The role of vitamin C in the prevention of pancreatic cancer: a systematic-review
Bibliographic record
Abstract
Introduction and aim: The aim of this systematic review was to assess the role of vitamin C in the prevention of pancreatic cancer (PC). Methods: A comprehensive literature search was performed in PubMed, Embase and Web of Science up to August 2023, to identify randomized controlled trials (RCT), cohort studies and mendelian randomization studies based on prospective databases assessing the role of vitamin C in PC prevention. Results: A total of twelve studies including European and North-American participants were included: two RCT, three mendelian randomization (MR) studies and seven cohort studies. Both RCT showed high quality in Cochrane risk of bias tool. Only one cohort study had <7 points in Newcastle Ottawa Scale. Both RCT found no association between the intake of 500 mg/day of vitamin C and the incidence of PC. Only one prospective cohort study found an association between vitamin C serum levels and a lower incidence of PC. The remaining cohort studies and MR studies found no association between dietary/supplements intake of vitamin C or circulating vitamin C levels and the incidence of PC. Conclusion: There is no supporting evidence that vitamin C prevents PC development. Future prospective quality studies including high-risk populations are needed.
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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 | 0.005 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.006 |
| Bibliometrics | 0.007 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".