How to use marginal structural models in randomized trials to estimate the natural direct and indirect effects of therapies mediated by causal intermediates.

Background: Although intention-to-treat analysis is a standard approach, additional supplemental analyses are often required to evaluate the biological relationship among interventions, intermediates, and outcomes. Therefore, we need to evaluate whether the effect of an intervention on a particular outcome is mediated by a hypothesized intermediate variable.
Purpose: To evaluate the size of the direct effect in the total effect, we applied the marginal structural model to estimate the average natural direct and indirect effects in a large-scale randomized controlled trial (RCT). Method The average natural direct effect is defined as the difference in the probability of a counterfactual outcome between the experimental and control arms, with the intermediate set to what it would have been, had the intervention been a control treatment. We considered two marginal structural models to estimate the average natural direct and indirect effects introduced by VanderWeele (Epidemiology 2009) and applied them in a large-scale RCT - the Candesartan Antihypertensive Survival Evaluation in Japan (CASE-J trial) - that compared angiotensin receptor blockers and calcium-channel blockers in high-risk hypertensive patients.
Results: There were no strong blood pressure-independent or dependent effects; however, a systolic blood pressure reduction of about 1.9  mmHg suppressed all events. Compared to the blood pressure-independent effects of calcium channel blockers, those of angiotensin receptor blockers contributed positively to cardiovascular and cardiac events, but negatively to cerebrovascular events.
Limitations: There is a particular condition for estimating the average natural direct effect. It is impossible to check whether this condition is satisfied with the available data.
Conclusion: We estimated the average natural direct and indirect effects through the achieved systolic blood pressure in the CASE-J trial. This first application of estimating the average natural effects in an RCT can be useful for obtaining an in-depth understanding of the results and further development of similar interventions.