Rare disease publishing trends worldwide and in China: a citespace-based bibliometric study

Rare disease publishing trends worldwide and in China: a citespace-based bibliometric study | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Rare disease publishing trends worldwide and in China: a citespace-based bibliometric study Qi Kong, Chen-Xin Fan, Li-Ming Chen, Ying Zhang, Xin-Lei Yan, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4451685/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Objective Here, we analyzed the research status of rare diseases in China and globally over the past decade using bibliometric and scientific knowledge graph methods. We aimed to understand research trends, determine frontier topics, and explore the developments in and the differences between research conducted in China and the rest of the world. Methods We focused on rare disease literature indexed in the Web of Science and CNKI databases from January 2013 to December 2023. We selected studies based on inclusion and exclusion criteria. Bibliometric methods and the CiteSpace 6.1.R6 software were used to prepare knowledge graphs and perform comparative analyses of authors, institutions, content, and hot topics between Chinese and English databases. Results A total of 10,754 articles from the Web of Science database and 969 articles from the CNKI database met the inclusion criteria. In the past 10 years, the diagnosis and treatment of rare diseases have been a common research focus in both China and foreign countries. However, China has emphasized more on "orphan drugs," whereas foreign countries have focused more on "genes" and "management." The United States had the greatest number of publications. However, China ranks high in terms of publication volume and institutional ranking. Conclusion The research interest in rare diseases has gradually increased worldwide, with European and American countries maintaining a leading position. China has made significant contributions to rare disease research. However, its research focus is lagging compared to international trends, and a lack of collaboration with foreign countries exists. The diagnosis and treatment of rare diseases remain central themes in the field, whereas genetic research, artificial intelligence intervention, and sociological studies on rare disease populations are emerging as hot topics. Rare diseases Orphan diseases Visualization Knowledge graph CiteSpace Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 1 Introduction Rare diseases refer to a group of clinically heterogeneous disorders characterized by considerably low prevalence and a small population of affected individuals[ 1 ]. Different countries and regions have established different specific definitions for rare diseases. The U.S. Food and Drug Administration (FDA) defines rare diseases as "any disease or condition that affects < 200,000 persons in the United States[ 2 ]." The European Medicines Agency (EMA) defines rare diseases as "life-threatening or chronically debilitating conditions that affect no more than 5 in 10,000 people in the EU[ 2 ]." According to The Report on the Definition of Rare Diseases in China 2021, China defines rare diseases as "diseases with a neonatal incidence rate of less than 1 in 10,000, a prevalence rate of less than 1 in 10,000, and a total affected population of less than 140,000[ 3 ]." According to estimates, rare diseases affect over 300 million patients worldwide, with over 7,000 rare diseases accounting for 10% of all human diseases. Among these, 80% are of genetic origin[ 4 ]. However, currently, effective treatment methods are unavailable for more than 90% of rare diseases[ 5 ]. The direct medical costs, non-medical costs, and productivity losses associated with rare diseases impose a significant burden on society[ 6 ]. Therefore, the treatment and management of rare diseases have become important global public health issues[ 7 ]. According to statistics, the number of patients with rare diseases in China is estimated to be approximately 20 million, with an average of 200,000 new cases reported annually[ 3 ]. Rare diseases are receiving increasing attention in China. In 2018, China released The First Batch of Rare Disease Catalog in China, which mentioned 121 rare diseases[ 8 ]. This made China the first country to classify rare diseases using a specific list[ 9 ]. In 2023, China released The Second Batch of Rare Disease Catalog in China, which added 86[ 10 ]new rare diseases to the list. Meanwhile, globally, developed countries such as the United States, France, and Germany have implemented national rare disease programs and orphan drug regulations and provide substantial funding to support research innovation and the establishment of healthcare systems for rare diseases[ 11 ]. Academic research on rare diseases has experienced unprecedented and rapid development. Web of Science (WoS) and China National Knowledge Infrastructure (CNKI) are the most comprehensive databases for core journal indexing in China and worldwide. They can help identify scientific research trends from publications in different languages and country perspectives[ 12 ]. This study aims to provide a comprehensive overview of the research trends in rare diseases over the past decade using CiteSpace software. We summarize the development process in the field of rare diseases and provide directions for further advancements in this area. 2 Methods 2.1 Retrieval Strategy The data for this study were obtained from the WoS Core Collection and CNKI databases. For the WoS database, a topic-based search was conducted using the keywords "(rare disease) OR (rare cancer) OR (rare tumor)" . The keyword "rare disease" was set as a "must inclusion", and the time range spanned from January 1, 2013, to December 31, 2023. The selected document types were "Review Article" and "Article." For the CNKI database, the search strategy included the keywords "(罕见病) OR (罕见疾病) OR (罕见肿瘤)" for the topic search. The time range spanned from January 1, 2013, to December 31, 2023. The selected document type was "Journal Article." 2.2 Inclusion Criteria The inclusion criteria for the academic papers were as follows: the articles must have keywords such as "罕见病" (rare disease), "罕见疾病" (rare disorder), or "罕见肿瘤" (rare tumor), and the research topic must be related to rare diseases or rare tumors. The inclusion was limited to academic journal papers available in the Chinese language for CNKI. No language restrictions were used for papers retrieved from the WoS. 2.3 Exclusion Criteria The exclusion criteria for literature selection were as follows: (1) Duplicate publications. (2) Literature unrelated to the research topic of rare diseases or rare tumors. (3) Literature without relevant keywords and/or the complete text. (4) Conference papers, patents, newspapers, and project reports. 2.4 Literature Screening and Data Extraction Two researchers conducted a thorough review of the literature based on the predetermined inclusion and exclusion criteria. They screened the titles and abstracts to exclude irrelevant data. In case of discrepancies, a third person was consulted for consensus. The search results from CNKI were exported in "Refworks" format, whereas the results from WoS were exported using "Plain Text - Full Record and References" as the data source. 2.5 Analysis Method CiteSpace 6.1.R6 is a Java-based program that supports visual exploration and knowledge discovery in literature databases. The analysis was conducted using CiteSpace to aid the visualization of the research landscape[13]. The time slice was set to 1 year, and the top N was set to 50. Pruning was set to Pathfinder and Pruning sliced networks. The analysis included the K-means clustering analysis of keywords and the identification of emerging research frontiers. The results were presented in the form of timeline graphs and keyword burst graphs in the visual interface of CiteSpace. 3 Results 3.1 Literature Search Results A total of 11,347 papers were retrieved from WoS. After data inspection, deduplication, and cleaning, 10,754 papers were included in the study. These papers were exported in the form of "Plain Text - Full Record and References". An initial screening of CNKI yielded 2,152 papers. After further evaluation, 969 papers were selected and included in the study (Figure 1). In the CNKI database (Figure 2A), the overall number of publications was relatively low and showed slow growth. There was a decline in 2018, followed by a recovery to normal levels. A rapid increase was observed from 2022. In 2023, the number of publications was 5.97 times greater than that in 2013. In the WoS database, the number of publications in the rare disease field showed a steady growth trend (Figure 2B). The growth rate increased significantly from 2018, although there was a marginal decline in 2023. Based on a comparison of the domestic and international publication counts (Figure 2C), the field of research on rare diseases is continuously expanding both domestically and internationally. Compared to domestic journals, international journals show a higher level of attention and depth of research in this field. Using a nonlinear index to fit the growth trend, the curve fitting equation for CNKI was set at Y = -134.6*exp(0.0567*X), R 2 = 0.8894; WoS is Y = -72.97*exp(0.0376*X), R 2 = 0.8644. 3.2 Database Literature Spatial Distribution (Core Countries/Institutions) 3.2.1 Countries and Regions The country with the greatest number of publications in the WoS database was the United States, with 2423 papers. China ranked second with 1969 papers, followed by Italy and Germany, both with over 1000 papers. However, there was a significant gap between the top two countries and the rest (Table 1 ). This indicates the core position of the United States in the field of rare disease research. China also demonstrated strong research capabilities. Among the top 10 countries, six were European countries. From the Network of Collaborating Countries (Figure 3), extensive and frequent collaboration was observed among European and American countries. However, currently, China has limited research collaborations with other countries. In terms of literature centrality, the Netherlands had the greatest intermediary centrality (0.09), indicating close collaborative connections with other countries. The Netherlands has not only published a large volume of research output but also achieved high-quality results in the field of rare disease research, thus playing a crucial role. 3.2.2 Research Institutions Among publishing institutions (Table 2 ), Chinese research institutions have abundant research output in both domestic and international databases. The Beijing Union Medical College Hospital, Chinese Academy of Medical Sciences, as a top medical and research center in China, is the only institution that ranks among the top 10 institutions in both domestic and international databases. It houses the National Key Laboratory for Rare and Difficult Diseases and focuses on diseases such as Gitelman syndrome, transthyretin amyloidosis cardiomyopathy, and hereditary retinal degeneration. Zhejiang University has the greatest number of publications in the WoS database and primarily focuses on rare diseases such as spinal muscular atrophy and Wilson's disease. Combining the results of the analysis of countries in the previous section, it is evident that European and American countries hold critical positions in the field of rare disease research. Meanwhile, the research capabilities of China are noteworthy. 3.3 Keywords 3.3.1 Co-occurrence of Keywords Keywords are a reflection of the core content of the literature. In this study, we selected co-occurrence network graphs of keywords with a frequency greater than 100 in the WoS database (Figure 4B). The top three keywords were "rare disease" (1662), "diagnoses" (980), and "mutation" (833) (Table 3 ). "Management" (794) also had a high frequency. In the CNKI database (Figure 4A, Table 3), "rare disease" was also the most frequently appearing keyword (452), followed by "orphan drugs" (100) and "diagnosis" (38). A comparison of the two showed that "rare disease," "diagnosis," "therapy," and "Children" are among the top 10 keywords with the greatest frequency in both databases. This indicates that diagnosis, therapy, and children’s rare diseases are common themes of concern in this field at both domestic and global levels, and they represent the research focus. However, among the high-frequency keywords in the domestic database, certain terms were related to orphan drugs and rare drugs, which were also treatment-related. In contrast, the international database focused more on gene-related directions such as "mutation" and "expression," as well as rare disease management. This reveals the different research perspectives between domestic and international studies in this field. Chinese research institutions may place a greater emphasis on drug development and application, whereas international research tends to explore the mechanisms underlying rare diseases and the social management of special populations. 3.3.2 Keyword Clustering Keyword clustering can reflect the different research focuses in a particular field. The smaller the clustering number, the more the keywords included in that cluster. In the WoS database (Table 4), orphan drugs and whole-exome sequencing were the most prominent research directions. Case reports were the primary form of research output, indicating that with the improvement of medical standards and advancement of diagnostic methods, a greater number of rare disease cases are being reported. In the CNKI database (Table 4 ), orphan drugs remain a research focus. The comparison between the two databases reconfirmed the difference in research focuses between domestic and international studies in the field of rare diseases. These research directions also indicate that international research on rare diseases has focused on findings at the molecular level, whereas Chinese journals continue to focus on treatment and medication, with less emphasis on the investigation of disease mechanisms. The development of the field of rare diseases in China is less advanced than the international community. 3.3.3 Keyword Timeline Graph The timeline graph reflects the development of keywords within each cluster. In the WoS database (Figure 5B), the top ten keywords in terms of frequency have been appearing since 2013 and have maintained a high occurrence rate over the past 10 years. This indicates that the diagnosis, therapy, management, and genetic research of rare diseases constitute the foundation of this field. On this basis, medical genetics (2019), genomics (2018), and public health (2020) have advanced considerably, aiding rare disease research at a deeper investigative level. In the CNKI database (Figure 5A), high-frequency keywords such as "rare disease," "orphan drugs," and "rare drugs" related to medications have appeared since 2013 and have laid the foundation for subsequent research directions. Keywords such as "diagnosis," "therapy," and "clinical trials" only appeared first in 2015-2016, exhibiting a lag compared to international trends. Keywords related to rare disease management and social support in the field of social sciences also appeared relatively late, indicating that China still lacks sufficient social attention and policy support for rare disease populations. Based on observations of the keyword burst graph (Figure 6), the Ice Bucket Challenge once created a wave of enthusiasm in China but disappeared within a year. This indicates that while marketing-style dissemination can increase social awareness of rare diseases, it does not significantly impact social security in rare disease populations. Currently, the research focus is concentrated on medical security, and governmental influence may significantly improve the lives of rare disease populations in China. 3.4 Authors In the WoS database, Taruscio, Domenica, Boycott, Kym M, and Baynam, Gareth were the top three authors in terms of publication volume (Table 5 ). The three authors constituted the center in the collaboration network, and their collaboration has gained prominence in the past 5 years (Figure 7B). Before this period, the author collaboration network was not significant, with the majority of authors producing independent work. This indicates that contemporary research places greater emphasis on multi-team collaboration and multi-center studies. Taruscio, Domenica, Boycott, Kym M, and others have contributed to rare disease research for long, consistently producing research output, and they are important scholars in this field. The author collaboration network reflected in the CNKI database is relatively close but shows clear stages (Figure 7A). In 2013-2014, Pei-Wen Wang and Jin-Ping Xie were the central authors in the network. The collaboration network centered around Shu-Yang Zhang, Bo Zhang, and Meng-Chun Gong lasted for a longer duration. The publication volume clearly indicated that this team has made outstanding contributions to the field of rare diseases (Table 5). However, their output decreased significantly in the past 3 years, and the formation of novel collaboration networks is not yet apparent. 