Knowledge Mapping of liver metastases from colonrectal cazncer: A bibliometric analysis (2018–2024) and reflections

Knowledge Mapping of liver metastases from colonrectal cazncer: A bibliometric analysis (2018–2024) and reflections | 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 Knowledge Mapping of liver metastases from colonrectal cazncer: A bibliometric analysis (2018–2024) and reflections Xusheng Zhang, Bendong Chen, Wenyan Zhou, Yongxin Ma, Qi Wang This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6792171/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 Background liver metastases from colonrectal cazncer is a significant source of secondary liver malignancies. Considerable progress has been made in its diagnosis and treatment over the years. However, no recent bibliometric analysis has been identified on this topic. The present study aims to comprehensively elucidate the knowledge structure and research status related to liver metastasis in colorectal cancer using bibliometric methods. Methods Utilizing the Web of Science Core Collection (WoSCC) database, a systematic literature search was performed for publications concerning liver metastasis in colorectal cancer from 2018 to 2024. Analyses were carried out using VOSviewer, CiteSpace software, and the R package "bibliometrix" to facilitate the relevant assessments. Results The analysis encompassed 6,340 articles distributed across 538 countries/regions. Findings revealed a consistent annual increase in the volume of publications addressing liver metastasis in colorectal cancer. Among the top research institutions were Sun Yat-sen University and Fudan University. The journal " Cancers " and " Annals of Surgery " emerged as the most prominent publication outlet in this domain, also being the most frequently co-cited journal. The body of research was produced by 37,041 authors, with JN Vauther, C Verhoef, and Y Wang identified as the top three influential authors in the context of liver metastasis in colorectal cancer. Moreover, Fong Y, Jemal A, and Van Cutsem E were recognized for having the highest citation counts. A timeline visualization of keywords by frequency indicated that "chemotherapy" stands out as the most critical topic within this research area. Additional emerging trends included "tumor metastasis", "pharmacokinetics", and "metastatic rectal cancer". Conclusion This investigation represents the inaugural comprehensive bibliometric analysis summarizing the research trajectories and advancements in liver metastasis associated with colorectal cancer. The insights derived from this study delineate the current research frontiers and trending topics, thereby serving as a valuable resource for future investigations within the realm of liver metastasis in colorectal cancer, although limiting the analysis to studies indexed in WoSCC may introduce bias into the results Bibliometrics Colorectal cancer Liver metastasis CiteSpace VOSviewers Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Introduction Colorectal cancer (CRC) is one of the most prevalent malignant tumors of the digestive system. In recent years, while the incidence and mortality rates of CRC in the United States have declined, there has been a contrary and significant increase in both mortality and incidence rates within the domestic population. CRC remains the second leading cause of cancer-related deaths worldwide[ 1 , 2 ]. The liver, due to its unique blood supply and anatomical structure[ 3 ], is the most common site of metastasis for various gastrointestinal cancers, including CRC[ 4 ]. Tumor metastasis is a major cause of poor prognosis and death. CRC is characterized by high incidence, high metastatic potential, and delayed diagnosis. For patients with early-stage CRC, the 5-year survival rate can reach up to 90%, but once distant metastasis occurs, the 5-year survival rate plummets to less than 20%[ 5 ]. Patients with colorectal cancer liver metastasis (CRCLM) are often diagnosed too late for surgical intervention, and treatment primarily relies on chemotherapy and integrated therapy[ 6 , 7 ]. Despite advancements and optimizations in chemotherapy regimens, the side effects and toxicities faced by patients undergoing chemotherapy remain a significant challenge and a leading cause of treatment discontinuation[ 8 ]. However, as of now, research literature and data on the pathogenesis, diagnosis, and treatment of colorectal cancer liver metastasis (CRCLM) are not systematic. There is an urgent need for more effective early diagnostic methods and safer, more efficacious treatment protocols. Bibliometrics focuses on the quantification of a complete body of knowledge. By analyzing existing quantitative literature and utilizing visual maps, it analyzes the current state of research, predicts the trajectory of a research field, and systematically summarizes the research progress of countries, institutions, authors, and disciplines[ 9 ]. This article aims to conduct a thorough and objective analysis of bibliometric indicators related to colorectal liver metastasis, elucidate the development trends, hotspots, and directions of research in colorectal liver metastasis, and assist researchers in more accurately and keenly grasping the research directions in this field. It also aims to build upon past achievements and accurately identify future prospective research hotspots, contributing more to the diagnosis and treatment of colorectal liver metastasis[ 10 ]. Materials and methods 1. Search strategy All retrieved data were sourced from the Web of Science Core Collection (WoSCC), employing the following search strategy: TS = (“colorectal cancer”) AND (“liver metastases” OR “liver metastasis”) OR TS = (“liver metastases” from colorectal cancer) AND publication years = (2018–2024) AND document types = (articles & reviews) AND language = (English). This process was conducted independently by two senior researchers (Qi Wang and Bendong Chen) to ensure relevance to the study's theme and to guarantee the accuracy of the retrieval process. A flowchart of the study's process is depicted in Fig. 1 . All publication records, including publication year, title, author names, affiliations, countries/regions, abstracts, keywords, and journal names, were exported and saved as plain text files, encompassing "full records and cited references". The size and color of the nodes represent the quantity and categorization of these items, respectively. The thickness of the lines between nodes reflects the degree of collaboration or co-citation of these items. 2. Analysis tools VOSviewer (version 1.6.20) is a software tool for constructing and visualizing bibliometric networks. This study utilizes VOSviewer to extract important terms and to construct and visualize the co-occurrence networks of these terms. CiteSpace (version 6.1. R1), developed by Professor Chen C, is a software tool utilized for bibliometric analysis and visualization[ 11 ]. In our study, it was employed for Citation Bursts analysis. The R package "bibliometrix" (version 3.2.1) ( https://www.bibliometrix.org ) was used for thematic evolution analysis and to construct a global distribution network of colorectal cancer liver metastasis publications. Additionally, Microsoft Office Excel 2021 was employed for quantitative analysis of the publications. Results 1. Analysis of countries/regions Initially, the study analyzed the number of publications from each country to identify the leading contributors in the field. A total of 25,479 institutions and 37,041 researchers from 538 countries/regions participated in CRCLM research. Based on the country of residence of the corresponding authors, the publication and citation metrics of the top 25 most productive countries/regions were analyzed (Table 1 ). The analysis revealed an increasing trend in the annual number of publications related to CRCLM from 2018 to 2024. Due to the fact that the literature for 2024 was only retrieved up to October 24, there was a noticeable decrease in the number of publications for 2024. Conversely, the annual citation rate showed a declining trend (Fig. 2 ). Subsequently, an analysis of the publication output of the top five countries with the highest cumulative number of publications from 2018 to 2024 was conducted, demonstrating a steady upward trend in cumulative publication output for China, the United States, France, Japan, and Italy (Fig. 3 . A). China published the highest number of articles (1,871, accounting for 29.5%, with multiple country publications accounting(MCP) for approximately 6.9%). It was followed by the United States (926, accounting for 14.6% of total publications, with MCP accounting for approximately 27.8%), and Japan ranked third (583, accounting for 9.2% of total publications, with MCP accounting for approximately 6.0%) (Fig. 3 A). Additionally, China ranked first with 28,749 citations, the United States ranked second with 17,861 citations, and Japan ranked third with 6,566 citations (Fig. 3 . B). This indicates that China, the United States, and Japan are the most significant contributors in this field, with the total number of publications from these three countries exceeding half of the total number of publications. A network visualization of the countries where the authors are based is depicted, with the size of the circles representing the number of publications, excluding countries with fewer than 5 publications (Fig. 3 . C). A geographical