Use of vitamin K antagonists (VKAs) has been suggested to reduce the risk of prostate cancer. We conducted a nested case–control study using Danish demographic and health data registries and summarized existing evidence in a meta‐analysis. The case–control study included all Danish men aged 40–85 years with incident histologically verified prostate adenocarcinoma between 2005 and 2015 (cases). For each case, we selected 10 age–matched controls. We used conditional logistic regression to estimate odds ratios (ORs) with 95% confidence intervals (CI) for prostate cancer associated with long–term VKA use adjusted for concomitant drug use, medical history and socioeconomic status. Among 38,832 prostate cancer cases, 1,089 (2.8%) had used VKAs for 3 or more years compared to 10,803 (2.8%) controls yielding a crude OR of 1.01 (95% CI, 0.95–1.08). Multivariable adjustment for covariates had limited influence on the association (OR, 1.03; 95% CI, 0.97–1.10). We observed no dose–response relationship (e.g. OR for 5–10 years of use, 1.06 95% CI, 0.97–1.16). We included 8 studies in the meta–analysis reporting effect estimates from 0.51 (95% CI, 0.23–1.13) to 1.10 (95% CI, 0.94–1.40). Using random effect methods, a pooled effect estimate of 0.86 (95% CI, 0.70–1.05) was obtained; however, there was considerable across–study heterogeneity (I2: 93.9%). In conclusion, we did not observe a reduced risk of prostate cancer associated with VKA use in this nationwide study and, taken together with previous study findings, a major protective effect of VKAs against prostate cancer seems unlikely.

Aims Drug‐induced diabetes is underreported in conventional drug safety monitoring and may contribute to the increasing incidence of type 2 diabetes. Therefore, we used routinely collected prescription data to screen all commonly used drugs for diabetogenic effects. Methods Leveraging the Danish nationwide health registries, we used a case‐only symmetry analysis design to evaluate all possible associations between drug initiation and subsequent diabetes. The study was conducted among individuals aged ≥40 years with a first‐ever prescription for any antidiabetic drug 1996‐2018 (n = 348 996). Sequence ratios (SRs) and 95% confidence intervals (CIs) were obtained for all possible drug class‐diabetes combinations. A lower bound of the 95% CI >1.00 was considered a signal. Signals generated in Denmark were replicated using the Services Australia, Pharmaceutical Benefits Scheme 10% data extract. Results Overall, 386 drug classes were investigated, of which 70 generated a signal. In total, 43 were classified as previously known based on the SIDER database or a literature review, for example, glucocorticoids (SR 1.67, 95% CI 1.62‐1.72) and β‐blockers (SR 1.20, 95% CI 1.16‐1.23). Of 27 new signals, three drug classes yielded a signal in both the Danish and Australian data source: digitalis glycosides (SR 2.15, 95% CI 2.04‐2.27, and SR 1.76, 95% CI 1.50‐2.08), macrolides (SR 1.20, 95% CI 1.16‐1.24, and SR 1.11, 95% CI 1.06‐1.16) and inhaled β2‐agonists combined with glucocorticoids (SR 1.35, 95% CI 1.28‐1.42, and SR 1.14, 95% CI 1.06‐1.22). Conclusion We identified 70 drug‐diabetes associations, of which 27 were classified as hitherto unknown. Further studies evaluating the hypotheses generated by this work are needed, particularly for the signal for digitalis glycosides.

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