3.5 Co-cited References Highly cited references can indicate the hot topics in a research field. By analyzing these co-cited references, the dynamic changes in research topics within a specific time range can be identified. The top three co-cited references were "Estimating cumulative point prevalence of rare diseases: analysis of the Orphanet database [14]", "Standards and guidelines for the interpretation of sequence variants: a joint consensus recommendation of the American College of Medical Genetics and Genomics and the Association for Molecular Pathology[15]", and "The mutational constraint spectrum quantified from variation in 141,456 humans[16]" (Table 6). The first-ranked reference was cited as many as 156 times. We used the Orphanet database to estimate the cumulative point prevalence of rare diseases. Of the 6,172 unique rare diseases, 71.9% were genetic, and 69.9% manifest in childhood. The second- and third-ranked references were both related to genomics. Table 7 presents further analysis of the hot topics and progress in the field of rare diseases over the past 10 years. This study selected the top 15 references with the strongest citation bursts. Among them, six articles were related to genomics[15-20], and three articles reported database-related content, including those related to the Orphanet [14] and HPO databases[21, 22]. Two articles introduced disease-related platforms, namely The Matchmaker Exchange[23], a platform for rare disease gene discovery, and PhenoTips[24], a software for patient phenotype analysis for clinical and research purposes. The remaining articles cover topics such as writing standards for reviews[25], disease terms definition [2], social science research[21], and reviews[26] on rare diseases. Evidently, genomic research is a hot topic in the field of rare diseases. Contribution to disease diagnosis and treatment using big data and artificial intelligence is also a growing trend. With social progression, minority groups are gradually receiving more attention, leading to an increase in social science research on rare disease populations. Centrality can indicate the importance and influence of literature in a specific field. In this study, the top four cited references with the greatest centrality were selected (Table 8). Among them, one article had a centrality ≥ 0.1. This article introduced the use of exome sequencing to identify disease-causing genes[27], reaffirming that genetics is a research hotspot and development trend in this field. 4 Discussion 4.1 Comparison of Domestic and Foreign Databases An analysis of the progressive knowledge graph in the field of rare diseases over the past 10 years shows that the field of rare disease research is entering a phase of rapid development. However, there are certain differences in the research data between domestic and foreign databases. In terms of the number of publications, the number of publications included in WoS over the past 10 years is ten times greater than that in CNKI. This could be explained by the fact that the publications were from global journals, whereas most journals in CNKI were from China. In terms of the growth rate, WoS has been growing rapidly since 2018, whereas CNKI showed a significant growth acceleration in 2022. This may be attributed to high-quality research from China being likely to be published internationally. From the perspective of focus, the frequency ranking of keywords and clustering in CNKI indicate that domestic journals in China focus more on rare disease drugs, whereas foreign journals focus on genetics and therapies. China’s policies may help explain this difference. European countries started using Managed Entry Agreements (MEAs) to manage rare disease drugs as early as 2013 or before that. National authorities have the flexibility to adjust funding support, and pharmaceutical companies can ensure the normal market access of drugs considering cost-benefit conditions[28]. In recent years, policies have further improved, and some countries have developed specific programs to evaluate the approval of rare disease drugs. For example, in Italy, the approval process for orphan drugs is stated to be completed within 100 days[29]. In comparison, China's corresponding policies are less advanced. Following the announcement of the first batch of rare disease catalogs in 2018, in April 2019, The Drug Administration Law of the People's Republic of China was enacted to encourage the development of innovative rare disease drugs and prioritize the evaluation of approval[30]. However, it did not specify a timeframe. Policy orientation is closely related to academic development. Developed countries such as Europe and the United States have established comprehensive and mature systems for implementing the research, approval, and market access of rare disease drugs. These countries are also the primary forces in the research and production of rare disease drugs. Therefore, they conduct more genetic research, uncovering disease mechanisms and exploring new signaling pathways and mechanisms of action for the development of new drugs and therapies. Conversely, in China, most rare disease drugs are imported, and issues related to drug accessibility and market access still require improvement, despite the introduction of multiple policies in recent years to encourage independent drug research and development. However, the process is lengthy, and significant achievements may only be reported years later. 4.2 Research Hotspots in the Field of Rare Diseases 4.2.1 Rise of Social Science Research Patients with rare diseases often bear a dual burden of physical and psychological challenges. In the era of the biological-psychological-social medicine model[31], the diagnosis and treatment of diseases are no longer limited to technical aspects; it is also important to focus on the psychological well-being and social identity of patients. This has led to the development of medical humanities research in the field of rare diseases. Among the top 15 highly cited references, Zurynski Y's cross-sectional study highlighted the reasons and consequences of delayed diagnosis in children with rare diseases. It emphasizes the need for healthcare professionals to provide psychological support to patients and for parents to prioritize genetic counseling and opt for rare disease-related education[32]. Disease burden is also a prominent theme of research. In the 2019 US Rare Disease Economic Burden Assessment, excess expenditures were primarily attributed to hospital inpatient care, prescription drugs, and productivity losses in the labor market owing to absenteeism and early retirement[33]. In addition, the keyword "quality of life" appears over 200 times in the WoS database. A survey on the survival conditions of rare disease populations showed a positive correlation between informal social support and the quality of life. Patients who received social assistance had better quality of life in the psychological and social domains than those who did not[34]. "Management" and "healthcare coverage" are also frequent keywords. Countries worldwide are continuously updating their policies related to rare diseases[35, 36]. Processes to integrate rare disease populations into mainstream society are a global issue. In May 2021, the United Nations passed its first resolution on "Addressing the Challenges of Rare Disease Patients and Their Families," which covers various aspects, such as education, employment, poverty, gender inequality, and support for the inclusion of patients with rare diseases in multiple societal dimensions[37]. As social citizens, rare disease populations have the right to enjoy social welfare policies, equal access to education, and employment opportunities. This can help improve their community awareness and self-acceptance. At the societal level, it can alleviate socioeconomic and management burdens, indicating the progress of human civilization. 4.2.2 Application of Artificial Intelligence and Big Data Owing to the small size of the rare disease population, misdiagnosis and mistreatment are common. The use of big data aids the sharing and linkage of patient information worldwide. Using the powerful computational capabilities of artificial intelligence, the relationship between genes and disease onset can be determined, and potential drug targets can be explored. Therefore, establishing a rare disease information database is of great significance for diagnosis, treatment, and research. Orphanet is a widely used database with information on rare disease medical classifications, gene information, and epidemiological indicators, among other data. The most highly cited reference in this context uses the accumulated data collected by Orphanet to estimate disease prevalence[14]. The Matchmaker Exchange (MME), which mentioned in a high-burst cited reference, is a federated network connecting databases of genotypes and rare phenotypes using a common application programming interface[23]. By 2022, which was 7 years since it was founded, the network had data from over 120,000 cases provided by more than 12,000 volunteers from 98 countries, with over 13,520 unique gene-to-gene matches established. New gene-disease connections are discovered every day[38]. Over the past decade, artificial intelligence has been used in the diagnosis and treatment of various diseases. For example, machine learning algorithms have been used to predict the clinical severity of progressive supranuclear palsy (PSP) by analyzing diffusion tensor imaging characteristics of the brain[39]. Automatic assessment tools have been developed to predict speech disorders in patients with amyotrophic lateral sclerosis (ALS) based on speech acoustics and pronunciation samples[40]. Big data and machine learning demonstrate the immense potential of artificial intelligence in the field of rare diseases. However, the widespread implementation of these tools in clinical applications requires regulatory frameworks, evidence from clinical trials, and compliance with ethical guidelines[41]. Disease registration is also focused on both domestically and internationally. Owing to the challenges in collecting rare disease data, individualized tracking of each patient is typically performed using case registries. Collecting epidemiological data through registries helps monitor the quality of management and patient prognosis processes while providing convenience for clinical research. Developed countries such as Europe and the United States have achieved a high level of refinement, regionalization, and networking in their registries. Examples include the European Rare Kidney Disease Registry (ERKReg)[42] and the European registry for patients with McArdle disease and other muscle glycogenoses (EUROMAC registry)[43] . In contrast, in China, rare disease registries have been developed relatively late. The National Rare Disease Registry System (NRDRS), established in 2016, is expected to have a positive impact on epidemiological research within the country[44]. 4.2.3 Genetic Research Genomic research is one of the most important hotspots in the field of rare diseases. In keyword analysis, keyword clustering in CNKI includes the label of "gene therapy," whereas the high-frequency keywords in WoS include "mutation," "expression," and "gene," all of which appear more than 300 times. Among the highly cited references in WoS, approximately half of the articles are related to genomics. The highest-ranked highly cited reference is a standard and guideline on the interpretation of sequence variations. It uses various types of variant evidence, including population data, computational data, functional data, and segregation data, to classify variations into five standards: "pathogenic," "likely pathogenic," "uncertain significance," "likely benign," and "benign"[15]. This article serves as a foundational declaration in the field of genomics. However, owing to the significant proportion of genetic diseases among rare diseases, the development of this guideline also contributes to the standardized representation of gene mutations in rare disease genomics research, which is of significance in determining gene-disease relationships. Genomics is not only used to explore the etiology of rare diseases but also plays a role in the development of therapeutic drugs and treatments as research progresses. Luxturna, a gene therapy drug using adeno-associated virus (AAV) vectors, is administered through subretinal injection to treat inherited retinal dystrophy caused by RPE65 protein deficiency. Patisiran is an oligonucleotide-based therapy for familial transthyretin amyloidosis (FTA) that inhibits the misfolding of transthyretin protein, thereby impeding disease progression. Rare disease drugs based on gene therapies such as CAR-T and retroviral vectors have also been approved and launched in foreign markets[45]. As more mechanisms are discovered, the scope of gene therapy will continue to expand, bringing new hope for the treatment of rare diseases. However, the adoption of gene therapy in China remains limited, and further research and development are needed before it can be widely used in clinical practice. 4.3 Key Scholars and Institutions in the Field of Rare Diseases In the CNKI database, the core author Shu-Yang Zhang stands out with a significantly high publication volume. As the President of Peking Union Medical College Hospital (PUMCH) and Vice President of Peking Union Medical College, the collaborative network centered around Shu-Yang Zhang has consistently produced output over the past decade. The research institutions associated with Shu-Yang Zhang, namely PUMCH and Peking Union Medical College, have also achieved remarkable results in the field of rare disease research in China. Shu-Yang Zhang is a leading scholar in the field of rare diseases in China, with most of his published articles focusing on rare cardiovascular diseases or rare disease policies in China. Examples include "Progress in the Diagnosis and Treatment of Rare Cardiovascular Diseases [46]" and "Construction and Application of China's National Rare Disease Registration System[47] ". The articles published by Shu-Yang Zhang are mostly systematic reviews and expert consensus articles. PUMCH, as the host institution of the National Key Laboratory for Severe and Rare Diseases, encompasses various disciplines such as oncology, surgery, obstetrics, and gynecology. Its achievements span multiple types of publications, including case reports, systematic reviews, and clinical studies. In the WoS database, Taruscio D and Boycott KMare authors with the greatest number of publications. The collaborative network centered around these authors is the only evident collaboration network in the WoS database. Taruscio D is affiliated with the Istituto Superiore di Sanita in Rome, Italy, whereas Boycott KM is affiliated with the Children's Hospital of Eastern Ontario in Canada. Both researchers have interests in genetics and experimental medicine. However, Taruscio D also focuses on public health management and healthcare services related to rare diseases, whereas Boycott KM has a stronger emphasis on genomics. In the analysis of co-cited literature, Boycott KM has two highly cited and highly prominent articles: "International Cooperation to Enable the Diagnosis of All Rare Genetic Diseases[48]" and "Rare-disease genetics in the era of next-generation sequencing: discovery to translation[18]" . However, Taruscio D does not have any highly cited articles. This indicates that Boycott KM is a key scholar in the field of international rare disease research and an important member of the International Rare Diseases Research Consortium (IRDiRC). From an institutional perspective, Chinese research institutions have demonstrated significant achievements in scientific research globally. However, collaboration with international institutions is yet to be established. Domestic and international institutions and scholars should strengthen communication and cooperation, learn from each other’s experiences, and collectively promote the development of the field of rare diseases. 