Modelling disease activity in juvenile dermatomyositis: A Bayesian approach.

Juvenile dermatomyositis is the most common form of the juvenile idiopathic inflammatory myopathies characterised by muscle and skin inflammation, leading to symmetric proximal muscle weakness and cutaneous symptoms. It has a fluctuating course and varying prognosis. In a Bayesian framework, we develop a joint model for four longitudinal outcomes, which accounts for within individual variability as well as inter-individual variability. Correlations among the outcome variables are introduced through a subject-specific random effect. Moreover, we exploit an approach similar to a hurdle model to account for excess of a specific outcome in the response. Clinical markers and symptoms are used as covariates in a regression set-up. Data from an ongoing observational cohort study are available, providing information on 340 subjects, who contributed 2725 clinical visits. The model shows good performance and yields efficient estimations of model parameters, as well as accurate predictions of the disease activity parameters, corresponding well to observed clinical patterns over time. The posterior distribution of the by-subject random intercepts shows a substantial correlation between two of the outcome variables. A subset of clinical markers and symptoms are identified as associated with disease activity. These findings have the potential to influence clinical practice as they can be used to stratify patients according to their prognosis and guide treatment decisions, as well as contribute to on-going research about the most relevant outcome markers for patients affected by juvenile dermatomyositis.