Cost-utility of fingolimod compared with dimethyl fumarate in highly active relapsing-remitting multiple sclerosis (RRMS) in England

Objective:The cost-effectiveness of new oral disease-modifying therapies (DMTs) has not been modeled in highly active (HA) relapsing-remitting multiple sclerosis (RRMS) requiring escalation therapy. This study sought to model the cost-effectiveness of fingolimod compared to dimethyl fumarate (DMF), for which relevant HA RRMS sub-group data were available, from the perspective of the National Health Service (NHS) in England.Methods:A cohort Markov model based on Expanded Disability Status Scale scores, similar to previous model designs, was constructed. Published post hoc clinical data in the HA RRMS sub-groups were taken from the pivotal trials for fingolimod and DMF vs placebo. Utility data for each health state and for relapses were used in line with previous similar models. Published costs were inflated to NHS cost year 2013-2014 and UK list prices used for both drugs. Possible Patient Access Scheme (PAS) discount scenarios were investigated.Results:In the base case, using list prices for each DMT, the average probabilistic incremental cost-effectiveness ratio (ICER) for fingolimod vs DMF was found to be 14,076, with a 73% chance of fingolimod being cost-effective at a willingness-to-pay threshold of 30,000 pound. Scenario and sensitivity analyses showed that uncertainty in disability progression efficacy was a key model driver. The model was robust to other changes and the majority of PAS permutations do not contradict the base case finding of cost-effectiveness of fingolimod.Conclusions:In conclusion, fingolimod remains cost-effective in HA RRMS following the introduction of DMF to the UK market, and this paper supports the evidence that has led fingolimod to be the only oral DMT reimbursed for HA RRMS in England. This model supports the restriction imposed by National Institute for Health and Care Excellence (NICE) on DMF in HA RRMS and highlights the importance of considering different sub-groups of multiple sclerosis when performing health economic analyses.