Restricted accessResearch articleFirst published online 2011-6
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.
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