https://orcid.org/0000-0002-8196-2599
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Anders Holt, Patricia McGettigan, Morten Lamberts, Unmeasured confounding is always unnerving: cannabis and cardiovascular risk, European Heart Journal, Volume 45, Issue 28, 21 July 2024, Pages 2574–2575, https://doi.org/10.1093/eurheartj/ehae314
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This commentary refers to ‘Cannabis for chronic pain: cardiovascular safety in a nationwide Danish study’, by A. Holt et al., https://doi.org/10.1093/eurheartj/ehad834 and the discussion piece ‘Cannabis use and cardiovascular diseases’, by V. Čulić, https://doi.org/10.1093/eurheartj/ehae313.
Thank you for your engagement in a relevant discussion. We agree that the lack of proper data on lifestyle factors such as smoking and alcohol use could bias the associations found between medical cannabis use and an elevated risk of new-onset arrhythmia [180-day absolute risk (AR) difference of 0.4% (95% confidence interval: 0.3%–0.5%)].1 Our initial solution to mitigate unmeasured confounding related to lifestyle factors was to adjust all analyses for educational level,1 but in lieu of the discussion raised here, we further defined two proxy variables to try and accommodate this issue: one for history of smoking (medical history of chronic obstructive pulmonary disease or tobacco use, or a recent prescription claim of smoking cessation drugs), and one for history of alcohol abuse (medical history of diagnoses directly related to alcohol). Patients exposed to medical cannabis were more likely to have a history of smoking (8.8%) than the control patients who were not (7.4%), whereas history of alcohol abuse was similar (2.1% vs. 2.6%). Adding the smoking and alcohol proxies as variables to the statistical models yielded comparable results compared with the main analyses (Table 1). Likewise, if the association between medical cannabis use and cardiovascular risk was assessed in a subgroup free of smoking and alcohol history, results were comparable as well (Table 1). The small differences between exposure groups could perhaps explain the lack of changes in the main results. Albeit, it could equally well be due to the inaccuracy of the proxy variables; thus, unmeasured lifestyle factors may still bias the proposed associations.
