Long-Term Use of Angiotensin Receptor Blockers and the Risk of Cancer
Bibliographic record
Abstract
The association between angiotensin receptor blockers (ARBs) and cancer is controversial with meta-analyses of randomized controlled trials and observational studies reporting conflicting results. Thus, the objective of this study was to determine whether ARBs are associated with an overall increased risk of the four most common cancers, namely, lung, colorectal, breast and prostate cancers, and to explore these effects separately for each cancer type. We conducted a retrospective cohort study using a nested case-control analysis within the United Kingdom (UK) General Practice Research Database. We assembled a cohort of patients prescribed antihypertensive agents between 1995, the year the first ARB (losartan) entered the UK market, and 2008, with follow-up until December 31, 2010. Cases were patients newly-diagnosed with lung, colorectal, breast and prostate cancer during follow-up. We used conditional logistic regression to estimate adjusted rate ratios (RRs) and 95% confidence intervals (CIs) of cancer incidence, comparing ever use of ARBs with ever use of diuretics and/or beta-blockers. The cohort included 1,165,781 patients, during which 41,059 patients were diagnosed with one of the cancers under study (rate 554/100,000 person-years). When compared to diuretics and/or beta-blockers, ever use of ARBs was not associated with an increased rate of cancer overall (RR: 1.00; 95% CI: 0.96-1.03) or with each cancer site separately. The use of angiotensin-converting enzyme inhibitors and calcium channel blockers was associated with an increased rate of lung cancer (RR: 1.13; 95% CI: 1.06-1.20 and RR: 1.19; 95% CI: 1.12-1.27, respectively). This study provides additional evidence that the use of ARBs does not increase the risk of cancer overall or any of the four major cancer sites. Additional research is needed to further investigate a potentially increased risk of lung cancer with angiotensin-converting enzyme inhibitors and calcium channel blockers.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| 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".