RESUMO
BACKGROUND: Several disease-modifying treatments (DMTs) for relapsing-remitting multiple sclerosis (RRMS) reduce relapse rates and slow disease progression. RRMS DMTs have varying efficacy and administration routes; DMTs prescribed first may not be the most effective on relapses or disease progression. Here, we aimed to quantify the benefit of initiating ofatumumab, a high-efficacy DMT, earlier in the treatment pathway. METHODS: Aggregate data from a real-world cohort of patients with RRMS, who were eligible for dimethyl fumarate (DMF) or ofatumumab treatment within the UK National Health Service (N = 615), were used to produce a simulated patient cohort. The cohort was tracked through a discrete event simulation (DES) model, based on the Expanded Disability Status Scale (EDSS), with a lifetime time horizon. Outcomes assessed were: mean number of relapses, time to wheelchair (EDSS ≥7), and time to death. Two modeling approaches were used. The first compared outcomes between two treatment sequences (base case: ofatumumab to natalizumab versus DMF to ofatumumab). The second incorporated a time-specific delay of 1-5 years for switching from DMF to ofatumumab; the difference in outcomes as a function of increasing delay to ofatumumab are reported. RESULTS: Compared with delayed ofatumumab, fewer relapses and increased time to wheelchair were predicted for earlier ofatumumab in the treatment-sequence approach (mean relapses over the lifetime time horizon: 8.63 versus 9.00; time to wheelchair: 17.55 versus 16.60 years). Time to death was similar for both sequences. At Year 10, a numerically greater proportion of patients receiving earlier ofatumumab had mild disease (EDSS 0-3: 44.12% versus 40.06%). Greater differences, reflecting poorer outcomes, were predicted for relapses and time to wheelchair with increasing delays to ofatumumab treatment. CONCLUSIONS: The DES model provided a means by which the magnitude of benefit associated with earlier ofatumumab initiation could be quantified; fewer relapses and a prolonged time to wheelchair were predicted.
