A pooled analysis of 14 cohort studies of anthropometric factors and pancreatic cancer risk
Bibliographic record
Abstract
Epidemiologic studies of pancreatic cancer risk have reported null or nonsignificant positive associations for obesity, while associations for height have been null. Waist and hip circumference have been evaluated infrequently. A pooled analysis of 14 cohort studies on 846,340 individuals was conducted; 2,135 individuals were diagnosed with pancreatic cancer during follow-up. Study-specific relative risks (RRs) and 95% confidence intervals (CIs) were calculated by Cox proportional hazards models, and then pooled using a random effects model. Compared to individuals with a body mass index (BMI) at baseline between 21-22.9 kg/m(2) , pancreatic cancer risk was 47% higher (95%CI:23-75%) among obese (BMI ≥ 30 kg/m(2) ) individuals. A positive association was observed for BMI in early adulthood (pooled multivariate [MV]RR = 1.30, 95%CI = 1.09-1.56 comparing BMI ≥ 25 kg/m(2) to a BMI between 21 and 22.9 kg/m(2) ). Compared to individuals who were not overweight in early adulthood (BMI < 25 kg/m(2) ) and not obese at baseline (BMI < 30 kg/m(2) ), pancreatic cancer risk was 54% higher (95%CI = 24-93%) for those who were overweight in early adulthood and obese at baseline. We observed a 40% higher risk among individuals who had gained BMI ≥ 10 kg/m(2) between BMI at baseline and younger ages compared to individuals whose BMI remained stable. Results were either similar or slightly stronger among never smokers. A positive association was observed between waist to hip ratio (WHR) and pancreatic cancer risk (pooled MVRR = 1.35 comparing the highest versus lowest quartile, 95%CI = 1.03-1.78). BMI and WHR were positively associated with pancreatic cancer risk. Maintaining normal body weight may offer a feasible approach to reducing morbidity and mortality from pancreatic cancer.
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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 | 0.025 | 0.034 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.007 | 0.019 |
| Bibliometrics | 0.007 | 0.008 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".