Abstract
Multistate processes provide a convenient framework when interest lies in characterising the transition intensities between a set of defined states. If, however, there is an unobserved event of interest (not known if and when the event occurs), which when it occurs stops future transitions in the multistate process from occurring, then drawing inference from the joint multistate and event process can be problematic. In health studies, a particular example of this could be resolution, where a resolved patient can no longer experience any further symptoms, and this is explored here for illustration. A multistate model that includes the state space of the original multistate process but partitions the state representing absent symptoms into a latent absorbing resolved state and a temporary transient state of absent symptoms is proposed. The expanded state space explicitly distinguishes between resolved and temporary spells of absent symptoms through disjoint states and allows the uncertainty of not knowing if resolution has occurred to be easily captured when constructing the likelihood; observations of absent symptoms can be considered to be temporary or having resulted from resolution. The proposed methodology is illustrated on a psoriatic arthritis data set where the outcome of interest is a set of intermittently observed disability scores. Estimated probabilities of resolving are also obtained from the model. © 2016 The Authors. Statistics in Medicine Published by John Wiley & Sons Ltd.
Highlights
In many pathological processes, patients may completely recover and be free of any further symptoms
For a set of intermittently observed psoriatic arthritis (PsA) patients, the primary aims of this paper are to characterise the rates of progression between a set of disability states and to consider the extent to which resolution occurs
We propose an expanded multistate model, which can naturally handle intermittent observations, that composes of (i) a latent absorbing state representing resolution, (ii) a partially latent transient state of temporary non-disability and (iii) various transient states of disability severity
Summary
Patients may completely recover and be free of any further symptoms. For a set of intermittently observed psoriatic arthritis (PsA) patients, the primary aims of this paper are to characterise the rates of progression between a set of disability states and to consider the extent to which resolution occurs Some complications in this scenario arise from the unknown times in which the disability status changes (transitions are interval censored) and not knowing if and when a patient has resolved. Note that the latter complication is in contrast to the standard time-to-event setting because it is generally known if the event of interest has occurred, such as death, even if the occurrence time is not known. Because non-disability is partitioned into a latent and partially latent state representing resolved and temporary non-disability, respectively, inference on each event can be obtained explicitly, and the uncertainty
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