Citation
Keil, Alexander P.; Edwards, Jessie K.; Richardson, David B.; Naimi, Ashley I.; & Cole, Stephen R. (2014). The Parametric G-Formula for Time-To-Event Data: Intuition and a Worked Example. Epidemiology, 25(6), 889-897. PMCID: PMC4310506Abstract
BACKGROUND: 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.METHODS: We provide a simple introduction to the parametric g-formula and illustrate its application in an 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.
RESULTS: Standard regression adjustment yields a biased estimate of the effect of treatment on mortality relative to the estimate obtained by the g-formula.
CONCLUSIONS: 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.
URL
http://dx.doi.org/10.1097/EDE.0000000000000160Reference Type
Journal ArticleYear Published
2014Journal Title
EpidemiologyAuthor(s)
Keil, Alexander P.Edwards, Jessie K.
Richardson, David B.
Naimi, Ashley I.
Cole, Stephen R.