The Diabetes-Pancreatic Cancer Risk Relationship over Time: A Systematic Review and Meta-Analysis
Bibliographic record
Abstract
Background/Objectives: The relationship between diabetes and pancreatic cancer (PCa) is controversial. In this meta-analysis and systematic review, we investigated diabetes and time since diagnosis as risk factors for PCa. Methods: Cohort and case-control studies were retrieved through a literature search. RevMan 5.4 software and a random effects model were used to estimate summary risks with their 95% confidence intervals (CIs), and the Newcastle–Ottawa Scale (NOS) was used to assess study quality. Results: Included were 23 studies representing 30,875,355 participants and 86,980 cases of PCa. The summary risk for the 14 case-control studies was 2.30 (95% CI: 2.03–2.62) and for the 9 cohort studies was 2.39 (95% CI: 2.09–2.73). The risk decreased with time after diabetes diagnosis: 3.27, 2.25, 1.55, and 1.12 for <2, 2–5, 5–10, and >10 years, respectively, in the case-control studies. The cohort studies also showed an increased risk of PCa in the first 2 years (4.29) and a decrease over time. Quality scores according to the NOS were 6–9 (good and fair quality), for an overall average of 7.82. Conclusions: Diabetes is a risk factor for PCa and this risk is much higher in the 2 years following diabetes diagnosis. In this period, the subgroup of patients who, through clinical follow-up and/or cancer screening, would have better clinical outcomes should be identified. Bearing in mind the poor survival rate for PCa, diabetes interventions focused on preventing onset and delaying progression via modifiable risk factors to reduce PCa incidence.
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How this classification was reachedexpand
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".