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Updated: Nov 8, 2025

A Method of Trigonometric Modelling of Seasonal Variation Demonstrated with Multiple Sclerosis Relapse Data
Published on: December 9, 2015
Disease modifying therapies in relapsing-remitting multiple sclerosis: A systematic review and network meta-analysis
Zhuoyi Liu1, Qiao Liao2, Haicheng Wen3
1Department of Anesthesiology, Xiangya Hospital, Central South University, Changsha, Hunan, China.
Objective:
To compare the efficacy and compliance of up-to-date disease modifying therapies (DMTs) in patients with remitting-relapsing MS (RRMS).
Methods:
We searched PubMed, EMBASE and Cochrane Library for eligible studies. Annualized relapse rate, discontinuation due to adverse events (AEs) were assessed as primary outcomes. Sensitivity analysis and inconsistency detection were performed to evaluated whether exclusion of high-risk studies affected the validity. Risk of bias was assessed using Cochrane's Risk-of-Bias Tool 2. Surface under the cumulative ranking curve (SUCRA) was used to estimate the rankings among different DMTs.
Results:
21 studies were included for main report. Seven studies were evaluated as "high risk" and were therefore excluded. Exclusion of high-risk studies did not affect the validity of evidence. The risk of relapses for most DMTs except Betaseron 50 μg was significantly lower comparing to placebo. Incompliance in patients treated with DMTs was not significantly increased comparing to placebo. Dimethyl fumarate and ocrelizumab had superiority in improving MRI outcomes. Ocrelizumab and ofatumumab had the largest reduction of risk in disability progression at 3 months. Referring to SUCRA, ofatumumab, alemtuzumab and natalizumab showed the best efficacy and compliance.
Conclusion:
The present study demonstrated the hierarchy of DMTs treating RRMS. Ofatumumab, alemtuzumab and natalizumab have superiority with respect to effectiveness and compliance. More studies are required to explore the long-term effect of DMTs. Our findings could provide helpful information and contribute to clinical treatment decision-making.
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