Proton pump inhibitors and colorectal cancer: A systematic review
Bibliographic record
Abstract
BACKGROUND: The use of proton pump inhibitors (PPI) is common worldwide, with reports suggesting that they may be overused. Several studies have found that PPI may affect colorectal cancer (CRC) risk. AIM: To summarize current knowledge on the relationship between PPI and CRC from basic research, epidemiological and clinical studies. METHODS: = 5). The quality of the included studies was assessed using the Newcastle-Ottawa Scale or Cochrane Risk of Bias 2.0 tool depending on the study design. RESULTS: the trophic effect of gastrin but instead may paradoxically inhibit it. These studies also suggest that PPI may have properties beneficial for CRC treatment. PPI appear to have anti-tumor properties (omeprazole, pantoprazole), and are potential T lymphokine-activated killer cell-originated protein kinase inhibitors (pantoprazole, ilaprazole), and chemosensitizing agents (pantoprazole). However, these mechanisms have not been confirmed in human trials. Current epidemiological studies suggest that there is no causal association between PPI use and increased CRC risk. Treatment studies show that concomitant PPI and capecitabine use may reduce the efficacy of chemotherapy resulting in poorer oncological outcomes, while also suggesting that pantoprazole may have a chemosensitizing effect with the fluorouracil, leucovorin, oxaliplatin (FOLFOX) regimen. CONCLUSION: An unexpected inhibitory effect of PPI on CRC carcinogenesis by way of several potential mechanisms is noted. This review identifies that different PPI agents may have differential effects on CRC treatment, with practical implications. Prospective studies are warranted to delineate this relationship and assess the role of individual PPI agents.
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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 | 0.003 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.006 |
| Bibliometrics | 0.007 | 0.010 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".