map of the number of publications and collaboration intensity for each country is shown (Fig. 3 . D). Furthermore, the analysis found that although Belgium published only 54 CRCLM articles, its MCP% was as high as 51.9%, making it the country with the highest proportion of international collaboration. While the United States had an MCP% of only 27.8%, its large base of publication output made it the country initiating and participating in the most international collaborations. Table 1 Top 25 most productive countries/regions in CRCLM research Rank Country Article N, % SCP MCP MCP % TC AC 1 China 1871 29.5 1741 130 6.9 28749 15.4 2 United States 926 14.6 669 257 27.8 17861 19.3 3 Japanese 583 9.2 548 35 6.0 6566 11.3 4 Italy 339 5.3 266 73 21.5 4934 14.6 5 Germany 325 5.1 216 109 33.5 5296 16.3 6 France 226 3.6 168 58 25.7 3268 14.5 7 Netherlands 218 3.4 135 83 38.1 4015 18.4 8 United Kingdom 186 2.9 99 87 46.8 3632 19.5 9 Spain 167 2.6 126 41 24.6 4011 24.0 10 Korea 166 2.6 147 19 11.4 1664 10.0 11 Canada 134 2.1 79 55 41.0 1733 12.9 12 Australia 99 1.6 68 31 31.3 1460 14.7 13 Norway 74 1.2 54 20 27.0 1837 24.8 14 Sweden 64 1.0 48 16 25.0 1287 20.1 15 Iran 59 0.9 35 24 40.7 784 13.3 16 Turkey 57 0.9 54 3 5.3 374 6.6 17 Austria 56 0.9 30 26 46.4 802 14.3 18 Belgium 54 0.9 26 28 51.9 741 13.7 19 Brazil 53 0.8 36 17 32.1 399 7.5 20 India 45 0.7 35 10 22.2 344 7.6 21 Popand 45 0.7 31 14 31.1 493 11.0 22 Switzerland 44 0.7 24 20 45.5 971 22.1 23 Denmark 36 0.6 30 6 16.7 426 11.8 24 Greece 34 0.5 18 16 47.1 286 8.4 25 Singapore 34 0.5 24 10 29.4 608 17.9 SCP: Single Country Publications; MCP: Multiple Country Publications; MCP% = MCP/ Articles; TC: Total citations; AC: Average citations. 2. Analysis of institutions Table 2 presents the top 10 universities with the highest number of published papers, with 2 institutions from China and 3 from the United States. Sun Yat-sen University had the highest number of publications (9.5%), followed by Fudan University (6.6%) and Memorial Sloan Kettering Cancer Center (6.3%). The collaboration network among these institutions is visualized in Fig. 4 . A (where the size of the circles represents the number of publications). The publication output of each institution is visualized in Fig. 4 . B. Table 2 Top 10 most productive institutions in CRCML research Rank Affiliation Country Articles n, % 1 Sun yat-sen university China 600 9.5 2 Fudan university China 416 6.6 3 Memorial Sloan Kettering Cancer Center United States 401 6.3 4 University of Oslo Norway 387 6.1 5 Assistance publique hopitaux paris (APHP) France 371 5.9 6 Universite paris cite France 347 5.5 7 Unicancer France 337 5.3 8 University of Texas System United States 320 5.0 9 Berlin institute of health Germany 290 4.6 10 Utmd Anderson Cancer Center United States 264 4.2 3. Journal distribution Analysis of the results revealed that a total of 1062 journals contributed to the publication of articles on colorectal cancer liver metastasis (CRCLM). Table 3 displays the top 10 journals with the highest number of CRCLM-related articles. The journal " Cancers " from Switzerland published the most articles related to CRCLM and also had the highest total citation count (TC); followed by " Annals of Surgery " from the United States, which published the second-highest number of relevant articles and had the second-highest total citation count, only behind " Cancers ". Bradford's law was applied to analyze the core journals within the subject matter of the included journals, and the distribution of these core journals is shown in Fig. 5 . A. The cumulative annual publication trend of the top five journals is depicted in Fig. 5 . B, showing a stable upward trend, with " Cancers " having the highest cumulative number of related literature over the years. The H-index was used to assess the impact of each journal on CRCLM, and it was found that " Cancers " led with an H-index of 28; " Annals of Surgery " was in second place with an H-index of 22; and " Cell Death & Disease " was in third place with an H-index of 20, indicating that these three journals play a significant role in the field of CRCLM research (Fig. 5 . C). Subsequently, we analyzed the interactions between relevant journals in this field, and the results are shown in Fig. 5 . D, where " Cancers " is visibly the most interconnected with other journals in recent years. Citation bursts refer to content that scholars in a particular field frequently cite over a period. In our study, CiteSpace identified five journals with strong citation bursts, arranged in chronological order (Fig. 5 E). It is evident that " Cancers ", " Frontiers in Oncology " and " Scientific Reports " rank as the top three journals of citation bursts in 2024 with the strongest relevance. In the literature coupling analysis, we also found that " Cancers " was widely cited as the most significant contributing journal to the CRCLM topic (Fig. 5 . F). Table 3 Local impact on CRCLM of Journal Rank Journal Region IF Articles H_index TC 1 Cancers Switzerland 4.5 267 28 2856 2 Annals of surgery United states 7.5 45 22 2622 3 Cell death & disease United kingdom 8.1 36 20 1129 4 Ejso United kingdom 3.5 117 20 1468 5 International journal of molecular sciences United states 4.9 68 20 2491 6 Annals of surgical oncology United states 3.4 129 19 1375 7 Bmc cancer United kingdom 3.8 80 18 1805 8 Frontiers in oncology Switzerland 3.5 181 18 1466 9 Journal of experimental & clinical cancer research Italy 11.4 32 18 933 10 Journal of surgical oncology United states 2 102 18 1073 TC: Total citation. 4. Analysis of authors A total of 37,041 authors contributed to the publication of research papers related to CRCLM, with 1,282 scholars publishing 5 or more articles on CRCLM, and 287 authors publishing 10 or more articles. The co-authorship network in CRCLM research is depicted in Fig. 6 . A. The most relevant authors in terms of CRCLM are shown in Fig. 6 . B, where Verhoef C and Wang Y published the highest number of articles, with 74 each. In terms of citation metrics, Vauthey JN emerged as the most cited author with 924 citations, followed by Pawlik TM, and D'Angelica MI ranked third (Fig. 6 . C). The top 18 authors in citation bursts are illustrated in Fig. 6 . D. 5. Keywords and trends Figure 7 . A illustrates that "properative chemotherapy", "surgical resection", "invasion", "prognostic factors", "colorectal neoplasms", "thermal ablation", and "proliferation" are the seven most explosively cited keywords related to CRCLM from 2018 to 2014, which to some extent represent the research hotspots in this field during that period. In the cumulative temporal frequency analysis of keywords, "colorectal cancer", "liver metastasis", "metastasis", "chemotherapy", and "prognosis" rank in the top five, representing the research focal points in the field during the analyzed time frame. An analysis of the cumulative frequency of the top ten keywords over time shows a stable increasing trend for all top keywords, with "chemotherapy" significantly outpacing others, suggesting that chemotherapy may be a particularly hot topic in this field (Fig. 7 . B). The top seven keywords in the most relevant Citation Bursts are shown in Fig. 7 . C. Additionally, we analyzed the evolution of CRCLM-related topics over time. The topic "tumor metastasis" has remained a hot topic from 2021 to the present; "pharmacokinetics" has been a popular topic since 2020 and continues to the present; "metastatic rectal cancer" emerged as the latest high-frequency topic in 2024, potentially indicating the newest research trend; the core topics of this study, "colorectal cancer" and "liver metastasis", have been high-frequency keywords since 2020 and continued through 2023 (Fig. 7 . D). 6. Document citation and reference co-citation analysis We sorted the included papers based on citation data from the WoSCC. There were 775 articles with a citation count of 30 or more; 507 articles with a citation count of 40 or more; and 359 articles with a citation count of 50 or more. The network graph of the corresponding citation files is shown in Fig. 8 . A, with the papers by Tauriello(2018), Hashiguchi (2020), Argilés (2020), Zeng (2018) and Chi (2019) ranking in the top five. In terms of cited references, the document Fong Y_1999_Ann Surg_v230 leads with 742 citations and a total link strength of 8225; Jemal A_2011_CA-Cancer J Clin_v61 is second with 739 citations and a total link strength of 3953; and Van Cutsem E_2016_Ann Oncol_v27 is third with 660 citations and a total link strength of 6812 (Fig. 8 . B, see Supplementary Material for Table S1 ). The top 20 most frequently cited documents in citation bursts are shown in Fig. 8 . C. Additionally, this study utilized a tri-field map to explore the main keywords, authors, and their affiliated institutions, as depicted in Fig. 8 . D. Discussion Individuals diagnosed with colorectal cancer liver metastasis (CRCLM) are confronted with elevated mortality figures and unfavorable prognoses, presenting significant obstacles in clinical diagnosis and therapeutic interventions[ 12 ]. In recent decades, the corpus of research focused on CRCLM has significantly expanded. Bibliometrics recognized as a progressive analytical approach, is extensively employed to evaluate the contemporary landscape and evolving trends within a research domain[ 13 ]. This article undertakes a thorough bibliometric analysis of CRCLM-related literature sourced from the