5 Conclusion This study used CiteSpace to analyze outstanding academic achievements in the field of rare diseases over the past decade. By visualizing and mapping key institutions, authors, keywords, and high-citation information, it identified research hotspots and development trends from different perspectives, providing insights for the global advancement of the field of rare diseases. However, there are certain limitations to this study. First, the literature selection process was manual, which may have introduced subjectivity in the inclusion of literature, organization of literature information, and merging of keywords, potentially leading to the loss of some relevant articles. Secondly, CiteSpace uses its in-built algorithms for keyword merging and clustering, which may not fully represent all research content within a particular cluster. Additionally, research on specific rare diseases often does not directly include the term "rare diseases," which implies that we may have excluded some studies focusing on individual rare diseases. Furthermore, owing to limitations in the CiteSpace software and CNKI database, the direct export of citation data was not possible, resulting in a lack of co-citation analysis for Chinese literature in this study. Abbreviations FDA The U.S. Food and Drug Administration EMA The European Medicines Agency WoS Web of Science CNKI China National Knowledge Infrastructure MEAs Managed Entry Agreements MME The Matchmaker Exchange PSP Progressive Supranuclear Palsy ALS Amyotrophic Lateral Sclerosis ERKReg European Rare Kidney Disease Registry EUROMAC registry European registry for patients with McArdle disease and other muscle glycogenoses NRDRS The National Rare Disease Registry System AAV Adeno-associated virus FTA Familial transthyretin amyloidosis PUMCH Peking Union Medical College Hospital IRDiRC International Rare Diseases Research Consortium Declarations Ethics approval and consent to participate Not applicable. Consent for publication All the authors had complete access to the manuscript and agreed to submit it for publication. Data Availability The data presented in this research are available on request from the corresponding author. Conflict of Interest The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. Funding This work was supported by Shanghai Municipal Philosophy and Social Sciences Planning Project: Research on the Multidimensional Construction of a Multi-level Healthcare System for Rare Diseases in Shanghai under the New Situation. [grant number: 2022BGL002]; 2022 Annual Talent Development Program of the Shanghai Municipal Health Commission: Research on Enhancing the Prevention, Treatment, and Assurance Capacity of Rare Diseases in Shanghai under the New Development Situation [grant number: 2022YQ058]. Author Contributions Qi Kong and Li-Ming Chen came up with the idea. Chen-Xin Fan, Ying Zhang conducted a thorough review of the literature, and Xin-Lei Yan was consulted for consensus in case of discrepancies. Chen-Xin Fan performed statistical analysis and made the figures by Citespace. Qi kong and Chen-Xin Fan composed the manuscript. Qi Kang and Pei-Hao Yin reviewed and optimized the manuscript. All the authors have approved the final draft submitted. Qi Kong, and Chen-Xin Fan contribute equally to this review. Acknowledgements We appreciate KeTeng Edit （http://ketengedit.com/）provided language editing services for this article. Authors’ information Qi Kong Institution: Putuo Hospital, Shanghai University of Traditional Chinese Medicine, Shanghai, China; Interventional Cancer Institute of Chinese Integrative Medicine, Shanghai University of Traditional Chinese Medicine, Shanghai, China Address: No.164 Lanxi Road, Putuo District, Shanghai, 200062, China; No.164 Lanxi Road, Putuo District, Shanghai, 200062, China Email: [email protected] Chen-Xin Fan Institution: Shanghai University of Traditional Chinese Medicine, Shanghai, China Address: 1200 Cai Lun Road,Zhangjiang Hi-TechPark,Pudong New Area, Shanghai, 201203, China Email: [email protected] Li-Ming Chen Institution: Yueyang Hospital of Integrated Traditional Chinese and Western Medicine, Shanghai University of Traditional Chinese Medicine, Shanghai, China Address: No.650 South Wanping Road, Xuhui District, Shanghai, 200030, China Email: [email protected] Ying Zhang Institution: Shanghai University of Traditional Chinese Medicine, Shanghai, China Address: 1200 Cai Lun Road,Zhangjiang Hi-TechPark,Pudong New Area, Shanghai, 201203, China Email: [email protected] Xin-Lei Yan Institution: Shanghai University of Traditional Chinese Medicine, Shanghai, China Address: 1200 Cai Lun Road,Zhangjiang Hi-TechPark,Pudong New Area, Shanghai, 201203, China Email: [email protected] Qi Kang Institution: Shanghai Health Development Research Center (Shanghai Medical Information Research Center) Address: No.1477 West Beijing Road, Shanghai 200040, China Email: [email protected] Pei-Hao Yin Institution: Putuo Hospital, Shanghai University of Traditional Chinese Medicine, Shanghai, China; Interventional Cancer Institute of Chinese Integrative Medicine, Shanghai University of Traditional Chinese Medicine, Shanghai, China Address: No.164 Lanxi Road, Putuo District, Shanghai, 200062, China; No.164 Lanxi Road, Putuo District, Shanghai, 200062, China Email: [email protected] References Schieppati A, Henter JI, Daina E, Aperia A. 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Rank Article counts Centrality Countries 1 2423 0 USA 2 1969 0 PEOPLES R CHINA 3 1123 0 ITALY 4 1020 0 GERMANY 5 881 0.01 FRANCE 6 821 0.07 ENGLAND 7 649 0 JAPAN 8 598 0.07 SPAIN 9 465 0.05 CANADA 10 379 0.09 NETHERLANDS Table 2 The top 10 productive institutions ranked by the numbers of publications. Rank Article counts Institutions(CNKI) Article counts Institutions(WoS) 1 74 中国医学科学院北京协和医院(Peking Union Medical College Hospital) 151 Zhejiang Univ 2 61 中国药科大学(China Medical University) 132 Capital Med Univ 3 31 北京大学(Peking University) 127 Harvard Med Sch 4 31 中国医学科学院北京协和医学院(Peking Union Medical College) 126 Univ Milan 5 21 山东大学(Shandong University) 123 Mayo Clin 6 20 国家药品监督管理局(National Medical Products Administration) 118 Univ Toronto 7 18 沈阳药科大学(Shenyang Pharmaceutical University) 105 Univ Penn 8 15 上海市卫生和健康发展研究中心(Shanghai Health and Health Development Research Center) 98 Chinese Acad Med Sci 9 14 四川大学华西医院(West China Hospital，Sichuan University) 94 Sichuan Univ 10 12 上海交通大学(Shanghai Jiao Tong University) 90 INSERM Table 3 The top 10 keywords ranked by the frequency. Rank Article counts Centrality Keywords of CNKI Article counts Centrality Keywords of WoS 1 452 1.19 罕见病(rare disease) 1662 0.01 rare disease 2 100 0.11 孤儿药(orphan drugs) 980 0 diagnosis 3 38 0.05 诊断(diagnosis) 833 0.01 mutation 4 35 0.02 治疗(therapy) 794 0.01 management 5 31 0.01 医疗保障(medical security) 619 0.01 disease 6 29 0.11 罕用药(rare drugs) 602 0.01 children 7 23 0.01 儿童(children) 403 0.01 therapy 8 20 0.05 罕见疾病(rare disorder) 390 0 case report 9 19 0.01 临床试验(clinical trial) 380 0.01 expression 10 15 0.02 可及性(accessibility) 377 0.01 cancer Table 4 The information of clusters about keyword co-citation analysis. Database Clusters Label Terms WoS Database 0 rare disease rare disease; target therapy; desmoplastic small round cell tumor; tyrosine kinase receptor; fetal growth restriction | squamous cell carcinoma; targeted therapy; penile cancer; systemic therapy; retroperitoneal sarcoma 1 orphan drug rare disease; orphan drug; spinal muscular atrophy; real-life outcome data; single-arm trial | rare diseases; comparative effectiveness; evidence generation; patient-oriented outcomes; evidence synthesis 2 case report case report; langerhans cell histiocytosis; igg4-related disease; central diabetes insipidus; bone marrow | magnetic resonance imaging; myeloid sarcoma; sacral spine; primary testicular lymphoma; testicular cancer 3 whole-exome sequencing rare disease; whole-exome sequencing; genic intolerance; health ethics; government regulation | mutation; variant; protein; tool; common disease 4 aortic dilatation rare disease; aortic dilatation; bicuspid aortic valve; aortic dissection; aortic coarctation | pulmonary hypertension; lung cancer; von recklinghausen; neurofibromatosis type; viral coinfection 5 oxidative stress rare disease; oxidative stress; lipid metabolism; mitochondrial dysfunction; brain iron accumulation | gene expression; growth; model; mutation; mice CNKI database 0 罕见病(rare disease) 罕见病(rare disease); 孤儿药(orphan drugs); 罕用药(rare drugs); 罕见疾病(rare disorder); 诊断(diagnosis) 1 孤儿药(orphan drugs) 孤儿药(orphan drugs); 药物政策(medicine policy); 对比分析(comparative analysis); 分析(analysis); 价格谈判(price negotiation) 2 罕用药(rare drugs) 罕用药(rare drugs); 美国(America); 制药企业(pharmaceutical companies); 研发(research and development); 适应证扩展(indication expansion) 3 病理学(Pathology) 病理学(Pathology); 基因治疗(gene therapy); 临床研究(clinical studies); 诊断(diagnosis); 罕见病(rare disease) 4 儿童(children) 儿童(children); 治疗(therapy); 人工智能(artificial intelligence); 临床表现(clinical manifestations); 分类(classification) 5 医学教育(medical education) 医学教育(medical education); 罕见疾病(rare disorder); 临床思维(clinical thinking); 计算机技术(computer technology); 教学质量(teaching quality) 6 医疗保障(medical security) 医疗保障(medical security); 血友病(Hemophilia); 可负担性(affordability); 伦理原则(ethical principles); 医保政策(medical insurance policy) 7 可及性(accessibility) 可及性(accessibility); 影响因素(influencing factors); 可获得性(availability); 策略研究(strategy research); 评价指标(evaluation index) 8 临床试验(clinical trial) 临床试验(clinical trial); 招募(recruitment); 药物研发(drug development); 肺部罕见肿瘤(rare lung tumors); 优先审评(priority review) 9 中国(China) 中国(China); 保障(guarantee); 国家罕见病注册系统( national rare disease registration system); 合作(cooperation); 戈谢病(Gauchers disease) Table 5 The top 5 productive authors ranked by the numbers of publications. Rank Article counts Author Rank Article counts Author 1 26 Taruscio, Domenica 1 27 张抒扬(Shu-Yang Zhang) 2 25 Boycott, Kym M 2 15 张波(Bo Zhang) 3 17 Baynam, Gareth 3 11 康琦(Qi Kang) 4 11 Robinson, Peter N 4 11 弓孟春(Meng-Chun Gong) 5 11 Lochmueller, Hanns 5 10 刘鑫(Xin Liu) 6 - - 6 10 金春林(Chun-Lin Jin) Table 6 The top 10 cited references with the highest cited frequency. Freq Burst Centrality Author Source DOI 170 28.18 0.02 Wakap SN EUR J HUM GENET 10.1038/s41431-019-0508-0 110 34.05 0.01 Richards S GENET MED 10.1038/gim.2015.30 86 13.74 0.01 Karczewski KJ NATURE 10.1038/s41586-020-2308-7 83 20.45 0.01 Lek M NATURE 10.1038/nature19057 60 3.62 0.02 Wright CF NAT REV GENET 10.1038/nrg.2017.116 58 9.74 0.03 Ferreira CR AM J MED GENET A 10.1002/ajmg.a.61124 57 0 0.02 Haendel M NAT REV DRUG DISCOV 10.1038/d41573-019-00180-y 49 3 0.03 Boycott KM AM J HUM GENET 10.1016/j.ajhg.2017.04.003 45 5.89 0.01 Landrum MJ NUCLEIC ACIDS RES 10.1093/nar/gkx1153 43 17.32 0.02 Boycott KM NAT REV GENET 10.1038/nrg3555 43 0 0.01 Rentzsch P NUCLEIC ACIDS RES 10.1093/nar/gky1016 Table 7 The top 15 cited references with the strongest citation bursts. Freq Burst Centrality Author Source 110 34.05 0.01 Richards S GENET MED 170 28.18 0.02 Wakap SN EUR J HUM GENET 83 20.45 0.01 Lek M NATURE 43 17.32 0.02 Boycott KM NAT REV GENET 86 13.74 0.01 Karczewski KJ NATURE 31 11.89 0.04 Kircher M NAT GENET 26 10.43 0.01 Köhler S NUCLEIC ACIDS RES 35 10.06 0.04 Richter T VALUE HEALTH 23 9.91 0 Page MJ PLOS MED 58 9.74 0.03 Ferreira CR AM J MED GENET A 34 9.07 0.05 Köhler S NUCLEIC ACIDS RES 34 9.06 0.02 Philippakis AA HUM MUTAT 32 9.04 0.01 Zurynski Y ORPHANET J RARE DIS 21 8.42 0.07 Girdea M HUM MUTAT 21 8.42 0.02 Yang YP NEW ENGL J MED Table 8 The top 4 cited references with the highest Centrality. Freq Burst Centrality Author Source DOI 22 3.9 0.11 Benson MD NEW ENGL J MED 10.1056/NEJMoa1716793 13 6.73 0.09 Bamshad MJ NAT REV GENET 10.1038/nrg3031 8 0 0.09 Gurovich Y NAT MED 10.1038/s41591-018-0279-0 21 8.42 0.07 Girdea M HUM MUTAT 10.1002/humu.22347 Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4451685","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":313893097,"identity":"619d67bc-5678-43bb-b5a4-e3d923520505","order_by":0,"name":"Qi Kong","email":"","orcid":"","institution":"Putuo Hosipital, Shanghai University of Traditional Chinese Medicine;Interventional Cancer Institute of Chinese Integrative Medicine, Shanghai University of Traditional Chinese Medicine","correspondingAuthor":false,"prefix":"","firstName":"Qi","middleName":"","lastName":"Kong","suffix":""},{"id":313893098,"identity":"1b128100-5c40-4e7c-bd04-3e2113c8d656","order_by":1,"name":"Chen-Xin Fan","email":"","orcid":"","institution":"Shanghai University of Traditional Chinese Medicine","correspondingAuthor":false,"prefix":"","firstName":"Chen-Xin","middleName":"","lastName":"Fan","suffix":""},{"id":313893099,"identity":"8ccc90d6-821d-47a4-a76b-8bf9d6e0f645","order_by":2,"name":"Li-Ming Chen","email":"","orcid":"","institution":"Yueyang Hospital of Integrated Traditional Chinese and Western Medicine, Shanghai University of Traditional Chinese Medicine","correspondingAuthor":false,"prefix":"","firstName":"Li-Ming","middleName":"","lastName":"Chen","suffix":""},{"id":313893100,"identity":"dd81e18f-0f6c-4ed7-8705-a170454b47fd","order_by":3,"name":"Ying Zhang","email":"","orcid":"","institution":"Shanghai University of Traditional Chinese Medicine","correspondingAuthor":false,"prefix":"","firstName":"Ying","middleName":"","lastName":"Zhang","suffix":""},{"id":313893101,"identity":"9429d24e-eba5-4cef-97d7-928a6f21af18","order_by":4,"name":"Xin-Lei Yan","email":"","orcid":"","institution":"Shanghai University of Traditional Chinese Medicine","correspondingAuthor":false,"prefix":"","firstName":"Xin-Lei","middleName":"","lastName":"Yan","suffix":""},{"id":313893102,"identity":"0f3dc571-3a65-4e39-9bd6-a78d83c30240","order_by":5,"name":"Qi Kang","email":"","orcid":"https://orcid.org/0000-0003-3779-1881","institution":"Shanghai Health Development Research Center","correspondingAuthor":false,"prefix":"","firstName":"Qi","middleName":"","lastName":"Kang","suffix":""},{"id":313893103,"identity":"768b98af-b7df-4d6c-ba3f-9a66c7440337","order_by":6,"name":"Pei-Hao Yin","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA8klEQVRIiWNgGAWjYDACZhBhcICBgb2BDSZmQKQWngNALQnEaIEAoBaJBCK1GBznPfbgQ8EdeX7J588e8/6wi2Zgb94mwVBzB7eWw3zphjMMnhnOnJ1jbsyTkJzbwHOsTILh2DM8WnjMpHkMDjNuuJ3DJs2TcCC3QSLHTIKx4TB+LX8MDttvuHn8GUSL/BsitADJxA03GMygtvDg1yJ5mMfcsMfgcPLMnhwzyTlpybltPGnFFgnHcGvhO3/G7MGPP4dt+9mPP5N4Y2OX289+eOONDzW4tSgcYGBDFQFzE3BqYGCQb0DXMgpGwSgYBaMAHQAAu3RUBBi6gaIAAAAASUVORK5CYII=","orcid":"https://orcid.org/0009-0001-1496-1107","institution":"Putuo Hospital, Shanghai University of Traditional Chinese Medicine; Interventional Cancer Institute of Chinese Integrative Medicine, Shanghai University of Traditional Chinese Medicine","correspondingAuthor":true,"prefix":"","firstName":"Pei-Hao","middleName":"","lastName":"Yin","suffix":""}],"badges":[],"createdAt":"2024-05-21 02:35:22","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4451685/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4451685/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":59295861,"identity":"cdf688a9-0650-46ae-b643-db6a399cdcef","added_by":"auto","created_at":"2024-06-28 20:15:56","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":77866,"visible":true,"origin":"","legend":"\u003cp\u003eFlowchart of literature search and data incorporation.\u003c/p\u003e","description":"","filename":"OnlineFIGURE1.png","url":"https://assets-eu.researchsquare.com/files/rs-4451685/v1/f3da43c91d367eae0d02bb8b.png"},{"id":59295473,"identity":"574e52a9-e036-46d0-8b66-d2d145a2fbf3","added_by":"auto","created_at":"2024-06-28 20:07:56","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":78171,"visible":true,"origin":"","legend":"\u003cp\u003eChart of annual publishing and growth trends.\u003c/p\u003e\n\u003cp\u003e(A) Trends in the number of publications per year in the CNKI database. (B) Trends in the number of publications per year in the WoS core database. (C) Comparison of publication growth trends between the CNKI and WoS core database.\u003c/p\u003e","description":"","filename":"OnlineFIGURE2.png","url":"https://assets-eu.researchsquare.com/files/rs-4451685/v1/8c6b8a7fa870433f266d422f.png"},{"id":59296081,"identity":"9045501f-42a6-46af-9033-2f5635fe16fa","added_by":"auto","created_at":"2024-06-28 20:23:56","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":182064,"visible":true,"origin":"","legend":"\u003cp\u003eNetwork of Collaborating Countries.\u003c/p\u003e\n\u003cp\u003eThe circle indicates the country; the larger the size of the circle, the greater the number of publications of the country. Links between nodes describe cooperation between the countries.\u003c/p\u003e","description":"","filename":"OnlineFIGURE3.png","url":"https://assets-eu.researchsquare.com/files/rs-4451685/v1/88729d6b380e5699d0e54844.png"},{"id":59295476,"identity":"1e9a4907-5189-4073-820e-191397f485ba","added_by":"auto","created_at":"2024-06-28 20:07:56","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":373502,"visible":true,"origin":"","legend":"\u003cp\u003eNetwork of primary keywords in publications.\u003c/p\u003e\n\u003cp\u003e(A) Network of primary keywords in the CNKI database. (B) Network of primary keywords in the WoS core database. The circle indicates the keyword; the larger the size of the circle, the greater the frequency of the keyword.\u003c/p\u003e","description":"","filename":"OnlineFIGURE4.png","url":"https://assets-eu.researchsquare.com/files/rs-4451685/v1/fd2324cc9eb8b3b607c94bad.png"},{"id":59295862,"identity":"2e0e18f1-5f5a-4a6e-9bc8-417467c12ec0","added_by":"auto","created_at":"2024-06-28 20:15:56","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":415920,"visible":true,"origin":"","legend":"\u003cp\u003eTimeline view of keywords.\u003c/p\u003e\n\u003cp\u003e(A) Timeline view of keywords in the CNKI database. (B) Timeline view of keywords in the WoS core database. The circular nodes on the line represent the top three keywords with the greatest frequency of occurrence in this time slice. The timeline is shown at the top of the figure, and the year corresponding to the node is its publication time. The link between nodes represents the co-citation relationship.