Application of marginal structural models for causal inference on the treatment effect for overall survival in randomized controlled trials with control arm patients switching to active intervention after disease progression.

This research explores the application of marginal structural models (MSMs) in evaluating the causal treatment effect of active intervention versus control on overall survival in randomized clinical trials (RCTs) allowing for control arm patients to switch to active intervention after disease progression. When MSMs are applied in RCTs under this type of treatment switching setting, the question of interest and model specifications differ from both observational studies and from RCTs where patients in both arms are permitted to take alternative treatments after disease progression. A violation of structural positivity may result as an undesired consequence if MSM model weights are constructed using data directly from both arms. This research proposes a two-step approach to avoid this issue. Through simulation studies, it is demonstrated that the proposed approach allows for MSM to be used for analyzing survival data to detect causal active treatment effects under this one-way treatment switching setting. Additionally, estimation for the causal effect of the active intervention as the next line (post-disease progression) therapy can also be obtained from the MSM approach. A case study is presented to illustrate the application of MSMs under this type of treatment switching setting.