Costs and effectiveness of fingolimod versus alemtuzumab in the treatment of highly active relapsing-remitting multiple sclerosis in the UK: re-treatment, discount, and disutility.

OBJECTIVE: Patients with relapsing-remitting multiple sclerosis (RRMS) treated with disease modifying therapies (DMTs) who continue to experience disease activity may be considered for escalation therapies such as fingolimod, or may be considered for alemtuzumab. Previous economic modeling used Markov models; applying one alternative technique, discrete event simulation (DES) modeling, allows re-treatment and long-term adverse events (AEs) to be included in the analysis. METHODS: A DES was adapted to model relapse-triggered re-treatment with alemtuzumab and the effect of including ongoing quality-adjusted life year (QALY) decrements for AEs that extend beyond previous 1-year Markov cycles. As the price to the NHS of fingolimod in the UK is unknown, due to a confidential patient access scheme (PAS), a variety of possible discounts were tested. The interaction of re-treatment assumptions for alemtuzumab with the possible discounts for fingolimod was tested to determine which DMT resulted in lower lifetime costs. The lifetime QALY results were derived from modeled treatment effect and short- and long-term AEs. RESULTS: Most permutations of fingolimod PAS discount and alemtuzumab re-treatment rate resulted in fingolimod being less costly than alemtuzumab. As the percentage of patients who are re-treated with alemtuzumab due to experiencing a relapse approaches 100% of those who relapse whilst on treatment, the discount required for fingolimod to be less costly drops below 5%. Consideration of treatment effect alone found alemtuzumab generated 0.2 more QALYs/patient; the inclusion of AEs up to a duration of 1 year reduced this advantage to only 0.14 QALYs/patient. Modeling AEs with a lifetime QALY decrement found that both DMTs generated very similar QALYs with the difference only 0.04 QALYs/patient. CONCLUSIONS: When the model captured alemtuzumab re-treatment and long-term AE decrements, it was found that fingolimod is cost-effective compared to alemtuzumab, assuming application of only a modest level of confidential PAS discount.

A discrete event simulation to model the cost-utility of fingolimod and natalizumab in rapidly evolving severe relapsing-remitting multiple sclerosis in the UK.

OBJECTIVE: Two disease-modifying therapies are licensed in the EU for use in rapidly-evolving severe (RES) relapsing-remitting multiple sclerosis (RRMS), fingolimod and natalizumab. Here a discrete event simulation (DES) model to analyze the cost-effectiveness of natalizumab and fingolimod in the RES population, from the perspective of the National Health Service (NHS) in the UK, is reported. METHODS: A DES model was developed to track individual RES patients, based on Expanded Disability Status Scale scores. Individual patient characteristics were taken from the RES sub-groups of the pivotal trials for fingolimod. Utility data were in line with previous models. Published costs were inflated to NHS cost year 2015. Owing to the confidential patient access scheme (PAS) discount applied to fingolimod in the UK, a range of discount levels were applied to the fingolimod list price, to capture the likelihood of natalizumab being cost-effective in a real-world setting. RESULTS: At the lower National Institute of Health and Care Excellence (NICE) threshold of £20,000/quality-adjusted life year (QALY), fingolimod only required a discount greater than 0.8% of list price to be cost-effective. At the upper threshold of £30,000/QALY employed by the NICE, fingolimod was cost-effective if the confidential discount is greater than 2.5%. Sensitivity analyses conducted using fingolimod list-price showed the model to be most sensitive to changes in the cost of each drug, particularly fingolimod. CONCLUSIONS: The DES model shows that only a modest discount to the UK fingolimod list-price is required to make fingolimod a more cost-effective option than natalizumab in RES RRMS.

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. 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.