\u003c/p\u003e","description":"","filename":"OnlineFIGURE5.png","url":"https://assets-eu.researchsquare.com/files/rs-4451685/v1/677590887025cc070a2ad215.png"},{"id":59295480,"identity":"ddb91aaa-bff8-49f5-bb05-b903913f5822","added_by":"auto","created_at":"2024-06-28 20:07:56","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":257409,"visible":true,"origin":"","legend":"\u003cp\u003eTwenty-five keywords with the strongest citation bursts.\u003c/p\u003e\n\u003cp\u003e(A)The 25 keywords with the strongest citation bursts in CNKI. (B) The 25 keywords with the strongest citation bursts in the WoS core database. The blue line indicates the time axis, whereas the red segment on the blue time axis indicates burst detection, along with the start year, end year, and burst duration.\u003c/p\u003e","description":"","filename":"OnlineFIGURE6.png","url":"https://assets-eu.researchsquare.com/files/rs-4451685/v1/2f05dfc64b93f266824a0407.png"},{"id":59295478,"identity":"71869131-2a77-4b03-a47f-b808dbd937e0","added_by":"auto","created_at":"2024-06-28 20:07:56","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":285412,"visible":true,"origin":"","legend":"\u003cp\u003eCo-author analysis.\u003c/p\u003e\n\u003cp\u003e(A) Co-author network in the CNKI database. (B) Co-author network in the WoS core database. The circle indicates the author; the larger the size of the circle, the greater the number of publications from the author. The links between the nodes indicate cooperation between the authors.\u003c/p\u003e","description":"","filename":"OnlineFIGURE7.png","url":"https://assets-eu.researchsquare.com/files/rs-4451685/v1/ade037f3dcfd3c06edd4308a.png"},{"id":65068439,"identity":"8e0b164c-c326-48fe-ab19-f6757daba9f5","added_by":"auto","created_at":"2024-09-23 09:22:36","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":3268649,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4451685/v1/8899fdda-6902-4d0c-bdc5-12f61a41488d.pdf"}],"financialInterests":"","formattedTitle":"Rare disease publishing trends worldwide and in China: a citespace-based bibliometric study","fulltext":[{"header":"1 Introduction","content":"\u003cp\u003eRare diseases refer to a group of clinically heterogeneous disorders characterized by considerably low prevalence and a small population of affected individuals[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. Different countries and regions have established different specific definitions for rare diseases. The U.S. Food and Drug Administration (FDA) defines rare diseases as \"any disease or condition that affects\u0026thinsp;\u0026lt;\u0026thinsp;200,000 persons in the United States[\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e].\" The European Medicines Agency (EMA) defines rare diseases as \"life-threatening or chronically debilitating conditions that affect no more than 5 in 10,000 people in the EU[\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e].\" According to The Report on the Definition of Rare Diseases in China 2021, China defines rare diseases as \"diseases with a neonatal incidence rate of less than 1 in 10,000, a prevalence rate of less than 1 in 10,000, and a total affected population of less than 140,000[\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e].\" According to estimates, rare diseases affect over 300\u0026nbsp;million patients worldwide, with over 7,000 rare diseases accounting for 10% of all human diseases. Among these, 80% are of genetic origin[\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. However, currently, effective treatment methods are unavailable for more than 90% of rare diseases[\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. The direct medical costs, non-medical costs, and productivity losses associated with rare diseases impose a significant burden on society[\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. Therefore, the treatment and management of rare diseases have become important global public health issues[\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eAccording to statistics, the number of patients with rare diseases in China is estimated to be approximately 20\u0026nbsp;million, with an average of 200,000 new cases reported annually[\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. Rare diseases are receiving increasing attention in China. In 2018, China released The First Batch of Rare Disease Catalog in China, which mentioned 121 rare diseases[\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. This made China the first country to classify rare diseases using a specific list[\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. In 2023, China released The Second Batch of Rare Disease Catalog in China, which added 86[\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]new rare diseases to the list. Meanwhile, globally, developed countries such as the United States, France, and Germany have implemented national rare disease programs and orphan drug regulations and provide substantial funding to support research innovation and the establishment of healthcare systems for rare diseases[\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. Academic research on rare diseases has experienced unprecedented and rapid development. Web of Science (WoS) and China National Knowledge Infrastructure (CNKI) are the most comprehensive databases for core journal indexing in China and worldwide. They can help identify scientific research trends from publications in different languages and country perspectives[\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. This study aims to provide a comprehensive overview of the research trends in rare diseases over the past decade using CiteSpace software. We summarize the development process in the field of rare diseases and provide directions for further advancements in this area.\u003c/p\u003e"},{"header":"2 Methods","content":"\u003ch2\u003e2.1\u0026nbsp; \u0026nbsp; \u0026nbsp;Retrieval Strategy\u003c/h2\u003e\n\u003cp\u003eThe data for this study were obtained from the WoS Core Collection and CNKI databases. For the WoS database, a topic-based search was conducted using the keywords \u0026quot;(rare disease) OR (rare cancer) OR (rare tumor)\u0026quot; . The keyword \u0026quot;rare disease\u0026quot; was set as a \u0026quot;must inclusion\u0026quot;, and the time range spanned from January 1, 2013, to December 31, 2023. The selected document types were \u0026quot;Review Article\u0026quot; and \u0026quot;Article.\u0026quot;\u003c/p\u003e\n\u003cp\u003eFor the CNKI database, the search strategy included the keywords \u0026quot;(罕见病) OR (罕见疾病) OR (罕见肿瘤)\u0026quot; for the topic search. The time range spanned from January 1, 2013, to December 31, 2023. The selected document type was \u0026quot;Journal Article.\u0026quot;\u003c/p\u003e\n\u003ch2\u003e2.2\u0026nbsp; \u0026nbsp; \u0026nbsp;Inclusion Criteria\u003c/h2\u003e\n\u003cp\u003eThe inclusion criteria for the academic papers were as follows: the articles must have keywords such as \u0026quot;罕见病\u0026quot; (rare disease), \u0026quot;罕见疾病\u0026quot; (rare disorder), or \u0026quot;罕见肿瘤\u0026quot; (rare tumor), and the research topic must be related to rare diseases or rare tumors. The inclusion was limited to academic journal papers available in the Chinese language for CNKI. No language restrictions were used for papers retrieved from the WoS.\u003c/p\u003e\n\u003ch2\u003e2.3\u0026nbsp; \u0026nbsp; \u0026nbsp;Exclusion Criteria\u003c/h2\u003e\n\u003cp\u003eThe exclusion criteria for literature selection were as follows:\u003c/p\u003e\n\u003cp\u003e(1) Duplicate publications.\u003c/p\u003e\n\u003cp\u003e(2) Literature unrelated to the research topic of rare diseases or rare tumors.\u003c/p\u003e\n\u003cp\u003e(3) Literature without relevant keywords and/or the complete text.\u003c/p\u003e\n\u003cp\u003e(4) Conference papers, patents, newspapers, and project reports.\u003c/p\u003e\n\u003ch2\u003e2.4\u0026nbsp; \u0026nbsp; \u0026nbsp;Literature Screening and Data Extraction\u003c/h2\u003e\n\u003cp\u003eTwo researchers conducted a thorough review of the literature based on the predetermined inclusion and exclusion criteria. They screened the titles and abstracts to exclude irrelevant data. In case of discrepancies, a third person was consulted for consensus. The search results from CNKI were exported in \u0026quot;Refworks\u0026quot; format, whereas the results from WoS were exported using \u0026quot;Plain Text - Full Record and References\u0026quot; as the data source.\u003c/p\u003e\n\u003ch2\u003e2.5\u0026nbsp; \u0026nbsp; \u0026nbsp;Analysis Method\u003c/h2\u003e\n\u003cp\u003eCiteSpace 6.1.R6 is a Java-based program that supports visual exploration and knowledge discovery in literature databases. The analysis was conducted using CiteSpace to aid the visualization of the research landscape[13]. The time slice was set to 1 year, and the top N was set to 50. Pruning was set to Pathfinder and Pruning sliced networks. The analysis included the K-means clustering analysis of keywords and the identification of emerging research frontiers. The results were presented in the form of timeline graphs and keyword burst graphs in the visual interface of CiteSpace.\u003c/p\u003e"},{"header":"3 Results","content":"\u003ch2\u003e3.1\u0026nbsp; \u0026nbsp; \u0026nbsp;Literature Search Results\u003c/h2\u003e\n\u003cp\u003eA total of 11,347 papers were retrieved from WoS. After data inspection, deduplication, and cleaning, 10,754 papers were included in the study. These papers were exported in the form of \u0026quot;Plain Text - Full Record and References\u0026quot;. An initial screening of CNKI yielded 2,152 papers. After further evaluation, 969 papers were selected and included in the study\u0026nbsp;(Figure 1).\u003c/p\u003e\n\u003cp\u003eIn the CNKI database (Figure 2A), the overall number of publications was relatively low and showed slow growth. There was a decline in 2018, followed by a recovery to normal levels. A rapid increase was observed from 2022. In 2023, the number of publications was 5.97 times greater than that in 2013. In the WoS database, the number of publications in the rare disease field showed a steady growth trend (Figure 2B). The growth rate increased significantly from 2018, although there was a marginal decline in 2023.\u003c/p\u003e\n\u003cp\u003eBased on a comparison of the domestic and international publication counts (Figure 2C), the field of research on rare diseases is continuously expanding both domestically and internationally. Compared to domestic journals, international journals show a higher level of attention and depth of research in this field.\u003c/p\u003e\n\u003cp\u003eUsing a nonlinear index to fit the growth trend, the curve fitting equation for CNKI was set at Y = -134.6*exp(0.0567*X), R\u003csup\u003e2\u0026nbsp;\u003c/sup\u003e= 0.8894; WoS is Y = -72.97*exp(0.0376*X), R\u003csup\u003e2\u0026nbsp;\u003c/sup\u003e= 0.8644.\u003c/p\u003e\n\u003ch2\u003e3.2\u0026nbsp; \u0026nbsp; \u0026nbsp;Database Literature Spatial Distribution (Core Countries/Institutions)\u003c/h2\u003e\n\u003ch3\u003e3.2.1\u0026nbsp;\u0026nbsp;Countries and Regions\u003c/h3\u003e\n\u003cp\u003eThe country with the greatest number of publications in the WoS database was the United States, with 2423 papers. China ranked second with 1969 papers, followed by Italy and Germany, both with over 1000 papers. However, there was a significant gap between the top two countries and the rest (Table 1 ). This indicates the core position of the United States in the field of rare disease research. China also demonstrated strong research capabilities. Among the top 10 countries, six were European countries. From the Network of Collaborating Countries (Figure 3), \u0026nbsp;extensive and frequent collaboration was observed among European and American countries. However, currently, China has limited research collaborations with other countries. In terms of literature centrality, the Netherlands had the greatest intermediary centrality (0.09), indicating close collaborative connections with other countries. The Netherlands has not only published a large volume of research output but also achieved high-quality results in the field of rare disease research, thus playing a crucial role.\u003c/p\u003e\n\u003ch3\u003e3.2.2\u0026nbsp;\u0026nbsp;Research Institutions\u003c/h3\u003e\n\u003cp\u003eAmong publishing institutions (Table 2\u0026nbsp;), Chinese research institutions have abundant research output in both domestic and international databases. The Beijing Union Medical College Hospital, Chinese Academy of Medical Sciences, as a top medical and research center in China, is the only institution that ranks among the top 10 institutions in both domestic and international databases. It houses the National Key Laboratory for Rare and Difficult Diseases and focuses on diseases such as Gitelman syndrome, transthyretin amyloidosis cardiomyopathy, and hereditary retinal degeneration. Zhejiang University has the greatest number of publications in the WoS database and primarily focuses on rare diseases such as spinal muscular atrophy and Wilson\u0026apos;s disease. Combining the results of the analysis of countries in the previous section, it is evident that European and American countries hold critical positions in the field of rare disease research. Meanwhile, the research capabilities of China are noteworthy.\u003c/p\u003e\n\u003ch2\u003e3.3\u0026nbsp; \u0026nbsp; \u0026nbsp;Keywords\u003c/h2\u003e\n\u003ch3\u003e3.3.1\u0026nbsp;\u0026nbsp;Co-occurrence of Keywords\u003c/h3\u003e\n\u003cp\u003eKeywords are a reflection of the core content of the literature. In this study, we selected co-occurrence network graphs of keywords with a frequency greater than 100 in the WoS database (Figure 4B). The top three keywords were \u0026quot;rare disease\u0026quot; (1662), \u0026quot;diagnoses\u0026quot; (980), and \u0026quot;mutation\u0026quot; (833) (Table 3\u0026nbsp;). \u0026quot;Management\u0026quot; (794) also had a high frequency. In the CNKI database (Figure 4A, Table 3), \u0026quot;rare disease\u0026quot; was also the most frequently appearing keyword (452), followed by \u0026quot;orphan drugs\u0026quot; (100) and \u0026quot;diagnosis\u0026quot; (38). A comparison of the two showed that \u0026quot;rare disease,\u0026quot; \u0026quot;diagnosis,\u0026quot; \u0026quot;therapy,\u0026quot; and \u0026quot;Children\u0026quot; are among the top 10 keywords with the\u0026nbsp;greatest\u0026nbsp;frequency in both databases. This indicates that diagnosis, therapy, and children\u0026rsquo;s rare diseases are common themes of concern in this field at both domestic and global levels, and they represent the research focus. However, among the high-frequency keywords in the domestic database, certain terms were related to orphan drugs and rare drugs, which were also treatment-related. In contrast, the international database focused more on gene-related directions such as \u0026quot;mutation\u0026quot; and \u0026quot;expression,\u0026quot; as well as rare disease management. This reveals the different research perspectives between domestic and international studies in this field. Chinese research institutions may place a greater emphasis on drug development and application, whereas international research tends to explore the mechanisms underlying rare diseases and the social management of special populations.\u003c/p\u003e\n\u003ch3\u003e3.3.2\u0026nbsp;\u0026nbsp;Keyword Clustering\u003c/h3\u003e\n\u003cp\u003eKeyword clustering can reflect the different research focuses in a particular field. The smaller the clustering number, the more the keywords included in that cluster. In the WoS database (Table 4), orphan drugs and whole-exome sequencing were the most prominent research directions. Case reports were the primary form of research output, indicating that with the improvement of medical standards and advancement of diagnostic methods, a greater number of rare disease cases are being reported. In the CNKI database (Table 4\u0026nbsp;), orphan drugs remain a research focus. The comparison between the two databases reconfirmed the difference in research focuses between domestic and international studies in the field of rare diseases. These research directions also indicate that international research on rare diseases has focused on findings at the molecular level, whereas Chinese journals continue to focus on treatment and medication, with less emphasis on the investigation of disease mechanisms. The development of the field of rare diseases in China is less advanced than the international community.