History-Adjusted Marginal Structural Models: Optimal Treatment Strategies

Much of clinical medicine involves choosing a future treatment plan that is expected to optimize a patient\u27s long-term outcome, and modifying this treatment plan over time in response to changes in patient characteristics. However, dynamic treatment regimens, or decision rules for altering treatment in response to time-varying covariates, are rarely estimated based on observational data. In a companion paper, we introduced a generalization of Marginal Structural Models, named History-Adjusted Marginal Structural Models, that estimate modification of causal effects by time-varying covariates. Here, we illustrate how History-Adjusted Marginal Structural Models can be used to identify a specific type of optimal dynamic treatment regimen. Estimation and interpretation of this dynamic treatment regimen are illustrated using an example drawn from the treatment of HIV infection using antiretroviral drugs