WoSCC spanning from 2018 to 2024, thereby offering a valuable reference for CRCLM researchers to accurately discern the developmental trajectories and emerging focal points of inquiry in this area. In this study, we utilized VOSviewer, CiteSpace, and the "bibliometrix" package in R to investigate the research dynamics and hotspots in the clinical science index (CSI) expansion for CRCLM. A total of 6,340 papers on the topic were retrieved from the WoSCC, covering a period from January 1, 2018, to October 24, 2024. In our analysis, we observed a stable upward trend in the number of papers published annually worldwide related to CRCLM. The cumulative temporal curve of the literature over the years also shows a consistent increase, which aligns with the global increasing trend of CRCLM. Chinese researchers are the largest contributors in the field of CRCLM research, with both the volume of publications and the number of citations ranking first globally. Among the top ten most prolific institutions, two are from China, including Fudan University and Sun Yat-sen University, with Sun Yat-sen University leading the world in publication volume. This indicates that China has made a significant contribution to the topic of CRCLM. However, despite China's total research output and citation data being far higher than other countries, the proportion of international collaboration in China is only 6.9%, while the United States leads with a 27.8% share of Multinational Collaborative Publications (MCP), indicating that American researchers have made greater efforts in international cooperation. This suggests that Chinese researchers should pay more attention to MCP, enhance international exchanges, and gain more international recognition and influence. Furthermore, although the total number of citations for Chinese publications ranks first, the average citation rate per Chinese publication is only 15.4. Given the large base of publications, this does not offer any advantage compared to other countries. This indicates that the quality (reader recognition) of some domestic publications is not high, suggesting that researchers should focus on controlling the quality of research outcomes to gain more recognition from peers in the same field. In the journal analysis, it was found that articles related to CRCLM are most frequently published in the journal Cancers , followed by Annals of Surgery and Cell Death & Disease . Cancers is one of the high-quality, influential journals in the field of oncology, with an impact factor of 4.5, and the analysis also indicates that Cancers is the most cited journal. Additionally, the Journal of Experimental & Clinical Cancer Research , ranking 9th in publication volume and with an impact factor of 11.4, emerges as the journal with the highest impact factor related to the CRCLM theme. The aforementioned journals may become significant publishing institutions in this field in the future. The seven most explosive citation keywords related to CRCLM from 2018 to 2024 are properative chemotherapy, surgical resection, invasion, prognostic factors, colorectal neoplasms, thermal ablation, and proliferation. These keywords represent the research hotspots in this field during this period. They cover treatment methods, prognosis, and mechanisms of CRCLM, indicating that the main focus of this research remains within the mainstream scope without reflecting many innovative contents or new perspectives. Based on the trend analysis of thematic summaries and keyword trends, the latest high-frequency trending topics are "tumor metastasis", "pharmacokinetics", and "metastatic rectal cancer". These represent the research trends and frontiers in the field of CRCLM. We have observed that the latest research trend topics do not introduce novel directions; apart from "pharmacokinetics", the other two merely describe the topic of disease metastasis and have persisted for a considerable duration. This may, to some extent, reflect a stagnation in breakthroughs and slow updates in CRCLM research, indicating a need for more innovative content and expansion of new perspectives. In colorectal cancer (CRC), the liver is the most common site of distant metastasis, with approximately half of CRC patients developing liver metastasis during the course of their disease. The primary treatment for CRCLM is complete hepatectomy, with a 5-year overall survival rate reaching nearly 60%[ 14 ]. However, no more than 20% of patients with CRCLM present with surgical indications at their initial visit[ 15 ]. The remaining patients can only be treated through other means, and for those with unresectable disease, even with the best chemotherapy regimens, the median survival rate remains low[ 16 ]. Studies have explored the use of immune checkpoint inhibitors (ICIs) in liver metastasis, with results showing that liver metastasis is not sensitive to ICIs[ 17 ]. Local regional therapy can cause irreversible damage to tumor cells and release tumor antigens, providing a theoretical basis for immunotherapy of liver metastasis. Therefore, researchers believe that the combination therapy of ICIs and local regional therapy is a promising option[ 18 ]. We have also noticed that "pharmacokinetics" is one of the latest trending topics. Since the vast majority of CRCLM cases are not candidates for surgery, chemotherapy has become prevalent, and the rise of this topic may be accompanied by the application of chemotherapy and other drug treatments, indicating that researchers may start to pay more attention to the safety and rationality of patient medication during chemotherapy, which is an indication of precision diagnosis and treatment. In the latest literature, nanomedicines composed of polymers, lipids, and inorganic nanoparticles are emerging and may replace traditional chemotherapy drugs because nanomedicines can effectively avoid side effects due to polytherapy[ 19 ]. The body of literature collectively cited refers to documents that are cited by multiple other publications, thereby considering the collectively cited documents as the research foundation of a particular field. In this analysis, we examined the most frequently cited collectively cited documents to identify the research foundation of CRCLM. The most cited document is by Fong et al., published in the Annals of Surgery in 1999. This study confirmed a 5-year survival rate of 37% and a 10-year survival rate of 22% for CRCLM patients through a continuous analysis of 1001 cases of colorectal liver metastasis. It was also found that positive resection margins, extrahepatic disease, positive lymph nodes in the primary tumor, a time interval of less than 12 months from the primary tumor to metastasis, more than one liver tumor, the largest liver tumor diameter exceeding 5 cm, and carcinoembryonic antigen levels exceeding 200 ng/ml are significant risk factors for CRCLM, laying an important foundation for the surgical treatment of CRCLM[ 20 ]. Additionally, we noted that Jemal A et al.'s Cancer Statistics, 2010 , published in 2011, ranks second in the list of cited documents. Although the article has a high impact factor of 503 points, the content described is relatively time-sensitive and dates back 14 years[ 21 ], making the high frequency of citation for this document somewhat puzzling. In addition, a bibliometric overview of the current state of CRCLM research reveals that studies on the pathogenesis of CRCLM do not seem to be reflected in this research, suggesting that such studies are either scarce or still in a very early stage. This may be a direction where researchers need to invest more effort. Furthermore, the topic of CRCLM diagnosis and treatment shows a sluggish pace, with research trends and high-frequency keywords indicating that there have been no revolutionary advances in recent years, and the topics of interest among researchers remain relatively conservative. The limitations of this study primarily stem from the reliance on a single database, WoSCC. A single database is prone to issues such as regional coverage bias, language bias, and metadata quality problems[ 22 – 24 ]. This suggests that the interpretation of the results of this analysis should be more cautious. Future studies could employ a more comprehensive approach by integrating multiple databases to avoid these biases, thereby providing a more objective conclusion. Conclusion The study employed bibliometric methods to reveal the current state and trends in CRCLM research, providing valuable guidance for researchers in understanding the research landscape of this field. There should be an increased emphasis on international collaboration in CRCLM research. Our research offers valuable insights for understanding and addressing CRCLM, laying the foundation for more in-depth studies and the discovery of more effective treatment methods. Further research should focus on the pathogenesis of CRCLM, early diagnosis, and personalized treatment to improve patient survival and quality of life. Declarations Data availability statement We retrieved and downloaded data related to liver cancer and liver metastasis of colorectal cancer from the Web of Science Core Collection. These data are publicly accessible. Our use of the data complies with the guidelines of the database, and the data have been submitted as required (Supplementary Material 1). Ethics and consent to Participate Not applicable. Consent to publish declarations All authors agree to the publication of this article. Clinical trial number Not applicable. Author contributions Xusheng Zhang: Investigation, Methodology, Writing original draft, Writing & editing, Software, Writing review & editing. Bendong Chen: Investigation, Methodology, Writing original draft, Writing & editing, Software, Writing review & editing. Wenyan Zhou: Investigation, Methodology, Software, Writing original draft, Writing review & editing. Yongxin Ma: Methodology, Supervision, Visualization, Writing review & editing. Qi Wang: Methodology, Supervision, Visualization, Writing review & editing Funding This study was supported by the project "Central Guidance for Local Science and Technology Development Special Project", project number: 2024FRD05060. 