A Quantitative Synthesis of Eight Decades of Global Multiple Sclerosis Research Using Bibliometrics

Abstract

Bibliometric studies on the field of multiple sclerosis (MS) research are scarce. The aim of this study is to offer an overarching view of the body of knowledge about MS research over eight decades-from 1945 to 2021-by means of a bibliometric analysis. We performed a quantitative analysis of a massive dataset based on Web of Science. The analysis included frequencies, temporal trends, collaboration networks, clusters of research themes, and an in-depth qualitative analysis. A total of 48,356 articles, with 1,766,086 citations were retrieved. Global MS research showed a steady increase with an annual growth rate of 6.4%, with more than half of the scientific production published in the last decade. Published articles came from 98 different countries by 123,569 authors in 3,267 journals, with the United States ranking first in a number of publications (12,770) and citations (610,334). A co-occurrence network analysis formed four main themes of research, covering the pathophysiological mechanisms, neuropsychological symptoms, diagnostic modalities, and treatment of MS. A noticeable increase in research on cognition, depression, and fatigue was observed, highlighting the increased attention to the quality of life of patients with MS. This bibliometric analysis provided a comprehensive overview of the status of global MS research over the past eight decades. These results could provide a better understanding of this field and help identify new directions for future research.

Keywords: articles; bibliometrics; citations; country productivity; impact factor; multiple sclerosis; publication trends; scientific collaboration.

Figure 1

(A) A world map with the distribution of country productivity, (B) a cumulative evolution of the number of MS papers by the top 25 countries.

Figure 2

Network of international collaborations in MS-related articles (countries that frequently collaborate have a similar color; circle size indicates papers per country, and line thickness indicates the number of co-authored articles).

Figure 3

A co-occurrence network analysis map showing associations between keywords in the dataset, with the keyword “multiple sclerosis” removed. The size of the circle indicates the keyword count in the sample, line thickness indicates co-occurrence frequency, and colors indicate a cluster of keywords.

Figure 4

(A) The trend of the proportion of articles containing the top 20 most used keywords at each given year; (B) the trend of their frequency at each given year.