Prediagnostic circulating adipokine concentrations and risk of renal cell carcinoma in male smokers
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
Despite a well-established link between obesity and renal cell carcinoma (RCC), the mechanism through which obesity acts to increase cancer risk is unclear. Adiponectin, leptin and resistin are adipocyte-secreted peptide hormones that may influence RCC development through their demonstrated effects on inflammation, insulin resistance and cell growth and proliferation. We conducted a nested case-control study to evaluate whether prediagnostic serum adiponectin, leptin and resistin levels are associated with RCC risk. This case-control study (273 cases and 273 controls) was nested within the Alpha-Tocopherol, Beta-Carotene Cancer Prevention Study cohort of Finnish male smokers. Odds ratios (ORs) and 95% confidence intervals (95% CIs) were estimated using conditional logistic regression models, with analyte levels modeled continuously and categorically (defined using quartiles among controls). High adiponectin levels were significantly associated with reduced RCC risk (Quartile 4 versus Quartile 1: OR = 0.52, 95% CI = 0.30-0.88; P trend = 0.01). This association remained upon additional adjustment for body mass index at blood collection and exclusion of cases diagnosed within the first 2 years of follow-up. In addition, model adjustment for adiponectin resulted in a substantial attenuation of the association between BMI and RCC (OR per 5 kg/m(2) changed from 1.19 to 1.05). No clear associations with RCC were observed for leptin or resistin. Our results suggest that elevated levels of circulating adiponectin are associated with decreased subsequent risk of RCC. These findings provide the strongest evidence to date, suggesting that the association between obesity and RCC is mediated at least in part through the effects of low adiponectin.
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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 | 0.000 | 0.000 |
| 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 | 0.000 |
| 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