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. Publisher’s note All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher. 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Jemal A, Siegel R, Xu J, Ward E: Cancer statistics, 2010 . CA-CANCER J CLIN 2010, 60 (5):277-300. Liu W: The data source of this study is Web of Science Core Collection? Not enough . SCIENTOMETRICS 2019, 121 (3):1815-1824. Missing author address information in Web of Science — An explorative study . Liu W: The changing role of non-English papers in scholarly communication: Evidence from Web of Science's three journal citation indexes . LEARN PUBL 2017, 30 (2):115-123. Additional Declarations No competing interests reported. Supplementary Files TableS1.docx SupplementaryMaterial1.txt 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. 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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-6792171","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":473133880,"identity":"82d1cd15-bba6-4534-8e9e-8af1fb69c04a","order_by":0,"name":"Xusheng Zhang","email":"","orcid":"","institution":"Ningxia Medical University","correspondingAuthor":false,"prefix":"","firstName":"Xusheng","middleName":"","lastName":"Zhang","suffix":""},{"id":473133881,"identity":"2c2b8464-0cf3-4ff2-8cd1-68f568a4fc71","order_by":1,"name":"Bendong Chen","email":"","orcid":"","institution":"General Hospital of Ningxia Medical University","correspondingAuthor":false,"prefix":"","firstName":"Bendong","middleName":"","lastName":"Chen","suffix":""},{"id":473133882,"identity":"b5e97895-7ef3-4a9a-83b5-0f08f1250573","order_by":2,"name":"Wenyan Zhou","email":"","orcid":"","institution":"General Hospital of Ningxia Medical University","correspondingAuthor":false,"prefix":"","firstName":"Wenyan","middleName":"","lastName":"Zhou","suffix":""},{"id":473133884,"identity":"b1a8caf8-44bb-4bf3-b4b4-966d73ed48df","order_by":3,"name":"Yongxin Ma","email":"","orcid":"","institution":"Ningxia Medical University","correspondingAuthor":false,"prefix":"","firstName":"Yongxin","middleName":"","lastName":"Ma","suffix":""},{"id":473133885,"identity":"643b339f-9e00-49bc-95c4-b51c88deae63","order_by":4,"name":"Qi Wang","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAvElEQVRIiWNgGAWjYHACxsc/Kmzk2NjbDxCthdmY4UyaMR/PmQSitbAJM7YcTpwn4WBAnHqD4wlszIUNzOltEgwJDD8qthGh5cwDtsczd7Dltkk3HmDsOXObsBazG/nfDXjP8OS2yRxIYGZsI0pLApsEb5tEOptEggHxWqR52wwSiNdif+YBs+GMMwmGbcBAPkiUXyTbExgffKj4Ly/f3n7wwY8KIrQwAIMWDg4Qox5VyygYBaNgFIwCrAAAEZo8o55/c0QAAAAASUVORK5CYII=","orcid":"","institution":"General Hospital of Ningxia Medical University","correspondingAuthor":true,"prefix":"","firstName":"Qi","middleName":"","lastName":"Wang","suffix":""}],"badges":[],"createdAt":"2025-05-31 16:53:08","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6792171/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6792171/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":85176125,"identity":"1865154e-321a-4ad2-9297-55719d66c936","added_by":"auto","created_at":"2025-06-23 06:35:03","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":443573,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eFlowchart of the study.\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"image1.png","url":"https://assets-eu.researchsquare.com/files/rs-6792171/v1/57b337d9679df90365120df7.png"},{"id":85175589,"identity":"6c517140-a06c-4daa-9b5a-821be5735c0e","added_by":"auto","created_at":"2025-06-23 06:27:03","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":206842,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eAnnual output of publications and average yearly article on CRCLM.\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"image2.png","url":"https://assets-eu.researchsquare.com/files/rs-6792171/v1/284ecc2755f26eeac071ed28.png"},{"id":85175591,"identity":"2045424b-fcc3-4dcf-bf2e-513598add30c","added_by":"auto","created_at":"2025-06-23 06:27:03","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":477273,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eVisualization and analysis of active countries/regions.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e(A) Temporal trends in country productivity;\u003c/p\u003e\n\u003cp\u003e(B) Top 20 countries of corresponding authors;\u003c/p\u003e\n\u003cp\u003e(C) Collaborator network map of countries/regions involved in CRCLM research;\u003c/p\u003e\n\u003cp\u003e(D)Intercountry collaboration network map.\u003c/p\u003e","description":"","filename":"image3.png","url":"https://assets-eu.researchsquare.com/files/rs-6792171/v1/e9c77f4bbfcfff67b7094896.png"},{"id":85175597,"identity":"deb7f6ac-9cc2-4555-ab26-61da3efd7c4f","added_by":"auto","created_at":"2025-06-23 06:27:03","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":406275,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eVisualization and analysis of active institutions.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e(A) Collaboration network map of institutions involved in CRCLM research;\u003c/p\u003e\n\u003cp\u003e(B) Top 20 relevant institutions.\u003c/p\u003e","description":"","filename":"image4.png","url":"https://assets-eu.researchsquare.com/files/rs-6792171/v1/e04f16e201c7311255bc5913.png"},{"id":85175593,"identity":"7f1aa613-2120-4f05-8a28-f6b67063e247","added_by":"auto","created_at":"2025-06-23 06:27:03","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":754582,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eVisualization and analysis of active journals.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e(A) Core Journals Identified by Bradford's Law;\u003c/p\u003e\n\u003cp\u003e(B) Cumulative publication volume over time;\u003c/p\u003e\n\u003cp\u003e(C) Assessment of journal impact in CRCLM based on H-Index;\u003c/p\u003e\n\u003cp\u003e(D) Interactive network map of CRCLM-related journals;\u003c/p\u003e\n\u003cp\u003e(E) Top 5 journals with citation bursts;\u003c/p\u003e\n\u003cp\u003e(F)Network map of bibliographic coupling journals.\u003c/p\u003e","description":"","filename":"image5.png","url":"https://assets-eu.researchsquare.com/files/rs-6792171/v1/750db96d59c6527572e9dcd5.png"},{"id":85175604,"identity":"6ab4fff9-551d-482a-b8e4-a5c17203be1f","added_by":"auto","created_at":"2025-06-23 06:27:03","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":747269,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eVisualize and analyze active authors.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e(A)Co-authorship network map of researchers involved in CRCLM research;\u003c/p\u003e\n\u003cp\u003e(B)Analysis of the most relevant authors;\u003c/p\u003e\n\u003cp\u003e(C)Analysis of the most cited authors;\u003c/p\u003e\n\u003cp\u003e(D)Top 18 authors with citation bursts.\u003c/p\u003e","description":"","filename":"image6.png","url":"https://assets-eu.researchsquare.com/files/rs-6792171/v1/e894df4385f26adb34ff8a2e.png"},{"id":85175608,"identity":"cda205ef-09b8-4bfd-8bc7-6362485511a5","added_by":"auto","created_at":"2025-06-23 06:27:04","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":444653,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eVisualization and analysis of active keywords and trend topics.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e(A) Network map of keywords associated with CRCLM;\u003c/p\u003e\n\u003cp\u003e(B) Temporal cumulative line chart of keywords;\u003c/p\u003e\n\u003cp\u003e(C) Top 7 keywords of the strongest citation bursts;\u003c/p\u003e\n\u003cp\u003e(D) Visualization of trend topics.\u003c/p\u003e","description":"","filename":"image7.png","url":"https://assets-eu.researchsquare.com/files/rs-6792171/v1/dd2c2d6826f775ecf346e1cb.png"},{"id":85175596,"identity":"f786161e-8792-4443-8773-8f3a663f96b7","added_by":"auto","created_at":"2025-06-23 06:27:03","extension":"png","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":882832,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eVisualize and analyze active literature.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e(A) Network diagram of CRCLM-related citation;\u003c/p\u003e\n\u003cp\u003e(B) Network diagram of co-cited documents;\u003c/p\u003e\n\u003cp\u003e(C) Top 20 reference documents with the strongest citation bursts;\u003c/p\u003e\n\u003cp\u003e(D)Three-field plot (middle field: Authors; left field: Keywords; right field: Institutions).