Geographical Differences in Hydrochlorothiazide Associated Risk of Skin Cancer Balanced Against Disability Related to Hypertensive Heart Disease
Bibliographic record
Abstract
BACKGROUND: Hypertension affects 25%-30% of the world population. Hydrochlorothiazide (HCTZ) is among the most used and cheapest medications but was in 2018 labeled with a warning stating the increased risk of nonmelanoma skin cancer (NMSC). This study describes geographical differences in the association between HCTZ and NMSC from the perspective of hypertensive heart disease (HHD). METHODS: We conducted a systematic literature search (PubMed, Embase, Clinicaltrial.gov, and Clinicaltrial.eu) using PICO/PECO acronyms, including case-control, cohort, and randomized controlled trials. We constructed a rate ratio of disability-adjusted life years (DALY) for HHD/NMSC in the global burden of disease (GBD) regions. RESULTS: No increased risk of NMSC with the use of HCTZ was found in Taiwan, India, and Brazil. A small (hazard ratio (HR)/odds ratio (OR) ≤1.5) but significantly increased risk was seen in Canada, the United States, and Korea. An increased risk (1.5< HR/OR ≤2.5) in Iceland, Spain, and Japan and a highly increased risk (HR/OR >2.5) in the United Kingdom, Denmark, the Netherlands, and Australia. HHD is associated with a more than tenfold DALY rate compared with NMSC in 13 of 21 GBD regions, corresponding to 77.2% of the global population. In none of these 13 regions was there an increased risk of HCTZ-associated NMSC. CONCLUSIONS: Despite limited information from many countries, our data point to large geographical differences in the association between HCTZ and NMSC. In all GBD regions, except Australasia, HHD constitutes a more than fivefold DALY rate compared to NMSC. This disproportionate risk should be considered before avoiding HCTZ from the antihypertensive treatment.
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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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".