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Intensity-based multistate models provide a useful framework forcharacterizing disease processes, the introduction of interventions, loss tofollow-up, and other complications arising in the conduct of randomized trialsstudying complex life history processes. Within this framework we discuss theissues involved in the specification of estimands and show the limiting valuesof common estimators of marginal process features based on cumulative incidencefunction regression models. When intercurrent events arise we stress the needto carefully define the target estimand and the importance of avoiding targetsof inference that are not interpretable in the real world. This hasimplications for analyses, but also the design of clinical trials whereprotocols may help in the interpretation of estimands based on marginalfeatures.

Multistate Models as a Framework for Estimand Specification in Clinical Trials of Complex Processes