Randomized phase III trial evaluating the role of weight loss in adjuvant treatment of overweight and obese women with early breast cancer (Alliance A011401): study design
Bibliographic record
Abstract
Abstract Excess body weight is a poor prognostic factor in women with early breast cancer, but the effect of weight loss on the risk of breast cancer recurrence and mortality in women who are overweight or obese at the time of breast cancer diagnosis has not been evaluated. The Alliance for Clinical Trials in Oncology Breast Cancer Weight Loss trial, also known as A011401, is testing the impact of a telephone-based weight loss program on invasive disease-free survival in 3136 women with a body mass index ≥27 kg/m 2 who have recently been diagnosed with stage II-III, HER-2 negative breast cancer. Secondary outcomes of the trial include the impact of the weight loss intervention on overall survival, body weight, physical activity, dietary intakes, incidence of comorbidities, serum biomarkers and patient reported outcomes. Participants are randomized 1:1 to a 2-year, telephone-based weight loss intervention or to an education control group. The intervention is delivered through 42 telephone calls, delivered by health coaches based at the Dana-Farber Cancer Institute. Calls are supplemented by an intervention workbook, as well as a number of tools to help facilitate weight loss. Intervention goals include loss of 10% of baseline body weight, achieved through caloric restriction and increased physical activity. This large-scale study testing the impact of purposeful weight loss after cancer diagnosis on the risk of breast cancer recurrence and mortality has the potential to make weight loss programs a standard part of breast cancer treatment.
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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 | 0.006 | 0.006 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.013 | 0.002 |
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".