Estimation of drug effect in radiographic progression for rheumatoid arthritis and psoriatic arthritis.

Abstract

To demonstrate the treatment effect on structural damage in rheumatoid arthritis (RA) and psoriatic arthritis (PsA), radiographic images of hands and feet are scored according to Sharp scoring systems in randomized clinical trials. However, the quantification of such an effect is challenging because the overall mean progression is lack of clinical interpretation. This article attempts to shed a light on the statistical challenges resulted from its scoring methods and heterogeneity of the study population and proposes a mixture distribution model approach to fit radiographic progression data. With such a model, the drug effect is fully captured by the mean progression of those patients who would progress in the study period under the control treatment. The resulting regression model also lends a tool in examining prognostic factors for radiographic progression. Simulations have been carried out to evaluate the precision of the parameter estimation procedure. Using the data examples from RA and PsA, we will show that the mixture distribution approach provides a better goodness of fit and leads to a casual inference of the study drug, hence a clinically meaningful interpretation.