Use of Calcium Channel Blockers and Risk of Breast Cancer
Bibliographic record
Abstract
BACKGROUND: Several observational studies have associated use of calcium channel blockers with an increased risk of breast cancer, but this association remains controversial. The objective of this study was to determine whether these drugs are associated with an increased risk of breast cancer overall, and to assess whether this risk varies with cumulative duration of use. METHODS: We identified a cohort of 273,152 women newly treated with antihypertensive drugs between 1 January 1995 and 31 December 2009, followed until 31 December 2010, using the UK Clinical Practice Research Datalink. We treated calcium channel blocker use as a time-varying variable, and lagged exposure by 1 year for latency considerations and to minimize reverse causality. We used time-dependent Cox proportional hazards models to estimate adjusted hazard ratios with 95% confidence intervals of incident breast cancer associated with use of calcium channel blockers overall and by cumulative duration of use (<5, 5-10, and ≥10 years). RESULTS: During 1,567,104 person-years of follow-up, 4,520 women were newly diagnosed with breast cancer (incidence rate: 2.9 per 1,000 per year). Compared with use of other antihypertensive drugs, use of calcium channel blockers was not associated with increased risk of breast cancer overall (hazard ratio: 0.97, 95% confidence interval: 0.91, 1.03). Similarly, there was no evidence of a duration-response relationship in terms of cumulative duration of use (P trend = 0.26). CONCLUSIONS: The results of this large population-based study indicate that long-term use of calcium channel blockers is not associated with an increased risk of breast cancer.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 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".