\u003c/p\u003e","description":"","filename":"image8.png","url":"https://assets-eu.researchsquare.com/files/rs-6792171/v1/d62e1034f4973b7d37632c1e.png"},{"id":87810247,"identity":"5359eb3f-d114-4a80-be94-17327fa6a51a","added_by":"auto","created_at":"2025-07-29 09:09:59","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":5917174,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6792171/v1/ffdbc951-fa48-4a74-9b18-8124e851ce2d.pdf"},{"id":85175587,"identity":"2209ba6a-962b-40d1-8fcc-79c9f4fd823d","added_by":"auto","created_at":"2025-06-23 06:27:03","extension":"docx","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":15111,"visible":true,"origin":"","legend":"","description":"","filename":"TableS1.docx","url":"https://assets-eu.researchsquare.com/files/rs-6792171/v1/f169abf5014da17040c6780f.docx"},{"id":85175620,"identity":"0260efbb-b154-4f70-b912-39ace1c51e25","added_by":"auto","created_at":"2025-06-23 06:27:05","extension":"txt","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":28720675,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryMaterial1.txt","url":"https://assets-eu.researchsquare.com/files/rs-6792171/v1/b501fc0fd68349bf681045c0.txt"}],"financialInterests":"No competing interests reported.","formattedTitle":"Knowledge Mapping of liver metastases from colonrectal cazncer: A bibliometric analysis (2018–2024) and reflections","fulltext":[{"header":"Introduction","content":"\u003cp\u003eColorectal cancer (CRC) is one of the most prevalent malignant tumors of the digestive system. In recent years, while the incidence and mortality rates of CRC in the United States have declined, there has been a contrary and significant increase in both mortality and incidence rates within the domestic population. CRC remains the second leading cause of cancer-related deaths worldwide[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. The liver, due to its unique blood supply and anatomical structure[\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e], is the most common site of metastasis for various gastrointestinal cancers, including CRC[\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. Tumor metastasis is a major cause of poor prognosis and death. CRC is characterized by high incidence, high metastatic potential, and delayed diagnosis. For patients with early-stage CRC, the 5-year survival rate can reach up to 90%, but once distant metastasis occurs, the 5-year survival rate plummets to less than 20%[\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. Patients with colorectal cancer liver metastasis (CRCLM) are often diagnosed too late for surgical intervention, and treatment primarily relies on chemotherapy and integrated therapy[\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. Despite advancements and optimizations in chemotherapy regimens, the side effects and toxicities faced by patients undergoing chemotherapy remain a significant challenge and a leading cause of treatment discontinuation[\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. However, as of now, research literature and data on the pathogenesis, diagnosis, and treatment of colorectal cancer liver metastasis (CRCLM) are not systematic. There is an urgent need for more effective early diagnostic methods and safer, more efficacious treatment protocols.\u003c/p\u003e \u003cp\u003eBibliometrics focuses on the quantification of a complete body of knowledge. By analyzing existing quantitative literature and utilizing visual maps, it analyzes the current state of research, predicts the trajectory of a research field, and systematically summarizes the research progress of countries, institutions, authors, and disciplines[\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. This article aims to conduct a thorough and objective analysis of bibliometric indicators related to colorectal liver metastasis, elucidate the development trends, hotspots, and directions of research in colorectal liver metastasis, and assist researchers in more accurately and keenly grasping the research directions in this field. It also aims to build upon past achievements and accurately identify future prospective research hotspots, contributing more to the diagnosis and treatment of colorectal liver metastasis[\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e].\u003c/p\u003e"},{"header":"Materials and methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e1. Search strategy\u003c/h2\u003e \u003cp\u003eAll retrieved data were sourced from the Web of Science Core Collection (WoSCC), employing the following search strategy: TS = (\u0026ldquo;colorectal cancer\u0026rdquo;) AND (\u0026ldquo;liver metastases\u0026rdquo; OR \u0026ldquo;liver metastasis\u0026rdquo;) OR TS = (\u0026ldquo;liver metastases\u0026rdquo; from colorectal cancer) AND publication years = (2018\u0026ndash;2024) AND document types = (articles \u0026amp; reviews) AND language = (English). This process was conducted independently by two senior researchers (Qi Wang and Bendong Chen) to ensure relevance to the study's theme and to guarantee the accuracy of the retrieval process. A flowchart of the study's process is depicted in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e \u003cp\u003eAll publication records, including publication year, title, author names, affiliations, countries/regions, abstracts, keywords, and journal names, were exported and saved as plain text files, encompassing \"full records and cited references\". The size and color of the nodes represent the quantity and categorization of these items, respectively. The thickness of the lines between nodes reflects the degree of collaboration or co-citation of these items.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003e2. Analysis tools\u003c/h3\u003e\n\u003cp\u003eVOSviewer (version 1.6.20) is a software tool for constructing and visualizing bibliometric networks. This study utilizes VOSviewer to extract important terms and to construct and visualize the co-occurrence networks of these terms.\u003c/p\u003e \u003cp\u003eCiteSpace (version 6.1. R1), developed by Professor Chen C, is a software tool utilized for bibliometric analysis and visualization[\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. In our study, it was employed for Citation Bursts analysis.\u003c/p\u003e \u003cp\u003eThe R package \"bibliometrix\" (version 3.2.1) (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.bibliometrix.org\u003c/span\u003e\u003cspan address=\"https://www.bibliometrix.org\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) was used for thematic evolution analysis and to construct a global distribution network of colorectal cancer liver metastasis publications. Additionally, Microsoft Office Excel 2021 was employed for quantitative analysis of the publications.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003e1. Analysis of countries/regions\u003c/h2\u003e \u003cp\u003eInitially, the study analyzed the number of publications from each country to identify the leading contributors in the field. A total of 25,479 institutions and 37,041 researchers from 538 countries/regions participated in CRCLM research. Based on the country of residence of the corresponding authors, the publication and citation metrics of the top 25 most productive countries/regions were analyzed (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe analysis revealed an increasing trend in the annual number of publications related to CRCLM from 2018 to 2024. Due to the fact that the literature for 2024 was only retrieved up to October 24, there was a noticeable decrease in the number of publications for 2024. Conversely, the annual citation rate showed a declining trend (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Subsequently, an analysis of the publication output of the top five countries with the highest cumulative number of publications from 2018 to 2024 was conducted, demonstrating a steady upward trend in cumulative publication output for China, the United States, France, Japan, and Italy (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e. A).\u003c/p\u003e \u003cp\u003eChina published the highest number of articles (1,871, accounting for 29.5%, with multiple country publications accounting(MCP) for approximately 6.9%). It was followed by the United States (926, accounting for 14.6% of total publications, with MCP accounting for approximately 27.8%), and Japan ranked third (583, accounting for 9.2% of total publications, with MCP accounting for approximately 6.0%) (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eA). Additionally, China ranked first with 28,749 citations, the United States ranked second with 17,861 citations, and Japan ranked third with 6,566 citations (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e. B). This indicates that China, the United States, and Japan are the most significant contributors in this field, with the total number of publications from these three countries exceeding half of the total number of publications. A network visualization of the countries where the authors are based is depicted, with the size of the circles representing the number of publications, excluding countries with fewer than 5 publications (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e. C). A geographical map of the number of publications and collaboration intensity for each country is shown (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e. D). Furthermore, the analysis found that although Belgium published only 54 CRCLM articles, its MCP% was as high as 51.9%, making it the country with the highest proportion of international collaboration. While the United States had an MCP% of only 27.8%, its large base of publication output made it the country initiating and participating in the most international collaborations.