From the Department of Neurology (N.A.H., N.M.D.V., B.R.B., S.K.L.D.), Radboud University Medical Centre; Donders Institute for Brain, Cognition and Behaviour (N.A.H., N.M.D.V., B.R.B., S.K.L.D.), Nijmegen, the Netherlands; Population Health Sciences (G.H., Y.B.-S.), Bristol Medical School, University of Bristol; Medical Research Council Integrative Epidemiology Unit at the University of Bristol (G.H.), Population Health Sciences, Bristol Medical School, University of Bristol, United Kingdom; and Center of Expertise for Parkinson & Movement Disorders (N.M.D.V., B.R.B., S.K.L.D.), Nijmegen, the Netherlands.
Neurology. 2024 Jul 9;103(1):e209547. doi: 10.1212/WNL.0000000000209547. Epub 2024 Jun 10.
Mediation analysis can be applied in medical research with the aim of understanding the pathways that operate between an exposure and its effects on an outcome. This method can help to improve our understanding of pathophysiologic mechanisms and may guide the choice of potential treatment strategies. Traditional mediation analysis decomposes the total effect of an intervention on the outcome into 2 effects: (1) an indirect effect, from exposure using a mediator to the outcome, and (2) a direct effect, directly from exposure to outcome. A limitation of this method is that it assumes no interaction between the exposure and the mediator, which can either lead to an over- or underestimation of clinically relevant effects. The "4-way decomposition" method has the advantage of overcoming this limitation. Specifically, the total effect of an exposure on the outcome is decomposed into 4 elements: (1) reference interaction (interaction only), (2) mediated interaction (mediation and interaction), (3) the pure indirect effect (mediation but not interaction), and (4) the direct effect (no mediation and no interaction). We provide a guide to select the most appropriate method to investigate and decompose any causal effect given the research question at hand. We explain the application of the 4-way decomposition and illustrate this with a real-world example of how aerobic exercise may influence motor function in persons with Parkinson disease.
中介分析可应用于医学研究,旨在了解暴露与对结局的影响之间的作用途径。这种方法有助于加深对病理生理机制的理解,并可能指导潜在治疗策略的选择。传统的中介分析将干预对结局的总效应分解为 2 种效应:(1)间接效应,即暴露通过中介对结局的影响,(2)直接效应,即暴露对结局的直接影响。这种方法的一个局限性是它假设暴露和中介之间没有相互作用,这可能导致对临床相关效应的高估或低估。“四向分解”方法具有克服这一局限性的优势。具体来说,暴露对结局的总效应可分解为 4 个要素:(1)参考相互作用(仅相互作用),(2)中介相互作用(中介和相互作用),(3)纯间接效应(仅中介而无相互作用),以及(4)直接效应(无中介和无相互作用)。我们提供了一个指南,用于根据手头的研究问题选择最合适的方法来调查和分解任何因果效应。我们解释了四向分解的应用,并通过一个真实的例子说明了有氧运动如何影响帕金森病患者的运动功能,这说明了这一点。