Correlated multistate models for multiple processes: an application to renal disease progression in systemic lupus erythematosus .

Bidirectional changes over time in the estimated glomerular filtration rate and in urine protein content are of interest for the treatment and management of patients with . Although these processes may be modelled by separate multistate models, the processes are likely to be correlated within patients. Motivated by the application, we develop a new multistate modelling framework where subject-specific random effects are introduced to account for the correlations both between the processes and within patients over time. Models are fitted by using bespoke code in standard statistical software. A variety of forms for the random effects are introduced and evaluated by using the data from the Systemic Lupus International Collaborating Clinics.