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eTop 25 most productive countries/regions in CRCLM research\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"9\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRank\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCountry\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eArticle\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eN, %\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eSCP\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eMCP\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eMCP %\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eTC\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003eAC\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eChina\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1871\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e29.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1741\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e130\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e6.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e28749\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e15.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eUnited States\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e926\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e14.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e669\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e257\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e27.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e17861\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e19.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eJapanese\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e583\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e9.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e548\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e6.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e6566\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e11.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eItaly\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e339\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e5.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e266\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e73\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e21.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e4934\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e14.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGermany\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e325\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e5.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e216\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e109\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e33.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e5296\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e16.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFrance\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e226\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e168\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e25.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e3268\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e14.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNetherlands\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e218\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e135\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e83\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e38.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e4015\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e18.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eUnited Kingdom\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e186\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e87\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e46.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e3632\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e19.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSpain\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e167\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e126\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e24.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e4011\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e24.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eKorea\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e166\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e147\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e11.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e1664\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e10.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCanada\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e134\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e79\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e41.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e1733\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e12.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAustralia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e68\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e31.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e1460\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e14.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNorway\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e74\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e54\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e27.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e1837\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e24.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSweden\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e64\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e25.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e1287\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e20.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eIran\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e40.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e784\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e13.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTurkey\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e54\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e5.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e374\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e6.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAustria\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e46.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e802\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e14.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBelgium\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e54\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e51.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e741\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e13.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBrazil\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e32.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e399\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e7.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eIndia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e22.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e344\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e7.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePopand\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e31.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e493\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e11.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSwitzerland\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e45.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e971\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e22.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDenmark\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e16.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e426\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e11.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGreece\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e47.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e286\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e8.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSingapore\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e29.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e608\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e17.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eSCP: Single Country Publications; MCP: Multiple Country Publications; MCP% = MCP/ Articles; TC: Total citations; AC: Average citations.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003e2. Analysis of institutions\u003c/h3\u003e\n\u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e presents the top 10 universities with the highest number of published papers, with 2 institutions from China and 3 from the United States. Sun Yat-sen University had the highest number of publications (9.5%), followed by Fudan University (6.6%) and Memorial Sloan Kettering Cancer Center (6.3%). The collaboration network among these institutions is visualized in Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e. A (where the size of the circles represents the number of publications). The publication output of each institution is visualized in Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e. B.