Systematic literature review and network meta-analysis in highly active relapsing–remitting multiple sclerosis and rapidly evolving severe multiple sclerosis

OBJECTIVE: Multiple sclerosis (MS) is a chronic, neurodegenerative autoimmune disorder affecting the central nervous system. Relapsing–remitting MS (RRMS) is the most common clinical form of MS and affects ∼85% of cases at onset. Highly active (HA) and rapidly evolving severe (RES) RRMS are 2 forms of RRMS amenable to disease-modifying therapies (DMT). This study explored the efficacy of fingolimod relative to other DMTs for the treatment of HA and RES RRMS. METHODS: A systematic literature review (SLR) was conducted to identify published randomised controlled trials in HA and RES RRMS. Identified evidence was vetted, and a Bayesian network meta-analysis (NMA) was performed to evaluate the relative efficacy of fingolimod versus dimethyl fumarate (DMF) in HA RRMS and versus natalizumab in RES RRMS. RESULTS: For HA RRMS, the SLR identified 2 studies with relevant patient subgroup data: 1 comparing fingolimod with placebo and the other comparing DMF with placebo. 3 studies were found for RES RRMS: 1 comparing fingolimod with placebo and 2 studies comparing natalizumab with placebo. NMA results in the HA population showed a favourable numerical trend of fingolimod versus DMF assessed for annualised relapse rate (ARR) and 3-month confirmed disability progression. For the RES population, the results identified an increase of ARR and 3-month confirmed disability progression for fingolimod versus natalizumab (not statistically significant). Sparse study data and the consequently high uncertainty around the estimates restricted our ability to demonstrate statistical significance in the studied subgroups. CONCLUSIONS: Data limitations are apparent when conducting an informative indirect comparison for the HA and RES RRMS subgroups as the subgroups analyses were retrospective analyses of studies powered to indicate differences across entire study populations. Comparisons across treatments in HA or RES RRMS will be associated with high levels of uncertainty until new data are collected for these subgroups.