OBJECTIVES: Multiple Sclerosis (MS) underwent a paradigm shift with the advent of Disease-Modifying Treatments (DMTs) at the beginning of the new century (2001). Up to some extent, the cost-effectiveness of these new treatments was demonstrated, using traditional outcomes like Annualized Relapse Rate (ARR) and Confirmed Disability Progression (CDP). However, ARR and CDP only partially cover MS patients’ symptoms. Other outcomes such as fatigue, Progression Independent of Relapse Activity (PIRA) and Brain Volume Loss (BVL), for instance, potentially bring additional value. This research aims to measure the theoretical gain that could be seen by incorporating these outcomes as additional variables into a cost-effectiveness model, from the perspective of England’s National Health Service (NHS).

METHODS: A cohort-based Markov model with 11 health states (10 Expanded Disability Status Scale (EDSS) plus death) was developed in R, based on a previously published model. Traditional parameters were derived from trials, past submissions, NHS, and literature. Fatigue was implemented as a discrete change of utility value(s) (one-shot change, change in a range of EDSS states, time-dependent change), PIRA as an additional rate independent of EDSS state, and BVL was implemented as a modifier of the CDP rate in several scenarios.

RESULTS: Compared to the initial base case, the inclusion of fatigue as a utility modifier could in an ICER change from -40% to +40%. Depending on the scenario, the inclusion of PIRA results in similar changes. Finally, a change in BVL does not impact the ICER significantly.

CONCLUSIONS: This research highlights the potential of the inclusion of non-traditional outcomes to modify our perception of the cost-effectiveness of future DMTs for MS. In their current collection in clinical trials, these variables could be double counted. This research paves the way for future MS cost-effectiveness models that are not based on ARR and CDP primarily.