Statistical analysis of study endpoints In order to compare the effects between the two study arms the investigators will perform t-tests and/or multivariable linear regression models. The latter technique allows us to use continuous outcome variables and both continuous and dichotomous independent variables. The efficacy endpoint of interest will be added to the model as dependent variable. Treatment group will be added as independent categorical variable. Appropriate covariates may be added to the model. Baseline measurements of specific variables (e.g. age, gender) will be added to the regression models as covariates should differences in the baseline values of these variables occur between treatment groups. Moreover, corrections will be performed when relevant for the specific endpoint. The possible covariates will be elaborated prior to conducting the statistics. For possible confounders, the investigators will test whether there is an association with both the dependent and independent variable (p <0.1). If this is the case, this confounder will be added to the model as covariate. Since all outcome variables - primary, secondary and exploratory - are continuous, this statistical technique can be applied.