Abstract
In psoriatic arthritis, permanent joint damage characterizes disease progression and represents a major debilitating aspect of the disease. Understanding the process of joint damage will assist in the treatment and disease management of patients. Multistate models provide a means to examine patterns of disease, such as symmetric joint damage. Additionally, the link between damage and the dynamic course of disease activity (represented by joint swelling and stress pain) at both the individual joint level and otherwise can be represented within a correlated multistate model framework. Correlation is reflected through the use of random effects for progressive models and robust variance estimation for non-progressive models. Such analyses, undertaken with data from a large psoriatic arthritis cohort, are discussed and the extent to which they permit causal reasoning is considered. For this, emphasis is given to the use of the Bradford Hill criteria for causation in observational studies and the concept of local (in)dependence to capture the dynamic nature of the relationships.
Highlights
From a clinical perspective, it is generally held that better understanding of a disease process will lead to more appropriate treatment and disease management of patients
In our discussion of psoriatic arthritis disease progression that follows, we use both the Bradford Hill criteria and Schweder’s localdependence concept to reason about whether associations that were found in our analyses, which are based on multistate models at the individual joint level of the hands, can be considered causal
The study of the progression of psoriatic arthritis by using multistate models has provided an intuitive way of examining the disease process from a dynamic perspective
Summary
It is generally held that better understanding of a disease process will lead to more appropriate treatment and disease management of patients. In this paper we illustrate their use for the study of disease progression in psoriatic arthritis In his 1970 seminal paper, Schweder (1970) introduced the concept of local (in)dependence between components of a composable finite Markov process. Local independence is an asymmetric relationship, i.e. it has a direction, and so, Yk being locally independent of Yj does not necessarily imply that Yj is locally independent of Yk over the same infinitesimal time interval This important concept of local independence was extended in Aalen (1987) to apply to more general stochastic processes that admit a Doob–Meyer decomposition, with unrelated innovations. In our discussion of the progression of psoriatic arthritis disease that follows, we use Schweder’s local (in)dependence concept as a means of characterizing the findings from dynamic analyses based on multistate models. After 30 years of data collection and 20 years of previous analyses, it seems appropriate to take up this challenge with the psoriatic arthritis cohort data that are discussed
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