Mediation Analysis of Path-Specific Effects in Randomised Clinical Trials With Repeatedly Measured Mediators and...

Questions about the mode of action (MoA) of a drug have interest to scientific communities as well as regulatory authorities. In the absence of an already established MoA such questions may be enlightened by causal mediation analysis in clinical trials. In this paper, we present a general framework that facilitates causal mediation analysis in a setting of a clinical trial where both the outcome of interest, one or more mediators and additional potential post-baseline confounders are measured repeatedly at planned visits. The targeted estimands are path-specific effects implicitly defined from a causal diagram that includes all the longitudinally measured variables. The framework including estimation method is developed with inspiration from a similar approach for time-to-event outcomes. The novelty of our approach compared to many currently used methods is that it directly establishes MoA, takes the full amount of longitudinal data into account, and properly adjusts for sources of confounding. We motivate and illustrate the approach with examples from the STEP 2 clinical trial. Modular SAS code is provided that can be used in a general setting.