Insulin, the Insulin-Like Growth Factor Axis, and Mortality in Patients With Nonmetastatic Colorectal Cancer
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
PURPOSE: Obesity, sedentary lifestyle, and Western dietary pattern have been linked to increased risk of cancer recurrence and mortality among patients with surgically resected colorectal cancer. Excess energy balance leads to increased circulating insulin and depressed levels of circulating insulin-like growth factor binding protein (IGFBP) -1, which promote cancer cell growth in preclinical models. PATIENTS AND METHODS: Among 373 patients diagnosed with nonmetastatic colorectal cancer between 1991 and 2004, we performed a prospective observational study nested within two large US cohorts to evaluate the association between mortality and prediagnosis circulating C-peptide (a marker of insulin secretion), IGFBP-1, insulin-like growth factor-I (IGF-I), and IGFBP-3. RESULTS: Compared with patients in the bottom quartile, patients in the top quartile of plasma C-peptide had an age-adjusted hazard ratio (HR) for death of 1.87 (95% CI, 1.04 to 3.36; P = .03 for trend), whereas those in the top quartile of circulating IGFBP-1 had a significant reduction in mortality (HR = 0.48; 95% CI, 0.28 to 0.84; P = .02 for trend). Little change in these estimates was noted after adjusting for other covariates known or suspected to influence survival. No associations were noted between mortality and IGF-I or IGFBP-3, which are two components of the IGF axis not closely correlated with lifestyle factors. CONCLUSION: Among patients with surgically resected colorectal cancer, higher levels of prediagnosis plasma C-peptide and lower levels of prediagnosis plasma IGFBP-1 were associated with increased mortality. Circulating insulin and IGFBP-1 are potential mediators of the association between lifestyle factors and mortality after colorectal cancer resection.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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