Drugs affecting renin-angiotensin-aldosterone system and the cancer risk: A meta-analysis of nested case-control studies.
Bibliographic record
Abstract
Multiple studies have discussed the associations between drugs affecting the renin-angiotensin-aldosterone system and the cancer risk, but their consequence s were conflicting. A meta-analysis of nested case-control studies published regarding this subject was conducted in our study, aims to estimate the association between ACEI/ARB and the cancer risk. Pubmed database was searched up to February, 1 2016 to identify eligible nested case-control studies, and we used Newcastle-Ottawa Scale (NOS) to assess quality of the studies. Pooled odds ratio (OR) and 95% confidence intervals (CIs) were calculated (with fixed effect model: Mantel-Haenszel). Publication bias and heterogeneity were evaluated before the calculation. Subgroup analysis and sensitivity analysis were also performed. Seven studies contributed to the analysis. Overall, ACEI/ARB use was not associated with the risk of cancer (OR=0.99, 95% CI 0.97-1.01), nor in long-term use patients (OR=0.97, 95% CI 0.92-1.01). ACEI may decrease cancer risk (OR=0.90, 95% CI 0.82-0.99). We observed no significant publication bias. In conclusion, ACEI/ARB use was not associated with cancer risk, nor in long-term use patients, but ACEI use may decrease cancer risk. More researches are needed to confirm these findings.
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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 | 0.019 | 0.040 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.014 | 0.040 |
| Bibliometrics | 0.007 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".