caused by increased body water, whereas long-term changes seem to be related with increased fat mass essential for risking recurrence and early death. IMPLICATIONS FOR PRACTICE: The diversity in methods discloses the need for the research community to reach consensus regarding study designs for future research in this area.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".