Weight Regain and Breast Cancer–Related Biomarkers Following an Exercise Intervention in Postmenopausal Women
Bibliographic record
Abstract
BACKGROUND: Epidemiologic studies have reported associations between weight fluctuations and postmenopausal breast cancer risk; however, the biological markers involved in this association are unknown. This study aimed to explore the associations between breast cancer-related biomarkers and weight regain following exercise-induced weight loss. METHODS: From the 400 participants included in the Breast Cancer and Exercise Trial in Alberta, a total of 214 lost weight during the intervention and had follow-up blood samples, body composition, and covariate measurements. Outcomes were measured at baseline, 12 months (end of the study), and 24 months (follow-up). RESULTS: During follow-up, weight regain was 1.80 kg [95% confidence interval (CI): -0.40-3.90], and was significantly associated with increases in estradiol [treatment effect ratio (TER) = 1.03; 95% CI, 1.01-1.04], estrone (TER = 1.02; 95% CI, 1.01-1.03), free estradiol (TER = 1.04; 95% CI, 1.02-1.05), the homeostatic model assessment for insulin resistance (TER = 1.03; 95% CI, 1.02-1.05), and insulin (TER = 1.03; 95% CI, 1.01-1.04), and decreases in sex hormone-binding globulin (SHBG; TER = 0.98; 95% CI, 0.97-0.99) levels. Nonstatistically significant associations were found for glucose and C-reactive protein. Furthermore, a statistically significant linear trend of increasing levels for all biomarkers, and decreasing SHBG, across weight regain categories was found. CONCLUSIONS: These results suggest that weight regain following exercise-induced weight loss is associated with breast cancer-related biomarker changes in postmenopausal women. IMPACT: These findings provide evidence to support the importance of developing effective strategies to prevent weight regain and, consequently, decrease postmenopausal breast cancer risk via changes in adiposity-related biomarkers.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 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 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".