This article discusses predicting damage in patients with juvenile myositis after treatment with various medications. These data were taken from medical records and not randomized. Investigators advocate using propensity scores for analysis of such non-randomized studies in order to reduce the effect of selection of treatment. Thus far, the studies have typically been comparing drug administration versus no drug after including a propensity score to compensate for potential bias in selecting patients for use of the agent. In this study, we use propensity scoring for multiple treatments given singly or in combination. We study two methods. We use a multiple logistic regression model with continuous propensity scores and a model that develops strata based on the dichotomous treatment assignment (received drug or not). We find the multiple logistic regression models predict damage better than the dichotomous model. In many cases, the propensity score also accounts for the effect of the treatment.