Comparing treatment policies with assistance from the structural nested mean model

Xi Lu, Kevin G. Lynch, David W. Oslin and Susan Murphy

Biometrics, 2016, vol. 72, issue 1, 10-19

Abstract: type="main" xml:lang="en">

Treatment policies, also known as dynamic treatment regimes, are sequences of decision rules that link the observed patient history with treatment recommendations. Multiple, plausible, treatment policies are frequently constructed by researchers using expert opinion, theories, and reviews of the literature. Often these different policies represent competing approaches to managing an illness. Here, we develop an “assisted estimator” that can be used to compare the mean outcome of competing treatment policies. The term “assisted” refers to the fact estimators from the Structural Nested Mean Model, a parametric model for the causal effect of treatment at each time point, are used in the process of estimating the mean outcome. This work is motivated by our work on comparing the mean outcome of two competing treatment policies using data from the ExTENd study in alcohol dependence.

Date: 2016
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