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eTop 10 most productive institutions in CRCML research\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRank\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAffiliation\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCountry\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eArticles\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003en, %\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSun yat-sen university\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eChina\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e600\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e9.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFudan university\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eChina\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e416\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e6.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMemorial Sloan Kettering Cancer Center\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eUnited States\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e401\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e6.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eUniversity of Oslo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNorway\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e387\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e6.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAssistance publique hopitaux paris (APHP)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eFrance\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e371\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e5.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eUniversite paris cite\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eFrance\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e347\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e5.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eUnicancer\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eFrance\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e337\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e5.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eUniversity of Texas System\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eUnited States\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e320\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e5.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBerlin institute of health\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eGermany\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e290\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e4.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eUtmd Anderson Cancer Center\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eUnited States\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e264\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e4.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003e3. Journal distribution\u003c/h2\u003e \u003cp\u003eAnalysis of the results revealed that a total of 1062 journals contributed to the publication of articles on colorectal cancer liver metastasis (CRCLM). Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e displays the top 10 journals with the highest number of CRCLM-related articles. The journal \"\u003cem\u003eCancers\u003c/em\u003e\" from Switzerland published the most articles related to CRCLM and also had the highest total citation count (TC); followed by \"\u003cem\u003eAnnals of Surgery\u003c/em\u003e\" from the United States, which published the second-highest number of relevant articles and had the second-highest total citation count, only behind \"\u003cem\u003eCancers\u003c/em\u003e\". Bradford's law was applied to analyze the core journals within the subject matter of the included journals, and the distribution of these core journals is shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e. A. The cumulative annual publication trend of the top five journals is depicted in Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e. B, showing a stable upward trend, with \"\u003cem\u003eCancers\u003c/em\u003e\" having the highest cumulative number of related literature over the years. The H-index was used to assess the impact of each journal on CRCLM, and it was found that \"\u003cem\u003eCancers\u003c/em\u003e\" led with an H-index of 28; \"\u003cem\u003eAnnals of Surgery\u003c/em\u003e\" was in second place with an H-index of 22; and \"\u003cem\u003eCell Death \u0026amp; Disease\u003c/em\u003e\" was in third place with an H-index of 20, indicating that these three journals play a significant role in the field of CRCLM research (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e. C). Subsequently, we analyzed the interactions between relevant journals in this field, and the results are shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e. D, where \"\u003cem\u003eCancers\u003c/em\u003e\" is visibly the most interconnected with other journals in recent years. Citation bursts refer to content that scholars in a particular field frequently cite over a period. In our study, CiteSpace identified five journals with strong citation bursts, arranged in chronological order (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eE). It is evident that \"\u003cem\u003eCancers\u003c/em\u003e\", \"\u003cem\u003eFrontiers in Oncology\u003c/em\u003e\" and \"\u003cem\u003eScientific Reports\u003c/em\u003e\" rank as the top three journals of citation bursts in 2024 with the strongest relevance. In the literature coupling analysis, we also found that \"\u003cem\u003eCancers\u003c/em\u003e\" was widely cited as the most significant contributing journal to the CRCLM topic (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e. F).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eLocal impact on CRCLM of Journal\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRank\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eJournal\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRegion\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eIF\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eArticles\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eH_index\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eTC\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCancers\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSwitzerland\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e267\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e2856\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAnnals of surgery\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eUnited states\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e2622\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCell death \u0026amp; disease\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eUnited kingdom\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e1129\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eEjso\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eUnited kingdom\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e117\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e1468\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eInternational journal of\u003c/p\u003e \u003cp\u003emolecular sciences\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eUnited states\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e68\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e2491\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAnnals of surgical oncology\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eUnited states\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e129\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e1375\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBmc cancer\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eUnited kingdom\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e1805\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFrontiers in oncology\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSwitzerland\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e181\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e1466\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eJournal of experimental\u003c/p\u003e \u003cp\u003e\u0026amp; clinical cancer research\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eItaly\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e11.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e933\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eJournal of surgical oncology\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eUnited states\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e102\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e1073\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eTC: Total citation.