Association between antihypertensive medications and risk of skin cancer in people older than 65 years: a population-based study
Bibliographic record
Abstract
BACKGROUND: The risk of skin cancer associated with antihypertensive medication use is unclear, although thiazides have been implicated in regulatory safety warnings. We aimed to assess whether use of thiazides and other antihypertensives is associated with increased rates of keratinocyte carcinoma and melanoma. METHODS: We conducted a population-based inception cohort study using linked administrative health data from Ontario, 1998-2017. We matched adults aged ≥ 66 years with a first prescription for an antihypertensive medication (thiazides, angiotensin-converting enzyme inhibitors, angiotensin II receptor blockers, calcium channel blockers, β-blockers) by age and sex to 2 unexposed adults who were prescribed a non-antihypertensive medication within 30 days of the index date. We evaluated each antihypertensive class in a separate cohort study. Our primary exposure was the cumulative dose within each class, standardized according to the World Health Organization's Defined Daily Dose. Outcomes were time to first keratinocyte carcinoma, advanced keratinocyte carcinoma and melanoma. RESULTS: The inception cohorts included a total of 302 634 adults prescribed an antihypertensive medication and 605 268 unexposed adults. Increasing thiazide exposure was associated with an increased rate of incident keratinocyte carcinoma (adjusted hazard ratios [HRs] per 1 Defined Annual Dose unit 1.08, 95% confidence interval [CI] 1.03-1.14), advanced keratinocyte carcinoma (adjusted HR 1.07, 95% CI 0.93-1.23) and melanoma (adjusted HR 1.34, 95% CI 1.01-1.78). We found no consistent evidence of association between other antihypertensive classes and keratinocyte carcinoma or melanoma. INTERPRETATION: Higher cumulative exposure to thiazides was associated with increased rates of incident skin cancer in people aged 66 years and older. Consideration of other antihypertensive treatments in patients at high risk of skin cancer may be warranted.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".