Use of angiotensin-converting-enzyme inhibitors or angiotensin-receptor blockers and cancer risk: a meta-analysis of observational studies
Bibliographic record
Abstract
BACKGROUND: Epidemiologic studies have reported inconsistent findings regarding the association between the use of angiotensin-converting-enzyme (ACE) inhibitors or angiotensin-receptor blockers and the risk of cancer. We performed a meta-analysis of observational studies to assess the association. METHODS: We searched MEDLINE, EMBASE and the Cochrane Library to identify studies through January 2011. Two evaluators independently reviewed and selected articles of cohort and case-control studies on the basis of predetermined selection criteria. RESULTS: Of 3970 screened articles, 12 cohort studies and 16 case-control studies were selected for analysis. We found no significant association between the use of ACE inhibitors or angiotensin-receptor blockers and the overall risk of cancer (relative risk [RR] 0.96, 95% confidence interval [CI] 0.90-1.03). We found a decreased risk of cancer associated with use of either medication when we restricted the analyses to cohort and nested case-control studies (RR 0.90, 95% CI 0.83-0.97) or to studies with long-term follow-up of more than five years (RR 0.89, 95% CI 0.83-0.96). In the subgroup meta-analyses by cancer site, a decreased risk was identified for esophageal cancer, whereas an increased risk was found for melanoma and kidney cancer. INTERPRETATION: No significant association was found between the use of ACE inhibitors or angiotensin-receptor blockers and overall risk of cancer. A possible beneficial effect associated with use of either medication was suggested in sensitivity analyses, including those of studies with long-term follow-up. Large randomized controlled trials with long-term follow-up are needed to specifically test the effect of each of these medications on the risk of cancer.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.009 | 0.004 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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 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".