Multicenter, randomized phase II trial of physical activity (PA), metformin (Met), or the combination on metabolic biomarkers in stage I-III colorectal (CRC) and breast cancer (BC) survivors.
Bibliographic record
Abstract
10059 Background: Observational data demonstrate an inverse relationship between PA and Met to disease outcomes in CRC & BC pts. A mechanism that these could impact cancer recurrence and mortality is hypothesized to involve insulin and related growth factors. We investigated the effects of PA, Met or the combination on metabolic biomarkers in CRC & BC pts. Methods: In a phase 2 RCT, stage I-III CRC & BC survivors at least 2 months from completing standard therapy (excluding hormone rx or trastuzumab) were randomized to PA, Met, PA + Met or control. Major eligibility included absence of recurrence or diabetes (glucose < 160 (random) or < 126 (fasting) mg/dl) and exercising < 120 min/wk. The PA intervention consisted of supervised aerobic training at least 2 x /wk. Metformin dosing was 850 mg 1x/day titrated to 850 mg 2x/day after 2 wks if tolerated. Interventions were 12 weeks in duration. Fasting bloods at baseline & 12 wks were analyzed for insulin (1oendpoint), leptin, IGF1, IGFBP1 & IGFBP3. Results: 139 pts were enrolled: 62% BC/38% CRC; 83% female; median BMI 28.3; median 2 yrs from dx; median age 56 (range 34-79). 107 pts completed assigned therapy. Pts in PA and PA + Met arms increased PA by 166 and 140 min/wk vs 30 min/wk in controls (both P<0.0001). Pts in the Met and PA + Met arms lost weight vs controls (-1.41 and -0.91 kg vs + 1.97 kg, both P <0.0001). Both interventions had impact on metabolic biomarkers (Table). Conclusions: PA and Met both led to significant changes in insulin and other biomarkers in CRC & BC survivors with potential synergistic effect on leptin with dual intervention. Clinical trial information: NCT01340300. [Table: see text]
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
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".