In MS, treatment start or switch is prompted by evidence of disease activity, often presenting as relapses or disability progression.  Whilst immunomodulatory therapies reduce disease activity, the time required to attain maximal effect is unclear. 

To develop a method that allows identification of the time to full clinically manifest effect of multiple sclerosis (MS) treatments (‘therapeutic lag’) on clinical disease activity.

Data from MSBase, a multinational MS registry, and OFSEP, the French national registry, were used.  Patients diagnosed with MS, minimum 1-year exposure to MS treatment, minimum 3-year pre-treatment follow up and yearly review were included in the analysis.  For analysis of disability progression, all events in the subsequent 5-year period were included in the analysis.  Density curves, representing incidence of relapses and 6-month confirmed progression events, were separately constructed for each sufficiently represented therapy.  Monte Carlo simulations were performed to identify the first local minimum of the first derivative after treatment start. This point represents the point of stabilisation of treatment effect, after the maximum treatment effect was observed.  The method was developed using MSBase, and externally validated in OFSEP.  A merged MSBase-OFSEP cohort was used for all subsequent analyses.

11180 eligible treatment epochs were identified for analysis of relapses and 4088 treatment epochs for disability progression.  There were no significant differences between the results of discovery and validation analyses.  The duration of therapeutic lag for relapses was calculated for 10 therapies and ranged between 12-30 weeks.  The duration of therapeutic lag for disability progression was calculated for 7 therapies and ranged between 30-70 weeks.