MuSER (Multiple Sclerosis Expected Rate) Predictive Model Development

Multiple Sclerosis (MS) is the most diffused among rare neurological pathologies, as it affects about 0.031% people all over the world. Its prevalence in the United States (US) was calculated to be around 0.14%, but according to National Multiple Sclerosis Society (NMSS) MS is not properly monitored and registered within American territory and the creation of a MS archive is expected to ameliorate the calculus accuracy. The aim of this work is to develop a simple but reliable biostatistical predictive model called MuSER (Multiple Sclerosis Expected Rate); it was projected based on the ascending trend that was observed during previous studies, although not dependable, is theoretically reliable, at least considering R2 coefficients. Efficiency of MuSER model will be assessed at the end of 2019. In order to predict MS incidence within an ethnically homogeneous population. Although not absolutely dependable, is theoretically reliable, at least considering R2 coefficients. Efficiency of MuSER model will be assessed at the end of 2019.