Alcohol Intake Among Breast Cancer Survivors: Change in Alcohol Use During a Weight Management Intervention
Bibliographic record
Abstract
BACKGROUND: Daily alcohol intake in quantities as small as half a drink/day significantly increases the risk of breast cancer recurrence for postmenopausal survivors. Interventions designed to modify alcohol use among survivors have not been studied; however, lifestyle interventions that target change in dietary intake may affect alcohol intake. OBJECTIVE: To evaluate change in alcohol use during a weight loss intervention for obese, rural-dwelling breast cancer survivors. METHODS: Data were derived from an 18-month trial that included a 6-month weight loss intervention delivered via group conference calls, followed by a 12-month randomized weight loss maintenance phase in which participants received continued group calls or mailed newsletters. Participants who reported regular alcohol use at baseline (N=37) were included in this study. RESULTS: Mean daily alcohol intake significantly decreased from baseline to 6 months during the weight loss intervention (19.6-2.3 g; P=.001). Mean alcohol intake did not significantly increase (b=0.99, P=.12) during the weight loss maintenance phase (months 6-18) and did not depend on randomization group (b=0.32, P=.799). CONCLUSIONS: Findings provide preliminary evidence that a weight loss intervention may address obesity and alcohol use risk factors for cancer recurrence. Minimal mail-based contact post weight loss can maintain alcohol use reductions through 18 months, suggesting durability in these effects. These results highlight a possibility that lifestyle interventions for survivors may modify health behaviors that are not the main foci of an intervention but that coincide with intervention goals. TRIAL REGISTRATION: Clinicaltrials.gov NCT01441011; https://clinicaltrials.gov/ct2/show/NCT01441011 (Archived by WebCite at http://www.webcitation.org/6lsJ9dMa9).
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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 | 0.001 | 0.002 |
| 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".