Statistical methods for assessing drug interactions using observational data.

ABSTRACT: With advances in medicine, many drugs and treatments become available. On the one hand, polydrug use (i.e. using more than one drug at a time) has been used to treat patients with multiple morbid conditions, and polydrug use may cause severe side effects. On the other hand, combination treatments have been successfully developed to treat severe diseases such as cancer and chronic diseases. Observational data, such as electronic health record data, may provide useful information for assessing drug interactions. In this article, we propose using marginal structural models to assess the average treatment effect and causal interaction of two drugs by controlling confounding variables. The causal effect and the interaction of two drugs are assessed using the weighted likelihood approach, with w

SUBMITTER: Xu Q 

PROVIDER: S-EPMC10810670 | biostudies-literature | 2024

REPOSITORIES: biostudies-literature