To further explore MS patient’s ability to work, we therefore investigated demographic and clinical factors influencing employment status in a population based MS cohort from Sogn and Fjordane County, Western Norway. We used a binary regression model to estimate odds ratios in order to identify possible independent factors associated with the outcome variable. Building a regression model included several steps as described by Hosmer and Lemeshow. The selection process of covariates related to employment began with a univariate analysis. Any variable with Lambrolizumab was selected as a candidate for the multivariate model based on the Wald test. More traditional levels of p,0.05 can fail in identifying variables known to be important. All candidates were included in a model and one by one nonsignificant variables were removed until the final model containing all significant variables. In this process large changes in OR for the remaining variables were thoroughly inspected. The Hosmer- Lemeshow goodness of fit test was used to test good fit for our regression model. Further, cross-tabulation and analysis of missing data in the multivariate analysis with respect to age at onset,Etanercept married status and gender were performed, and there were no significant differences recorded between missing data to the cases included in the analysis. This study set out with the aim of evaluating employment status in a county based MS population and to investigate characteristic demographic and clinical features in MS-subtypes. One notable finding was the clear differences in employment rate in the various subtypes of MS. In the present study we found that 66.1% of patients with RRMS were employed full-time or part –time. In comparison, only 24.3% of SPMS patients and 14.8% of PPMS patients were employed. These findings are in line with two former studies, showing that patients with RRMS with lower disability levels have a higher employment rate than patients with progressive types of MS with more pronounced disabilities.