\u003c/p\u003e\n\u003ch3\u003e3.3.3\u0026nbsp;\u0026nbsp;Keyword Timeline Graph\u003c/h3\u003e\n\u003cp\u003eThe timeline graph reflects the development of keywords within each cluster. In the WoS database\u0026nbsp;(Figure 5B), the top ten keywords in terms of frequency have been appearing since 2013 and have maintained a high occurrence rate over the past 10 years. This indicates that the diagnosis, therapy, management, and genetic research of rare diseases constitute the foundation of this field. On this basis, medical genetics (2019), genomics (2018), and public health (2020) have advanced considerably, aiding rare disease research at a deeper investigative level. In the CNKI database\u0026nbsp;(Figure 5A), high-frequency keywords such as \u0026quot;rare disease,\u0026quot; \u0026quot;orphan drugs,\u0026quot; and \u0026quot;rare drugs\u0026quot; related to medications have appeared since 2013 and have laid the foundation for subsequent research directions. Keywords such as \u0026quot;diagnosis,\u0026quot; \u0026quot;therapy,\u0026quot; and \u0026quot;clinical trials\u0026quot; only appeared first in 2015-2016, exhibiting a lag compared to international trends. Keywords related to rare disease management and social support in the field of social sciences also appeared relatively late, indicating that China still lacks sufficient social attention and policy support for rare disease populations. Based on observations of the keyword burst graph (Figure 6), the Ice Bucket Challenge once created a wave of enthusiasm in China but disappeared within a year. This indicates that while marketing-style dissemination can increase social awareness of rare diseases, it does not significantly impact social security in rare disease populations. Currently, the research focus is concentrated on medical security, and governmental influence may significantly improve the lives of rare disease populations in China.\u003c/p\u003e\n\u003ch2\u003e3.4\u0026nbsp; \u0026nbsp; \u0026nbsp;Authors\u003c/h2\u003e\n\u003cp\u003eIn the WoS database, Taruscio, Domenica, Boycott, Kym M, and Baynam, Gareth were the top three authors in terms of publication volume (Table 5\u0026nbsp;). The three authors constituted the center in the collaboration network, and their collaboration has gained prominence in the past 5 years (Figure 7B). Before this period, the author collaboration network was not significant, with the majority of authors producing independent work. This indicates that contemporary research places greater emphasis on multi-team collaboration and multi-center studies. Taruscio, Domenica, Boycott, Kym M, and others have contributed to rare disease research for long, consistently producing research output, and they are important scholars in this field.\u003c/p\u003e\n\u003cp\u003eThe author collaboration network reflected in the CNKI database is relatively close but shows clear stages (Figure 7A). In 2013-2014, Pei-Wen Wang and Jin-Ping Xie were the central authors in the network. The collaboration network centered around Shu-Yang Zhang, Bo Zhang, and Meng-Chun Gong lasted for a longer duration. The publication volume clearly indicated that this team has made outstanding contributions to the field of rare diseases (Table 5). However, their output decreased significantly in the past 3 years, and the formation of novel collaboration networks is not yet apparent.\u003c/p\u003e\n\u003ch2\u003e3.5\u0026nbsp; \u0026nbsp; \u0026nbsp;Co-cited References\u003c/h2\u003e\n\u003cp\u003eHighly cited\u0026nbsp;references\u0026nbsp;can indicate the hot topics in a research field. By analyzing these co-cited references, the dynamic changes in research topics within a specific time range can be identified.\u0026nbsp; The top three co-cited references were \u0026quot;Estimating cumulative point prevalence of rare diseases: analysis of the Orphanet database\u0026nbsp;[14]\u0026quot;, \u0026quot;Standards and guidelines for the interpretation of sequence variants: a joint consensus recommendation of the American College of Medical Genetics and Genomics and the Association for Molecular Pathology[15]\u0026quot;, and \u0026quot;The mutational constraint spectrum quantified from variation in 141,456 humans[16]\u0026quot;\u0026nbsp;(Table 6). The first-ranked reference was cited as many as 156 times. We used the Orphanet database to estimate the cumulative point prevalence of rare diseases. Of the 6,172 unique rare diseases, 71.9% were genetic, and 69.9% manifest in childhood. The second- and third-ranked references were both related to genomics.\u003c/p\u003e\n\u003cp\u003eTable 7 presents further analysis of the hot topics and progress in the field of rare diseases over the past 10 years. This study selected the top 15 references with the strongest citation bursts. Among them, six articles were related to genomics[15-20], and three articles reported database-related content, including those related to the Orphanet [14] and HPO databases[21, 22]. Two articles introduced disease-related platforms, namely The Matchmaker Exchange[23], a platform for rare disease gene discovery, and PhenoTips[24], a software for patient phenotype analysis for clinical and research purposes. The remaining articles cover topics such as writing standards for reviews[25], disease terms definition [2], social science research[21], and reviews[26] on rare diseases. Evidently, genomic research is a hot topic in the field of rare diseases. Contribution to disease diagnosis and treatment using big data and artificial intelligence is also a growing trend. With social progression, minority groups are gradually receiving more attention, leading to an increase in social science research on rare disease populations.\u003c/p\u003e\n\u003cp\u003eCentrality can indicate the importance and influence of literature in a specific field. In this study, the top four cited references with the greatest centrality were selected (Table 8). Among them, one article had a centrality \u0026ge; 0.1. This article introduced the use of exome sequencing to identify disease-causing genes[27], reaffirming that genetics is a research hotspot and development trend in this field.\u003c/p\u003e"},{"header":"4 Discussion","content":"\u003ch2\u003e4.1\u0026nbsp; \u0026nbsp; \u0026nbsp;Comparison of Domestic and Foreign Databases\u003c/h2\u003e\n\u003cp\u003eAn analysis of the progressive knowledge graph in the field of rare diseases over the past 10 years shows that the field of rare disease research is entering a phase of rapid development. However, there are certain differences in the research data between domestic and foreign databases. In terms of the number of publications, the number of publications included in WoS over the past 10 years is ten times greater than that in CNKI. This could be explained by the fact that the publications were from global journals, whereas most journals in CNKI were from China. In terms of the growth rate, WoS has been growing rapidly since 2018, whereas CNKI showed a significant growth acceleration in 2022. This may be attributed to high-quality research from China being likely to be published internationally.\u003c/p\u003e\n\u003cp\u003eFrom the perspective of focus, the frequency ranking of keywords and clustering in CNKI indicate that domestic journals in China focus more on rare disease drugs, whereas foreign journals focus on genetics and therapies. China\u0026rsquo;s policies may help explain this difference. European countries started using Managed Entry Agreements (MEAs) to manage rare disease drugs as early as 2013 or before that. National authorities have the flexibility to adjust funding support, and pharmaceutical companies can ensure the normal market access of drugs considering cost-benefit conditions[28]. In recent years, policies have further improved, and some countries have developed specific programs to evaluate the approval of rare disease drugs. For example, in Italy, the approval process for orphan drugs is stated to be completed within 100 days[29]. In comparison, China\u0026apos;s corresponding policies are less advanced. Following the announcement of the first batch of rare disease catalogs in 2018, in April 2019, \u003cem\u003eThe Drug Administration Law of the People\u0026apos;s Republic of China\u003c/em\u003e was enacted to encourage the development of innovative rare disease drugs and prioritize the evaluation of approval[30]. However, it did not specify a timeframe.\u003c/p\u003e\n\u003cp\u003ePolicy orientation is closely related to academic development. Developed countries such as Europe and the United States have established comprehensive and mature systems for implementing the research, approval, and market access of rare disease drugs. These countries are also the primary forces in the research and production of rare disease drugs. Therefore, they conduct more genetic research, uncovering disease mechanisms and exploring new signaling pathways and mechanisms of action for the development of new drugs and therapies. Conversely, in China, most rare disease drugs are imported, and issues related to drug accessibility and market access still require improvement, despite the introduction of multiple policies in recent years to encourage independent drug research and development. However, the process is lengthy, and significant achievements may only be reported years later.\u003c/p\u003e\n\u003ch2\u003e4.2\u0026nbsp; \u0026nbsp; \u0026nbsp;Research Hotspots in the Field of Rare Diseases\u003c/h2\u003e\n\u003ch3\u003e4.2.1\u0026nbsp;\u0026nbsp;Rise of Social Science Research\u003c/h3\u003e\n\u003cp\u003ePatients with rare diseases often bear a dual burden of physical and psychological challenges. In the era of the biological-psychological-social medicine model[31], the diagnosis and treatment of diseases are no longer limited to technical aspects; it is also important to focus on the psychological well-being and social identity of patients. This has led to the development of medical humanities research in the field of rare diseases. Among the top 15 highly cited references, Zurynski Y\u0026apos;s cross-sectional study highlighted the reasons and consequences of delayed diagnosis in children with rare diseases. It emphasizes the need for healthcare professionals to provide psychological support to patients and for parents to prioritize genetic counseling and opt for rare disease-related education[32]. Disease burden is also a prominent theme of research. In the 2019 US Rare Disease Economic Burden Assessment, excess expenditures were primarily attributed to hospital inpatient care, prescription drugs, and productivity losses in the labor market owing to absenteeism and early retirement[33].\u003c/p\u003e\n\u003cp\u003eIn addition, the keyword \u0026quot;quality of life\u0026quot; appears over 200 times in the WoS database. A survey on the survival conditions of rare disease populations showed a positive correlation between informal social support and the quality of life. Patients who received social assistance had better quality of life in the psychological and social domains than those who did not[34]. \u0026quot;Management\u0026quot; and \u0026quot;healthcare coverage\u0026quot; are also frequent keywords. Countries worldwide are continuously updating their policies related to rare diseases[35, 36]. Processes to integrate rare disease populations into mainstream society are a global issue. In May 2021, the United Nations passed its first resolution on \u0026quot;Addressing the Challenges of Rare Disease Patients and Their Families,\u0026quot; which covers various aspects, such as education, employment, poverty, gender inequality, and support for the inclusion of patients with rare diseases in multiple societal dimensions[37]. As social citizens, rare disease populations have the right to enjoy social welfare policies, equal access to education, and employment opportunities. This can help improve their community awareness and self-acceptance. At the societal level, it can alleviate socioeconomic and management burdens, indicating the progress of human civilization.\u003c/p\u003e\n\u003ch3\u003e4.2.2\u0026nbsp;\u0026nbsp;Application of Artificial Intelligence and Big Data\u003c/h3\u003e\n\u003cp\u003eOwing to the small size of the rare disease population, misdiagnosis and mistreatment are common. The use of big data aids the sharing and linkage of patient information worldwide. Using the powerful computational capabilities of artificial intelligence, the relationship between genes and disease onset can be determined, and potential drug targets can be explored. Therefore, establishing a rare disease information database is of great significance for diagnosis, treatment, and research. Orphanet is a widely used database with information on rare disease medical classifications, gene information, and epidemiological indicators, among other data. The most highly cited reference in this context uses the accumulated data collected by Orphanet to estimate disease prevalence[14]. The Matchmaker Exchange (MME), which mentioned in a high-burst cited reference,\u0026nbsp;is a federated network connecting databases of genotypes and rare phenotypes using a common application programming interface[23]. By 2022, which was 7 years since it was founded, \u0026nbsp;the network had data from over 120,000 cases provided by more than 12,000 volunteers from 98 countries, with over 13,520 unique gene-to-gene matches established. New gene-disease connections are discovered every day[38].\u0026nbsp;Over the past decade, artificial intelligence has been used in the diagnosis and treatment of various diseases. For example, machine learning algorithms have been used to predict the clinical severity of progressive supranuclear palsy (PSP) by analyzing diffusion tensor imaging characteristics of the brain[39]. Automatic assessment tools have been developed to predict speech disorders in patients with amyotrophic lateral sclerosis (ALS) based on speech acoustics and pronunciation samples[40]. Big data and machine learning demonstrate the immense potential of artificial intelligence in the field of rare diseases. However, the widespread implementation of these tools in clinical applications requires regulatory frameworks, evidence from clinical trials, and compliance with ethical guidelines[41].\u003c/p\u003e\n\u003cp\u003eDisease registration is also focused on both domestically and internationally. Owing to the challenges in collecting rare disease data, individualized tracking of each patient is typically performed using case registries. Collecting epidemiological data through registries helps monitor the quality of management and patient prognosis processes while providing convenience for clinical research. Developed countries such as Europe and the United States have achieved a high level of refinement, regionalization, and networking in their registries. Examples include the European Rare Kidney Disease Registry (ERKReg)[42]\u0026nbsp;and the European\u0026nbsp;registry for patients with McArdle disease and other muscle glycogenoses\u0026nbsp;(EUROMAC\u0026nbsp;registry)[43]\u0026nbsp;. In contrast, in China, rare disease registries have been developed relatively late. The National Rare Disease Registry System (NRDRS), established in 2016, is expected to have a positive impact on epidemiological research within the country[44].\u003c/p\u003e\n\u003ch3\u003e4.2.3\u0026nbsp;\u0026nbsp;Genetic Research\u003c/h3\u003e\n\u003cp\u003eGenomic research is one of the most important hotspots in the field of rare diseases. In keyword analysis, keyword clustering in CNKI includes the label of \u0026quot;gene therapy,\u0026quot; whereas the high-frequency keywords in WoS include \u0026quot;mutation,\u0026quot; \u0026quot;expression,\u0026quot; and \u0026quot;gene,\u0026quot; all of which appear more than 300 times. Among the highly cited references in WoS, approximately half of the articles are related to genomics. The highest-ranked highly cited reference is a standard and guideline on the interpretation of sequence variations. It uses various types of variant evidence, including population data, computational data, functional data, and segregation data, to classify variations into five standards: \u0026quot;pathogenic,\u0026quot; \u0026quot;likely pathogenic,\u0026quot; \u0026quot;uncertain significance,\u0026quot; \u0026quot;likely benign,\u0026quot; and \u0026quot;benign\u0026quot;[15]. This article serves as a foundational declaration in the field of genomics. However, owing to the significant proportion of genetic diseases among rare diseases, the development of this guideline also contributes to the standardized representation of gene mutations in rare disease genomics research, which is of significance in determining gene-disease relationships.\u003c/p\u003e\n\u003cp\u003eGenomics is not only used to explore the etiology of rare diseases but also plays a role in the development of therapeutic drugs and treatments as research progresses. Luxturna, a gene therapy drug using adeno-associated virus (AAV) vectors, is administered through subretinal injection to treat inherited retinal dystrophy caused by RPE65 protein deficiency. Patisiran is an oligonucleotide-based therapy for familial transthyretin amyloidosis (FTA) that inhibits the misfolding of transthyretin protein, thereby impeding disease progression. Rare disease drugs based on gene therapies such as CAR-T and retroviral vectors have also been approved and launched in foreign markets[45]. As more mechanisms are discovered, the scope of gene therapy will continue to expand, bringing new hope for the treatment of rare diseases. However, the adoption of gene therapy in China remains limited, and further research and development are needed before it can be widely used in clinical practice.