Do drugs interact together in cardiovascular prevention? A meta-analysis of powerful or factorial randomized controlled trials.
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2022
- doi: 10.1016/j.therap.2022.04.004
- issn: 0040-5957
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info:eu-repo/semantics/altIdentifier/doi/10.1016/j.therap.2022.04.004
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info:eu-repo/semantics/altIdentifier/pmid/35643744
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info:eu-repo/semantics/altIdentifier/eissn/1958-5578
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info:eu-repo/semantics/altIdentifier/urn/urn:nbn:ch:serval-BIB_EF6BDB3E9CAD2
info:eu-repo/semantics/openAccess , CC BY-NC-ND 4.0 , https://creativecommons.org/licenses/by-nc-nd/4.0/
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M. Fall et al., « Do drugs interact together in cardiovascular prevention? A meta-analysis of powerful or factorial randomized controlled trials. », Serveur académique Lausannois, ID : 10.1016/j.therap.2022.04.004
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To explore whether preventive cardiovascular drugs (antihypertensive, antiplatelet, lipid lowering and hypoglycemic agents) interact together in cardiovascular prevention. We searched PubMed®, Web of science™, Embase and Cochrane library for powerful randomized placebo-controlled trials (>1000 patients). We explored whether drug effect on major vascular events changed according to cross-exposure to other drug classes or to cardiovascular risk factors (hypertension or type 2 diabetes), through a meta-analysis of relative odds ratio computed by trial subgroups. A significant interaction was suggested from confidence intervals of the ratio of odds ratios, when they excluded neutral value of 1. In total, 14 trials with 178,398 patients were included. No significant interaction was observed between co-prescribed drugs or between these medications and type 2 diabetes/hypertension status. Our meta-analysis is the first one to evaluate drug-drug and drug-hypertension/type 2 diabetes status interactions in terms of cardiovascular risks: we did not observe any significant interaction. This indirectly reinforces the rationale of using several contrasted mechanisms to address cardiovascular prevention; and allows the combination effect prediction by a simple multiplication of their odds ratios. The limited availability of data reported or obtained from authors is a strong argument in favor of data sharing.