Plotting summary predictions in multistate survival models: Probabilities of relapse and death in remission for bone marrow transplantation patients

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Abstract
Multistate survival analysis usually involves a series of detailed regression analyses describing transitions between various states. There is an often neglected need for the many estimates resulting from such an analysis to be re‐synthesized into summary statements, such as prediction of various outcomes from specified patient histories. Arjas and Eerola recently proposed a framework for dynamic probabilistic causality which has calculation of such prediction statements as a central tool. We illustrate these procedures on data from a multicentre bone marrow transplantation study, with death while in remission and relapse as terminal events and recovery of the patients's platelets to a normal level and the onset of acute graft‐versus‐host disease as intermediate events, using Cox regression models throughout. Among the features illustrated by the resulting plots is a strong effect on death while in remission if the platelets do not recover within the first three months.

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