\u003c/p\u003e\n\u003ch2\u003e4.3\u0026nbsp; \u0026nbsp; \u0026nbsp;Key Scholars and Institutions in the Field of Rare Diseases\u003c/h2\u003e\n\u003cp\u003eIn the CNKI database, the core author Shu-Yang Zhang stands out with a significantly high publication volume. As the President of Peking Union Medical College Hospital (PUMCH) and Vice President of Peking Union Medical College, the collaborative network centered around Shu-Yang Zhang has consistently produced output over the past decade. The research institutions associated with Shu-Yang Zhang, namely PUMCH and Peking Union Medical College, have also achieved remarkable results in the field of rare disease research in China. Shu-Yang Zhang is a leading scholar in the field of rare diseases in China, with most of his published articles focusing on rare cardiovascular diseases or rare disease policies in China. Examples include \u0026quot;Progress in the Diagnosis and Treatment of Rare Cardiovascular Diseases\u0026nbsp;[46]\u0026quot;\u003csup\u003e\u0026nbsp;\u003c/sup\u003eand \u0026quot;Construction and Application of China\u0026apos;s National Rare Disease Registration System[47]\u003csup\u003e\u0026nbsp;\u003c/sup\u003e\u0026quot;. The articles published by Shu-Yang Zhang are mostly systematic reviews and expert consensus articles. PUMCH, as the host institution of the National Key Laboratory for Severe and Rare Diseases, encompasses various disciplines such as oncology, surgery, obstetrics, and gynecology. Its achievements span multiple types of publications, including case reports, systematic reviews, and clinical studies.\u003c/p\u003e\n\u003cp\u003eIn the WoS database, Taruscio D and Boycott KMare authors with the greatest number of publications. The collaborative network centered around these authors is the only evident collaboration network in the WoS database. Taruscio D is affiliated with the Istituto Superiore di Sanita in Rome, Italy, whereas Boycott KM is affiliated with the Children\u0026apos;s Hospital of Eastern Ontario in Canada. Both researchers have interests in genetics and experimental medicine. However, Taruscio D also focuses on public health management and healthcare services related to rare diseases, whereas Boycott KM has a stronger emphasis on genomics.\u003c/p\u003e\n\u003cp\u003eIn the analysis of co-cited literature, Boycott KM has two highly cited and highly prominent articles: \u0026quot;International Cooperation to Enable the Diagnosis of All Rare Genetic Diseases[48]\u0026quot; and \u0026quot;Rare-disease genetics in the era of next-generation sequencing: discovery to translation[18]\u0026quot; . However, Taruscio D does not have any highly cited articles. This indicates that Boycott KM is a key scholar in the field of international rare disease research and an important member of the International Rare Diseases Research Consortium (IRDiRC).\u003c/p\u003e\n\u003cp\u003eFrom an institutional perspective, Chinese research institutions have demonstrated significant achievements in scientific research globally. However, collaboration with international institutions is yet to be established. Domestic and international institutions and scholars should strengthen communication and cooperation, learn from each other\u0026rsquo;s experiences, and collectively promote the development of the field of rare diseases.\u003c/p\u003e"},{"header":"5 Conclusion","content":"\u003cp\u003eThis study used CiteSpace to analyze outstanding academic achievements in the field of rare diseases over the past decade. By visualizing and mapping key institutions, authors, keywords, and high-citation information, it identified research hotspots and development trends from different perspectives, providing insights for the global advancement of the field of rare diseases.\u003c/p\u003e \u003cp\u003eHowever, there are certain limitations to this study. First, the literature selection process was manual, which may have introduced subjectivity in the inclusion of literature, organization of literature information, and merging of keywords, potentially leading to the loss of some relevant articles. Secondly, CiteSpace uses its in-built algorithms for keyword merging and clustering, which may not fully represent all research content within a particular cluster. Additionally, research on specific rare diseases often does not directly include the term \"rare diseases,\" which implies that we may have excluded some studies focusing on individual rare diseases. Furthermore, owing to limitations in the CiteSpace software and CNKI database, the direct export of citation data was not possible, resulting in a lack of co-citation analysis for Chinese literature in this study.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cdiv class=\"DefinitionList\"\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eFDA\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eThe U.S. Food and Drug Administration\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eEMA\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eThe European Medicines Agency\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eWoS\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eWeb of Science\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eCNKI\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eChina National Knowledge Infrastructure\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eMEAs\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eManaged Entry Agreements\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eMME\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eThe Matchmaker Exchange\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003ePSP\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eProgressive Supranuclear Palsy\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eALS\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eAmyotrophic Lateral Sclerosis\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eERKReg\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eEuropean Rare Kidney Disease Registry\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eEUROMAC registry\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eEuropean registry for patients with McArdle disease and other muscle glycogenoses\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eNRDRS\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eThe National Rare Disease Registry System\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eAAV\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eAdeno-associated virus\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eFTA\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eFamilial transthyretin amyloidosis\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003ePUMCH\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003ePeking Union Medical College Hospital\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eIRDiRC\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eInternational Rare Diseases Research Consortium\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"Declarations","content":"\u003ch2\u003eEthics approval and consent to participate\u003c/h2\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003ch2\u003eConsent for publication\u003c/h2\u003e\n\u003cp\u003eAll the authors had complete access to the manuscript and agreed to submit it for publication.\u003c/p\u003e\n\u003ch2\u003eData Availability\u003c/h2\u003e\n\u003cp\u003eThe data presented in this research are available on request from the corresponding author.\u0026nbsp;\u003c/p\u003e\n\u003ch2\u003eConflict of Interest\u003c/h2\u003e\n\u003cp\u003eThe authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.\u003c/p\u003e\n\u003ch2\u003eFunding\u003c/h2\u003e\n\u003cp\u003eThis work was supported by Shanghai Municipal Philosophy and Social Sciences Planning Project: Research on the Multidimensional Construction of a Multi-level Healthcare System for Rare Diseases in Shanghai under the New Situation. [grant number: 2022BGL002]; 2022 Annual Talent Development Program of the Shanghai Municipal Health Commission: Research on Enhancing the Prevention, Treatment, and Assurance Capacity of Rare Diseases in Shanghai under the New Development Situation [grant number: 2022YQ058].\u003c/p\u003e\n\u003ch2\u003eAuthor Contributions\u003c/h2\u003e\n\u003cp\u003eQi Kong and Li-Ming Chen came up with the idea. Chen-Xin Fan, Ying Zhang conducted a thorough review of the literature, and Xin-Lei Yan was consulted for consensus in case of discrepancies. Chen-Xin Fan performed statistical analysis and made the figures by Citespace. Qi kong and Chen-Xin Fan composed the manuscript. Qi Kang and Pei-Hao Yin reviewed and optimized the manuscript. All the authors have approved the final draft submitted. Qi Kong, and Chen-Xin Fan contribute equally to this review.\u003c/p\u003e\n\u003ch2\u003eAcknowledgements\u003c/h2\u003e\n\u003cp\u003eWe appreciate KeTeng Edit （http://ketengedit.com/）provided language editing services for this article.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026rsquo; information\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eQi Kong\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eInstitution: Putuo Hospital, Shanghai University of Traditional Chinese Medicine, Shanghai, China;\u003c/p\u003e\n\u003cp\u003eInterventional Cancer Institute of Chinese Integrative Medicine, Shanghai University of Traditional Chinese Medicine, Shanghai, China\u003c/p\u003e\n\u003cp\u003eAddress: No.164 Lanxi Road, Putuo District, Shanghai, 200062, China; No.164 Lanxi Road, Putuo District, Shanghai, 200062, China\u003c/p\u003e\n\u003cp\u003eEmail: [email protected]\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eChen-Xin Fan\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eInstitution: Shanghai University of Traditional Chinese Medicine, Shanghai, China\u003c/p\u003e\n\u003cp\u003eAddress: 1200 Cai Lun Road,Zhangjiang Hi-TechPark,Pudong New Area, Shanghai, 201203, China\u003c/p\u003e\n\u003cp\u003eEmail: [email protected]\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eLi-Ming Chen\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eInstitution: Yueyang Hospital of Integrated Traditional Chinese and Western Medicine, Shanghai University of Traditional Chinese Medicine, Shanghai, China\u003c/p\u003e\n\u003cp\u003eAddress: No.650 South Wanping Road, Xuhui District, Shanghai, 200030, China\u003c/p\u003e\n\u003cp\u003eEmail: [email protected]\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eYing Zhang\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eInstitution: Shanghai University of Traditional Chinese Medicine, Shanghai, China\u003c/p\u003e\n\u003cp\u003eAddress: 1200 Cai Lun Road,Zhangjiang Hi-TechPark,Pudong New Area, Shanghai, 201203, China\u003c/p\u003e\n\u003cp\u003eEmail: [email protected]\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eXin-Lei Yan\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eInstitution: Shanghai University of Traditional Chinese Medicine, Shanghai, China\u003c/p\u003e\n\u003cp\u003eAddress: 1200 Cai Lun Road,Zhangjiang Hi-TechPark,Pudong New Area, Shanghai, 201203, China\u003c/p\u003e\n\u003cp\u003eEmail: [email protected]\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eQi Kang\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eInstitution: Shanghai Health Development Research Center (Shanghai Medical Information Research Center)\u003c/p\u003e\n\u003cp\u003eAddress: No.1477 West Beijing Road, Shanghai 200040, China\u003c/p\u003e\n\u003cp\u003eEmail: [email protected]\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePei-Hao Yin\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eInstitution: Putuo Hospital, Shanghai University of Traditional Chinese Medicine, Shanghai, China;\u003c/p\u003e\n\u003cp\u003eInterventional Cancer Institute of Chinese Integrative Medicine, Shanghai University of Traditional Chinese Medicine, Shanghai, China\u003c/p\u003e\n\u003cp\u003eAddress: No.164 Lanxi Road, Putuo District, Shanghai, 200062, China; No.164 Lanxi Road, Putuo District, Shanghai, 200062, China\u003c/p\u003e\n\u003cp\u003eEmail: [email protected]\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eSchieppati A, Henter JI, Daina E, Aperia A. 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Am J Hum Genet. 2017;100(5):695\u0026ndash;705. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.ajhg.2017.04.003\u003c/span\u003e\u003cspan address=\"10.1016/j.ajhg.2017.04.003\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"},{"header":"Tables","content":"\u003ch2\u003eTable 1 The top 10 productive countries with publications concerning rare disease.\u003c/h2\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cem\u003eRank\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cem\u003eArticle counts\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cem\u003eCentrality\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cem\u003eCountries\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e2423\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eUSA\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1969\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003ePEOPLES R CHINA\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1123\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eITALY\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1020\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eGERMANY\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e881\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eFRANCE\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e821\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eENGLAND\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e649\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eJAPAN\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e598\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eSPAIN\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e465\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eCANADA\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e379\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eNETHERLANDS\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003ch2\u003eTable 2 The top 10 productive institutions ranked by the numbers of publications.\u003c/h2\u003e\n\u003cdiv align=\"center\"\u003e\n \u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" summary='{\"styleId\":2}'\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cem\u003eRank\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cem\u003eArticle counts\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cem\u003eInstitutions(CNKI)\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cem\u003eArticle counts\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cem\u003eInstitutions(WoS)\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e74\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e中国医学科学院北京协和医院(Peking Union Medical College Hospital)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e151\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eZhejiang Univ\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e61\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e中国药科大学(China Medical University)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e132\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eCapital Med Univ\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e北京大学(Peking University)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e127\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eHarvard Med Sch\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e中国医学科学院北京协和医学院(Peking Union Medical College)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e126\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eUniv Milan\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e山东大学(Shandong University)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e123\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eMayo Clin\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e国家药品监督管理局(National Medical Products Administration)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e118\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eUniv Toronto\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e沈阳药科大学(Shenyang Pharmaceutical University)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e105\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eUniv Penn\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e上海市卫生和健康发展研究中心(Shanghai Health and Health Development Research Center)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e98\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eChinese Acad Med Sci\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e四川大学华西医院(West China Hospital，Sichuan University)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e94\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eSichuan Univ\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e上海交通大学(Shanghai Jiao Tong University)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e90\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eINSERM\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003ch2\u003eTable 3 The top 10 keywords\u0026nbsp;ranked by the\u0026nbsp;frequency.