Abstract
BackgroundMultiple sclerosis (MS) is a heterogeneous autoimmune disease, with a rapidly evolving body of literature on disease-modifying therapy (DMT) that urgently needs to be synthesized and regularized. MethodsThe original material used for the analysis was obtained from the Web of Science Core Collection (WoSCC) in the Science Citation Index Expanded Edition (SCI-E). The data material was accessed through VOSviewer, Citespace, R package “Bibliometrix”, and Scimago Graphica for data analysis and visualization. Among them, the clustering algorithm based on the Largest Likelihood Ratio (LLR) and the burst citation algorithm is the key. ResultsAs of November 6th, 2022, 4142 publications related to emerging disease-modifying therapies (e-DMT) for MS, 6521 publications related to traditional disease-modifying therapies (t-DMT) for MS, and 1793 publications in cross-cutting disease-modifying therapies (I-DMT) for MS were included in the analysis, respectively. Publications related to DMT in MS were analyzed descriptively (for three subjects: country, institution, and author) and predictively (for two subjects: keywords and references) separately according to three sections: e-DMT, t-DMT, and I-DMT. Topics that still have relevant reference output as of 2022 include the safety of Coronavirus disease 2019 (COVID-19) mRNA vaccination, therapeutic inertia (TI), cladribine tablets, autologous hematopoietic stem cell transplantation (aHSCT), progressive multiple sclerosis, and pediatric multiple sclerosis. ConclusionThe future research focus for MS DMT is the combination trial or cross-trial of various treatment methods to improve the development of individualized treatment plans for MS patients. The exact contents of the research frontiers are included but not limited to ocrelizumab, fingolimod and other monoclonal antibodies, fumaric acid ester, cladribine tablet, aHSCT, and other interventions of randomized controlled trials (RCTs); the impact of mRNA COVID-19 vaccination on MS patients; TI, patient adherence, and other medical management issues; and continued exploration of biomarkers for more accurate disease classification based on the existing clinical indication classification.
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