Explaining the Obesity Paradox: The Association between Body Composition and Colorectal Cancer Survival (C-SCANS Study)
Why this work is in the frame
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Bibliographic record
Abstract
Abstract Background: Body composition may partially explain the U-shaped association between body mass index (BMI) and colorectal cancer survival. Methods: Muscle and adiposity at colorectal cancer diagnosis and survival were examined in a retrospective cohort using Kaplan–Meier curves, multivariable Cox regression, and restricted cubic splines in 3,262 early-stage (I–III) male (50%) and female (50%) patients. Sarcopenia was defined using optimal stratification and sex- and BMI-specific cut points. High adiposity was defined as the highest tertile of sex-specific total adipose tissue (TAT). Primary outcomes were overall mortality and colorectal cancer–specific mortality (CRCsM). Results: Slightly over 42% patients were sarcopenic. During 5.8 years of follow-up, 788 deaths occurred, including 433 from colorectal cancer. Sarcopenic patients had a 27% [HR, 1.27; 95% confidence interval (CI), 1.09–1.48] higher risk of overall mortality than those who were not sarcopenic. Females with both low muscle and high adiposity had a 64% higher risk of overall mortality (HR, 1.64; 95% CI, 1.05–2.57) than females with adequate muscle and lower adiposity. The lowest risk of overall mortality was seen in patients with a BMI between 25 and <30 kg/m2, a range associated with the greatest number of patients (58.6%) who were not at increased risk of overall mortality due to either low muscle or high adiposity. Conclusions: Sarcopenia is prevalent among patients with non-metastatic colorectal cancer, and should, along with adiposity be a standard oncological marker. Impact: Our findings suggest a biologic explanation for the obesity paradox in colorectal cancer and refute the notion that the association between overweight and lower mortality is due solely to methodologic biases. Cancer Epidemiol Biomarkers Prev; 26(7); 1008–15. ©2017 AACR.
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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 | 0.006 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 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 it