\u003c/h2\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"610\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"6.39344262295082%\"\u003e\n \u003cp\u003e\u003cem\u003eRank\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.754098360655737%\"\u003e\n \u003cp\u003e\u003cem\u003eArticle counts\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.655737704918034%\"\u003e\n \u003cp\u003e\u003cem\u003eCentrality\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.9672131147541%\"\u003e\n \u003cp\u003e\u003cem\u003eKeywords of CNKI\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.754098360655737%\"\u003e\n \u003cp\u003e\u003cem\u003eArticle counts\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.819672131147541%\"\u003e\n \u003cp\u003e\u003cem\u003eCentrality\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.65573770491803%\"\u003e\n \u003cp\u003e\u003cem\u003eKeywords of WoS\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e452\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1.19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e罕见病(rare disease)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1662\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003erare disease\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e100\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e孤儿药(orphan drugs)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e980\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003ediagnosis\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e38\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e诊断(diagnosis)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e833\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003emutation\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e35\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e治疗(therapy)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e794\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003emanagement\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e医疗保障(medical security)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e619\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003edisease\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e罕用药(rare drugs)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e602\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003echildren\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e儿童(children)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e403\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003etherapy\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e罕见疾病(rare disorder)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e390\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003ecase report\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e临床试验(clinical trial)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e380\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eexpression\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e可及性(accessibility)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e377\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003ecancer\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003ch2\u003eTable 4 The information of clusters about keyword co-citation analysis.\u003c/h2\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"99%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"11.278195488721805%\"\u003e\n \u003cp\u003e\u003cem\u003eDatabase\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.278195488721805%\"\u003e\n \u003cp\u003e\u003cem\u003eClusters\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.488721804511279%\"\u003e\n \u003cp\u003e\u003cem\u003e\u0026nbsp;Label\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"61.954887218045116%\"\u003e\n \u003cp\u003e\u003cem\u003eTerms\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"11.278195488721805%\" rowspan=\"6\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eWoS Database\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.278195488721805%\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.488721804511279%\"\u003e\n \u003cp\u003erare disease\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"61.954887218045116%\"\u003e\n \u003cp\u003erare disease; target therapy; desmoplastic small round cell tumor; tyrosine kinase receptor; fetal growth restriction | squamous cell carcinoma; targeted therapy; penile cancer; systemic therapy; retroperitoneal sarcoma\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"12.711864406779661%\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.45762711864407%\"\u003e\n \u003cp\u003eorphan drug\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"69.83050847457628%\"\u003e\n \u003cp\u003erare disease; orphan drug; spinal muscular atrophy; real-life outcome data; single-arm trial | rare diseases; comparative effectiveness; evidence generation; patient-oriented outcomes; evidence synthesis\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"12.711864406779661%\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.45762711864407%\"\u003e\n \u003cp\u003ecase report\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"69.83050847457628%\"\u003e\n \u003cp\u003ecase report; langerhans cell histiocytosis; igg4-related disease; central diabetes insipidus; bone marrow | magnetic resonance imaging; myeloid sarcoma; sacral spine; primary testicular lymphoma; testicular cancer\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"12.711864406779661%\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.45762711864407%\"\u003e\n \u003cp\u003ewhole-exome sequencing\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"69.83050847457628%\"\u003e\n \u003cp\u003erare disease; whole-exome sequencing; genic intolerance; health ethics; government regulation | mutation; variant; protein; tool; common disease\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"12.711864406779661%\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.45762711864407%\"\u003e\n \u003cp\u003eaortic dilatation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"69.83050847457628%\"\u003e\n \u003cp\u003erare disease; aortic dilatation; bicuspid aortic valve; aortic dissection; aortic coarctation | pulmonary hypertension; lung cancer; von recklinghausen; neurofibromatosis type; viral coinfection\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"12.711864406779661%\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.45762711864407%\"\u003e\n \u003cp\u003eoxidative stress\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"69.83050847457628%\"\u003e\n \u003cp\u003erare disease; oxidative stress; lipid metabolism; mitochondrial dysfunction; brain iron accumulation | gene expression; growth; model; mutation; mice\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"11.278195488721805%\" rowspan=\"10\"\u003e\n \u003cp\u003eCNKI\u003c/p\u003e\n \u003cp\u003edatabase\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.278195488721805%\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.488721804511279%\"\u003e\n \u003cp\u003e罕见病(rare disease)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"61.954887218045116%\"\u003e\n \u003cp\u003e罕见病(rare disease);\u0026nbsp;孤儿药(orphan drugs);\u0026nbsp;罕用药(rare drugs);\u0026nbsp;罕见疾病(rare disorder);\u0026nbsp;诊断(diagnosis)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"12.711864406779661%\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.45762711864407%\"\u003e\n \u003cp\u003e孤儿药(orphan drugs)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"69.83050847457628%\"\u003e\n \u003cp\u003e孤儿药(orphan drugs);\u0026nbsp;药物政策(medicine policy);\u0026nbsp;对比分析(comparative analysis);\u0026nbsp;分析(analysis);\u0026nbsp;价格谈判(price negotiation)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"12.711864406779661%\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.45762711864407%\"\u003e\n \u003cp\u003e罕用药(rare drugs)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"69.83050847457628%\"\u003e\n \u003cp\u003e罕用药(rare drugs);\u0026nbsp;美国(America);\u0026nbsp;制药企业(pharmaceutical companies);\u0026nbsp;研发(research and development);\u0026nbsp;适应证扩展(indication expansion)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"12.711864406779661%\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.45762711864407%\"\u003e\n \u003cp\u003e病理学(Pathology)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"69.83050847457628%\"\u003e\n \u003cp\u003e病理学(Pathology);\u0026nbsp;基因治疗(gene therapy);\u0026nbsp;临床研究(clinical studies);\u0026nbsp;诊断(diagnosis);\u0026nbsp;罕见病(rare disease)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"12.711864406779661%\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.45762711864407%\"\u003e\n \u003cp\u003e儿童(children)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"69.83050847457628%\"\u003e\n \u003cp\u003e儿童(children);\u0026nbsp;治疗(therapy);\u0026nbsp;人工智能(artificial intelligence);\u0026nbsp;临床表现(clinical manifestations);\u0026nbsp;分类(classification)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"12.711864406779661%\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.45762711864407%\"\u003e\n \u003cp\u003e医学教育(medical education)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"69.83050847457628%\"\u003e\n \u003cp\u003e医学教育(medical education);\u0026nbsp;罕见疾病(rare disorder);\u0026nbsp;临床思维(clinical thinking);\u0026nbsp;计算机技术(computer technology);\u0026nbsp;教学质量(teaching quality)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"12.711864406779661%\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.45762711864407%\"\u003e\n \u003cp\u003e医疗保障(medical security)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"69.83050847457628%\"\u003e\n \u003cp\u003e医疗保障(medical security);\u0026nbsp;血友病(Hemophilia);\u0026nbsp;可负担性(affordability);\u0026nbsp;伦理原则(ethical principles);\u0026nbsp;医保政策(medical insurance policy)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"12.711864406779661%\"\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.45762711864407%\"\u003e\n \u003cp\u003e可及性(accessibility)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"69.83050847457628%\"\u003e\n \u003cp\u003e可及性(accessibility);\u0026nbsp;影响因素(influencing factors);\u0026nbsp;可获得性(availability);\u0026nbsp;策略研究(strategy research);\u0026nbsp;评价指标(evaluation index)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"12.711864406779661%\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.45762711864407%\"\u003e\n \u003cp\u003e临床试验(clinical trial)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"69.83050847457628%\"\u003e\n \u003cp\u003e临床试验(clinical trial);\u0026nbsp;招募(recruitment);\u0026nbsp;药物研发(drug development);\u0026nbsp;肺部罕见肿瘤(rare lung tumors);\u0026nbsp;优先审评(priority review)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"12.711864406779661%\"\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.45762711864407%\"\u003e\n \u003cp\u003e中国(China)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"69.83050847457628%\"\u003e\n \u003cp\u003e中国(China);\u0026nbsp;保障(guarantee);\u0026nbsp;国家罕见病注册系统( national rare disease registration system);\u0026nbsp;合作(cooperation);\u0026nbsp;戈谢病(Gauchers disease)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003ch2\u003eTable 5\u0026nbsp;The top\u0026nbsp;5\u0026nbsp;productive\u0026nbsp;authors\u0026nbsp;ranked by the numbers of publications.\u003c/h2\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"555\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"6.846846846846847%\"\u003e\n \u003cp\u003e\u003cem\u003eRank\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.54054054054054%\"\u003e\n \u003cp\u003e\u003cem\u003eArticle counts\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"29.00900900900901%\"\u003e\n \u003cp\u003e\u003cem\u003eAuthor\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.531531531531531%\"\u003e\n \u003cp\u003e\u003cem\u003eRank\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.54054054054054%\"\u003e\n \u003cp\u003e\u003cem\u003eArticle counts\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.531531531531531%\"\u003e\n \u003cp\u003e\u003cem\u003eAuthor\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eTaruscio, Domenica\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e张抒扬(Shu-Yang Zhang)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eBoycott, Kym M\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e张波(Bo Zhang)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eBaynam, Gareth\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e康琦(Qi Kang)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eRobinson, Peter N\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e弓孟春(Meng-Chun Gong)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eLochmueller, Hanns\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e刘鑫(Xin Liu)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e金春林(Chun-Lin Jin)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003ch2\u003eTable 6 The top 10 cited references with the highest cited frequency.\u003c/h2\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"603\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"9.286898839137645%\"\u003e\n \u003cp\u003e\u003cem\u003eFreq\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.7893864013267%\"\u003e\n \u003cp\u003e\u003cem\u003eBurst\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.588723051409618%\"\u003e\n \u003cp\u003e\u003cem\u003eCentrality\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.925373134328359%\"\u003e\n \u003cp\u003e\u003cem\u003eAuthor\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.22719734660033%\"\u003e\n \u003cp\u003e\u003cem\u003eSource\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"30.182421227197345%\"\u003e\n \u003cp\u003e\u003cem\u003eDOI\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"9.286898839137645%\"\u003e\n \u003cp\u003e170\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.7893864013267%\"\u003e\n \u003cp\u003e28.18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.588723051409618%\"\u003e\n \u003cp\u003e0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.925373134328359%\"\u003e\n \u003cp\u003eWakap SN\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.22719734660033%\"\u003e\n \u003cp\u003eEUR J HUM GENET\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"30.182421227197345%\"\u003e\n \u003cp\u003e10.1038/s41431-019-0508-0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"9.286898839137645%\"\u003e\n \u003cp\u003e110\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.7893864013267%\"\u003e\n \u003cp\u003e34.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.588723051409618%\"\u003e\n \u003cp\u003e0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.925373134328359%\"\u003e\n \u003cp\u003eRichards S\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.22719734660033%\"\u003e\n \u003cp\u003eGENET MED\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"30.182421227197345%\"\u003e\n \u003cp\u003e10.1038/gim.2015.30\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"9.286898839137645%\"\u003e\n \u003cp\u003e86\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.7893864013267%\"\u003e\n \u003cp\u003e13.74\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.588723051409618%\"\u003e\n \u003cp\u003e0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.925373134328359%\"\u003e\n \u003cp\u003eKarczewski KJ\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.22719734660033%\"\u003e\n \u003cp\u003eNATURE\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"30.182421227197345%\"\u003e\n \u003cp\u003e10.1038/s41586-020-2308-7\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"9.286898839137645%\"\u003e\n \u003cp\u003e83\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.7893864013267%\"\u003e\n \u003cp\u003e20.45\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.588723051409618%\"\u003e\n \u003cp\u003e0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.925373134328359%\"\u003e\n \u003cp\u003eLek M\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.22719734660033%\"\u003e\n \u003cp\u003eNATURE\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"30.182421227197345%\"\u003e\n \u003cp\u003e10.1038/nature19057\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"9.286898839137645%\"\u003e\n \u003cp\u003e60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.7893864013267%\"\u003e\n \u003cp\u003e3.62\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.588723051409618%\"\u003e\n \u003cp\u003e0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.925373134328359%\"\u003e\n \u003cp\u003eWright CF\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.22719734660033%\"\u003e\n \u003cp\u003eNAT REV GENET\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"30.182421227197345%\"\u003e\n \u003cp\u003e10.1038/nrg.2017.116\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"9.286898839137645%\"\u003e\n \u003cp\u003e58\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.7893864013267%\"\u003e\n \u003cp\u003e9.74\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.588723051409618%\"\u003e\n \u003cp\u003e0.