An algorithm using clinical data to predict the optimal individual glucocorticoid dosage to treat multiple sclerosis relapses.

Background: Glucocorticoid (GC) pulse therapy is used for multiple sclerosis (MS) relapse treatment; however, GC resistance is a common problem. Considering that GC dosing is individual with several response-influencing factors, establishing a predictive model, which supports clinicians to estimate the maximum GC dose above which no additional therapeutic value can be expected presents a huge clinical need.

Method: We established two, independent retrospective cohorts of MS patients.