Abstract

Disease-modifying therapies (DMTs) can reduce multiple sclerosis (MS) relapse rates; understanding treatment patterns and effectiveness in relapse reduction across all available DMTs using real-world data is important. We describe treatment patterns and post-DMT initiation relapses stratified by the number of pre-initiation relapses among newly treated MS patients overall, and by treatment. IBM MarketScan research databases were used to identify adult MS patients newly initiating DMTs (index event) from 01/01/2011-01/04/2016 with 12 months of continuous enrolment pre-index and post-index. MS was determined by ≥2 non-diagnostic claims with an ICD-9-CM (340) or ICD-10-CM (G35) code. Patients had not taken DMTs in the pre-index period. Non-persistence was defined as discontinuing index therapy (>60 days without DMT) or switching DMTs. Relapse was defined using a validated claims-based algorithm. The final sample consisted of 9,378 newly treated MS patients (average age, 46.7 years; 73.3%, female). Patients started with an injectable (65.5%), oral (26.1%), or infusion (8.4%, not shown) DMT. An overall 27% reduction in relapses was observed pre-index to post-index and was highest among those on oral agents (39.4%). Patients without pre-index relapse (vs those with ≥3) were more likely to be relapse-free post-index (81.6% vs 31.4%). Non-persistence was observed in 44.7% of patients, mainly due to discontinuation (90.3%). Patients with and without pre-index relapses had similar 12-month post-index persistence with DMTs (39.6% vs 38.9%); however, persistence was lower for patients with relapse within 3 (49.0% vs 62.1%) or 6 months (48.4% vs 63.2%) post-index. Those on oral agents were most persistent (50.3%) among those relapsing within 3 months. Reduction in MS relapses was observed in those initiating a DMT among treatment-naive MS patients, with better gains among those initiating oral DMTs. However, patients relapsing early during treatment exhibit lower persistence, and there is still an unmet need in these patients.

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