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.925373134328359%\"\u003e\n \u003cp\u003eFerreira CR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.22719734660033%\"\u003e\n \u003cp\u003eAM J MED GENET A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"30.182421227197345%\"\u003e\n \u003cp\u003e10.1002/ajmg.a.61124\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"9.286898839137645%\"\u003e\n \u003cp\u003e57\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.7893864013267%\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.588723051409618%\"\u003e\n \u003cp\u003e0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.925373134328359%\"\u003e\n \u003cp\u003eHaendel M\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.22719734660033%\"\u003e\n \u003cp\u003eNAT REV DRUG DISCOV\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"30.182421227197345%\"\u003e\n \u003cp\u003e10.1038/d41573-019-00180-y\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"9.286898839137645%\"\u003e\n \u003cp\u003e49\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.7893864013267%\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.588723051409618%\"\u003e\n \u003cp\u003e0.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.925373134328359%\"\u003e\n \u003cp\u003eBoycott KM\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.22719734660033%\"\u003e\n \u003cp\u003eAM J HUM GENET\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"30.182421227197345%\"\u003e\n \u003cp\u003e10.1016/j.ajhg.2017.04.003\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"9.286898839137645%\"\u003e\n \u003cp\u003e45\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.7893864013267%\"\u003e\n \u003cp\u003e5.89\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.588723051409618%\"\u003e\n \u003cp\u003e0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.925373134328359%\"\u003e\n \u003cp\u003eLandrum MJ\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.22719734660033%\"\u003e\n \u003cp\u003eNUCLEIC ACIDS RES\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"30.182421227197345%\"\u003e\n \u003cp\u003e10.1093/nar/gkx1153\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"9.286898839137645%\"\u003e\n \u003cp\u003e43\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.7893864013267%\"\u003e\n \u003cp\u003e17.32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.588723051409618%\"\u003e\n \u003cp\u003e0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.925373134328359%\"\u003e\n \u003cp\u003eBoycott KM\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.22719734660033%\"\u003e\n \u003cp\u003eNAT REV GENET\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"30.182421227197345%\"\u003e\n \u003cp\u003e10.1038/nrg3555\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"9.286898839137645%\"\u003e\n \u003cp\u003e43\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.7893864013267%\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.588723051409618%\"\u003e\n \u003cp\u003e0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.925373134328359%\"\u003e\n \u003cp\u003eRentzsch P\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.22719734660033%\"\u003e\n \u003cp\u003eNUCLEIC ACIDS RES\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"30.182421227197345%\"\u003e\n \u003cp\u003e10.1093/nar/gky1016\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003ch2\u003eTable 7 The top 15 cited references with the\u0026nbsp;strongest citation bursts.\u003c/h2\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"9.417040358744394%\"\u003e\n \u003cp\u003e\u003cem\u003eFreq\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.434977578475337%\"\u003e\n \u003cp\u003e\u003cem\u003eBurst\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.919282511210762%\"\u003e\n \u003cp\u003e\u003cem\u003eCentrality\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.233183856502244%\"\u003e\n \u003cp\u003e\u003cem\u003eAuthor\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"36.99551569506726%\"\u003e\n \u003cp\u003e\u003cem\u003eSource\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"9.417040358744394%\"\u003e\n \u003cp\u003e110\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.434977578475337%\"\u003e\n \u003cp\u003e34.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.919282511210762%\"\u003e\n \u003cp\u003e0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.233183856502244%\"\u003e\n \u003cp\u003eRichards S\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"36.99551569506726%\"\u003e\n \u003cp\u003eGENET MED\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"9.417040358744394%\"\u003e\n \u003cp\u003e170\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.434977578475337%\"\u003e\n \u003cp\u003e28.18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.919282511210762%\"\u003e\n \u003cp\u003e0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.233183856502244%\"\u003e\n \u003cp\u003eWakap SN\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"36.99551569506726%\"\u003e\n \u003cp\u003eEUR J HUM GENET\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"9.417040358744394%\"\u003e\n \u003cp\u003e83\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.434977578475337%\"\u003e\n \u003cp\u003e20.45\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.919282511210762%\"\u003e\n \u003cp\u003e0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.233183856502244%\"\u003e\n \u003cp\u003eLek M\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"36.99551569506726%\"\u003e\n \u003cp\u003eNATURE\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"9.417040358744394%\"\u003e\n \u003cp\u003e43\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.434977578475337%\"\u003e\n \u003cp\u003e17.32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.919282511210762%\"\u003e\n \u003cp\u003e0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.233183856502244%\"\u003e\n \u003cp\u003eBoycott KM\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"36.99551569506726%\"\u003e\n \u003cp\u003eNAT REV GENET\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"9.417040358744394%\"\u003e\n \u003cp\u003e86\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.434977578475337%\"\u003e\n \u003cp\u003e13.74\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.919282511210762%\"\u003e\n \u003cp\u003e0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.233183856502244%\"\u003e\n \u003cp\u003eKarczewski KJ\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"36.99551569506726%\"\u003e\n \u003cp\u003eNATURE\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"9.417040358744394%\"\u003e\n \u003cp\u003e31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.434977578475337%\"\u003e\n \u003cp\u003e11.89\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.919282511210762%\"\u003e\n \u003cp\u003e0.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.233183856502244%\"\u003e\n \u003cp\u003eKircher M\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"36.99551569506726%\"\u003e\n \u003cp\u003eNAT GENET\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"9.417040358744394%\"\u003e\n \u003cp\u003e26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.434977578475337%\"\u003e\n \u003cp\u003e10.43\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.919282511210762%\"\u003e\n \u003cp\u003e0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.233183856502244%\"\u003e\n \u003cp\u003eK\u0026ouml;hler S\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"36.99551569506726%\"\u003e\n \u003cp\u003eNUCLEIC ACIDS RES\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"9.417040358744394%\"\u003e\n \u003cp\u003e35\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.434977578475337%\"\u003e\n \u003cp\u003e10.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.919282511210762%\"\u003e\n \u003cp\u003e0.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.233183856502244%\"\u003e\n \u003cp\u003eRichter T\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"36.99551569506726%\"\u003e\n \u003cp\u003eVALUE HEALTH\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"9.417040358744394%\"\u003e\n \u003cp\u003e23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.434977578475337%\"\u003e\n \u003cp\u003e9.91\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.919282511210762%\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.233183856502244%\"\u003e\n \u003cp\u003ePage MJ\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"36.99551569506726%\"\u003e\n \u003cp\u003ePLOS MED\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"9.417040358744394%\"\u003e\n \u003cp\u003e58\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.434977578475337%\"\u003e\n \u003cp\u003e9.74\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.919282511210762%\"\u003e\n \u003cp\u003e0.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.233183856502244%\"\u003e\n \u003cp\u003eFerreira CR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"36.99551569506726%\"\u003e\n \u003cp\u003eAM J MED GENET A\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"9.417040358744394%\"\u003e\n \u003cp\u003e34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.434977578475337%\"\u003e\n \u003cp\u003e9.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.919282511210762%\"\u003e\n \u003cp\u003e0.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.233183856502244%\"\u003e\n \u003cp\u003eK\u0026ouml;hler S\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"36.99551569506726%\"\u003e\n \u003cp\u003eNUCLEIC ACIDS RES\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"9.417040358744394%\"\u003e\n \u003cp\u003e34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.434977578475337%\"\u003e\n \u003cp\u003e9.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.919282511210762%\"\u003e\n \u003cp\u003e0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.233183856502244%\"\u003e\n \u003cp\u003ePhilippakis AA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"36.99551569506726%\"\u003e\n \u003cp\u003eHUM MUTAT\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"9.417040358744394%\"\u003e\n \u003cp\u003e32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.434977578475337%\"\u003e\n \u003cp\u003e9.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.919282511210762%\"\u003e\n \u003cp\u003e0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.233183856502244%\"\u003e\n \u003cp\u003eZurynski Y\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"36.99551569506726%\"\u003e\n \u003cp\u003eORPHANET J RARE DIS\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"9.417040358744394%\"\u003e\n \u003cp\u003e21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.434977578475337%\"\u003e\n \u003cp\u003e8.42\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.919282511210762%\"\u003e\n \u003cp\u003e0.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.233183856502244%\"\u003e\n \u003cp\u003eGirdea M\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"36.99551569506726%\"\u003e\n \u003cp\u003eHUM MUTAT\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"9.417040358744394%\"\u003e\n \u003cp\u003e21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.434977578475337%\"\u003e\n \u003cp\u003e8.42\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.919282511210762%\"\u003e\n \u003cp\u003e0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.233183856502244%\"\u003e\n \u003cp\u003eYang YP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"36.99551569506726%\"\u003e\n \u003cp\u003eNEW ENGL J MED\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003ch2\u003eTable 8 \u0026nbsp;The top 4 cited references with the highest Centrality.\u003c/h5\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"99%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e\u003cem\u003eFreq\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.34020618556701%\"\u003e\n \u003cp\u003e\u003cem\u003eBurst\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.463917525773196%\"\u003e\n \u003cp\u003e\u003cem\u003eCentrality\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.49484536082474%\"\u003e\n \u003cp\u003e\u003cem\u003eAuthor\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.556701030927837%\"\u003e\n \u003cp\u003e\u003cem\u003eSource\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"29.896907216494846%\"\u003e\n \u003cp\u003e\u003cem\u003eDOI\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.34020618556701%\"\u003e\n \u003cp\u003e3.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.463917525773196%\"\u003e\n \u003cp\u003e0.11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.49484536082474%\"\u003e\n \u003cp\u003eBenson MD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.556701030927837%\"\u003e\n \u003cp\u003eNEW ENGL J MED\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"29.896907216494846%\"\u003e\n \u003cp\u003e10.1056/NEJMoa1716793\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.34020618556701%\"\u003e\n \u003cp\u003e6.73\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.463917525773196%\"\u003e\n \u003cp\u003e0.09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.49484536082474%\"\u003e\n \u003cp\u003eBamshad MJ\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.556701030927837%\"\u003e\n \u003cp\u003eNAT REV GENET\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"29.896907216494846%\"\u003e\n \u003cp\u003e10.1038/nrg3031\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.34020618556701%\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.463917525773196%\"\u003e\n \u003cp\u003e0.09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.49484536082474%\"\u003e\n \u003cp\u003eGurovich Y\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.556701030927837%\"\u003e\n \u003cp\u003eNAT MED\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"29.896907216494846%\"\u003e\n \u003cp\u003e10.1038/s41591-018-0279-0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.34020618556701%\"\u003e\n \u003cp\u003e8.42\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.463917525773196%\"\u003e\n \u003cp\u003e0.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.49484536082474%\"\u003e\n \u003cp\u003eGirdea M\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.556701030927837%\"\u003e\n \u003cp\u003eHUM MUTAT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"29.896907216494846%\"\u003e\n \u003cp\u003e10.1002/humu.22347\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Rare diseases, Orphan diseases, Visualization, Knowledge graph, CiteSpace","lastPublishedDoi":"10.21203/rs.3.rs-4451685/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4451685/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eObjective\u003c/h2\u003e \u003cp\u003eHere, we analyzed the research status of rare diseases in China and globally over the past decade using bibliometric and scientific knowledge graph methods. We aimed to understand research trends, determine frontier topics, and explore the developments in and the differences between research conducted in China and the rest of the world.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eWe focused on rare disease literature indexed in the Web of Science and CNKI databases from January 2013 to December 2023. We selected studies based on inclusion and exclusion criteria. Bibliometric methods and the CiteSpace 6.1.R6 software were used to prepare knowledge graphs and perform comparative analyses of authors, institutions, content, and hot topics between Chinese and English databases.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eA total of 10,754 articles from the Web of Science database and 969 articles from the CNKI database met the inclusion criteria. In the past 10 years, the diagnosis and treatment of rare diseases have been a common research focus in both China and foreign countries. However, China has emphasized more on \"orphan drugs,\" whereas foreign countries have focused more on \"genes\" and \"management.\" The United States had the greatest number of publications. However, China ranks high in terms of publication volume and institutional ranking.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eThe research interest in rare diseases has gradually increased worldwide, with European and American countries maintaining a leading position. China has made significant contributions to rare disease research. However, its research focus is lagging compared to international trends, and a lack of collaboration with foreign countries exists. The diagnosis and treatment of rare diseases remain central themes in the field, whereas genetic research, artificial intelligence intervention, and sociological studies on rare disease populations are emerging as hot topics.\u003c/p\u003e","manuscriptTitle":"Rare disease publishing trends worldwide and in China: a citespace-based bibliometric study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-06-28 20:07:51","doi":"10.21203/rs.3.rs-4451685/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"85243414-8225-499c-8d56-bf50fc7df008","owner":[],"postedDate":"June 28th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2024-09-23T09:14:26+00:00","versionOfRecord":[],"versionCreatedAt":"2024-06-28 20:07:51","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-4451685","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4451685","identity":"rs-4451685","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}