The parametric g-formula for time-to-event data: intuition and a worked example.
The parametric g-formula for time-to-event data: intuition and a worked example.
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用于事件时间数据的参数G形式：直觉和有效的示例。
DOI：
10.1097/ede.0000000000000160
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发表时间：
2014-11
期刊：
影响因子：
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通讯作者：
Cole SR
中科院分区：
文献类型：
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作者：
Keil AP;Edwards JK;Richardson DB;Naimi AI;Cole SR
参数g公式可用于估计政策、干预或治疗的效果。与标准回归方法不同，参数g公式可用于调整受先前暴露影响的时变混杂因素。到目前为止，已发表的应用该方法的例子还很少。我们对参数g公式进行了简单的介绍，并说明了它在骨髓移植患者的一项小型队列研究中的应用，在该研究中，治疗对死亡率的影响受到时变混杂的影响。标准回归调整对治疗对死亡率的影响的估计相对于g公式得到的估计是有偏差的。G公式允许估计公共卫生官员的相关参数：在假设干预下死亡风险的变化，例如减少接触有害物质或引入有益的新治疗方法。我们提出了一种简单的方法来实现参数g公式，该公式足够普遍，可以很容易地适应许多与公共卫生相关的设置。
The parametric g-formula can be used to estimate the effect of a policy, intervention, or treatment. Unlike standard regression approaches, the parametric g-formula can be used to adjust for time-varying confounders that are affected by prior exposures. To date, there are few published examples in which the method has been applied. We provide a simple introduction to the parametric g-formula and illustrate its application in analysis of a small cohort study of bone marrow transplant patients in which the effect of treatment on mortality is subject to time-varying confounding. Standard regression adjustment yields a biased estimate of the effect of treatment on mortality relative to the estimate obtained by the g-formula. The g-formula allows estimation of a relevant parameter for public health officials: the change in the hazard of mortality under a hypothetical intervention, such as reduction of exposure to a harmful agent or introduction of a beneficial new treatment. We present a simple approach to implement the parametric g-formula that is sufficiently general to allow easy adaptation to many settings of public health relevance.