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003e4. Analysis of authors\u003c/h3\u003e\n\u003cp\u003eA total of 37,041 authors contributed to the publication of research papers related to CRCLM, with 1,282 scholars publishing 5 or more articles on CRCLM, and 287 authors publishing 10 or more articles. The co-authorship network in CRCLM research is depicted in Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e. A. The most relevant authors in terms of CRCLM are shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e. B, where Verhoef C and Wang Y published the highest number of articles, with 74 each. In terms of citation metrics, Vauthey JN emerged as the most cited author with 924 citations, followed by Pawlik TM, and D'Angelica MI ranked third (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e. C). The top 18 authors in citation bursts are illustrated in Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e. D.\u003c/p\u003e \u003cp\u003e \u003cb\u003e5. Keywords and trends\u003c/b\u003e \u003c/p\u003e \u003cp\u003eFigure \u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003e. A illustrates that \"properative chemotherapy\", \"surgical resection\", \"invasion\", \"prognostic factors\", \"colorectal neoplasms\", \"thermal ablation\", and \"proliferation\" are the seven most explosively cited keywords related to CRCLM from 2018 to 2014, which to some extent represent the research hotspots in this field during that period. In the cumulative temporal frequency analysis of keywords, \"colorectal cancer\", \"liver metastasis\", \"metastasis\", \"chemotherapy\", and \"prognosis\" rank in the top five, representing the research focal points in the field during the analyzed time frame. An analysis of the cumulative frequency of the top ten keywords over time shows a stable increasing trend for all top keywords, with \"chemotherapy\" significantly outpacing others, suggesting that chemotherapy may be a particularly hot topic in this field (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003e. B). The top seven keywords in the most relevant Citation Bursts are shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003e. C. Additionally, we analyzed the evolution of CRCLM-related topics over time. The topic \"tumor metastasis\" has remained a hot topic from 2021 to the present; \"pharmacokinetics\" has been a popular topic since 2020 and continues to the present; \"metastatic rectal cancer\" emerged as the latest high-frequency topic in 2024, potentially indicating the newest research trend; the core topics of this study, \"colorectal cancer\" and \"liver metastasis\", have been high-frequency keywords since 2020 and continued through 2023 (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003e. D).\u003c/p\u003e \n\u003ch3\u003e6. Document citation and reference co-citation analysis\u003c/h3\u003e\n\u003cp\u003eWe sorted the included papers based on citation data from the WoSCC. There were 775 articles with a citation count of 30 or more; 507 articles with a citation count of 40 or more; and 359 articles with a citation count of 50 or more. The network graph of the corresponding citation files is shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003e. A, with the papers by Tauriello(2018), Hashiguchi (2020), Argil\u0026eacute;s (2020), Zeng (2018) and Chi (2019) ranking in the top five. In terms of cited references, the document Fong Y_1999_Ann Surg_v230 leads with 742 citations and a total link strength of 8225; Jemal A_2011_CA-Cancer J Clin_v61 is second with 739 citations and a total link strength of 3953; and Van Cutsem E_2016_Ann Oncol_v27 is third with 660 citations and a total link strength of 6812 (Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003e. B, see Supplementary Material for Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e). The top 20 most frequently cited documents in citation bursts are shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003e. C. Additionally, this study utilized a tri-field map to explore the main keywords, authors, and their affiliated institutions, as depicted in Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003e. D.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eIndividuals diagnosed with colorectal cancer liver metastasis (CRCLM) are confronted with elevated mortality figures and unfavorable prognoses, presenting significant obstacles in clinical diagnosis and therapeutic interventions[\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. In recent decades, the corpus of research focused on CRCLM has significantly expanded. Bibliometrics recognized as a progressive analytical approach, is extensively employed to evaluate the contemporary landscape and evolving trends within a research domain[\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. This article undertakes a thorough bibliometric analysis of CRCLM-related literature sourced from the WoSCC spanning from 2018 to 2024, thereby offering a valuable reference for CRCLM researchers to accurately discern the developmental trajectories and emerging focal points of inquiry in this area.\u003c/p\u003e \u003cp\u003eIn this study, we utilized VOSviewer, CiteSpace, and the \"bibliometrix\" package in R to investigate the research dynamics and hotspots in the clinical science index (CSI) expansion for CRCLM. A total of 6,340 papers on the topic were retrieved from the WoSCC, covering a period from January 1, 2018, to October 24, 2024.\u003c/p\u003e \u003cp\u003eIn our analysis, we observed a stable upward trend in the number of papers published annually worldwide related to CRCLM. The cumulative temporal curve of the literature over the years also shows a consistent increase, which aligns with the global increasing trend of CRCLM. Chinese researchers are the largest contributors in the field of CRCLM research, with both the volume of publications and the number of citations ranking first globally. Among the top ten most prolific institutions, two are from China, including Fudan University and Sun Yat-sen University, with Sun Yat-sen University leading the world in publication volume. This indicates that China has made a significant contribution to the topic of CRCLM. However, despite China's total research output and citation data being far higher than other countries, the proportion of international collaboration in China is only 6.9%, while the United States leads with a 27.8% share of Multinational Collaborative Publications (MCP), indicating that American researchers have made greater efforts in international cooperation. This suggests that Chinese researchers should pay more attention to MCP, enhance international exchanges, and gain more international recognition and influence. Furthermore, although the total number of citations for Chinese publications ranks first, the average citation rate per Chinese publication is only 15.4. Given the large base of publications, this does not offer any advantage compared to other countries. This indicates that the quality (reader recognition) of some domestic publications is not high, suggesting that researchers should focus on controlling the quality of research outcomes to gain more recognition from peers in the same field.\u003c/p\u003e \u003cp\u003eIn the journal analysis, it was found that articles related to CRCLM are most frequently published in the journal \u003cem\u003eCancers\u003c/em\u003e, followed by \u003cem\u003eAnnals of Surgery\u003c/em\u003e and \u003cem\u003eCell Death \u0026amp; Disease\u003c/em\u003e. \u003cem\u003eCancers\u003c/em\u003e is one of the high-quality, influential journals in the field of oncology, with an impact factor of 4.5, and the analysis also indicates that \u003cem\u003eCancers\u003c/em\u003e is the most cited journal. Additionally, the \u003cem\u003eJournal of Experimental \u0026amp; Clinical Cancer Research\u003c/em\u003e, ranking 9th in publication volume and with an impact factor of 11.4, emerges as the journal with the highest impact factor related to the CRCLM theme. The aforementioned journals may become significant publishing institutions in this field in the future.\u003c/p\u003e \u003cp\u003eThe seven most explosive citation keywords related to CRCLM from 2018 to 2024 are properative chemotherapy, surgical resection, invasion, prognostic factors, colorectal neoplasms, thermal ablation, and proliferation. These keywords represent the research hotspots in this field during this period. They cover treatment methods, prognosis, and mechanisms of CRCLM, indicating that the main focus of this research remains within the mainstream scope without reflecting many innovative contents or new perspectives.\u003c/p\u003e \u003cp\u003eBased on the trend analysis of thematic summaries and keyword trends, the latest high-frequency trending topics are \"tumor metastasis\", \"pharmacokinetics\", and \"metastatic rectal cancer\". These represent the research trends and frontiers in the field of CRCLM. We have observed that the latest research trend topics do not introduce novel directions; apart from \"pharmacokinetics\", the other two merely describe the topic of disease metastasis and have persisted for a considerable duration. This may, to some extent, reflect a stagnation in breakthroughs and slow updates in CRCLM research, indicating a need for more innovative content and expansion of new perspectives.\u003c/p\u003e \u003cp\u003eIn colorectal cancer (CRC), the liver is the most common site of distant metastasis, with approximately half of CRC patients developing liver metastasis during the course of their disease. The primary treatment for CRCLM is complete hepatectomy, with a 5-year overall survival rate reaching nearly 60%[\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. However, no more than 20% of patients with CRCLM present with surgical indications at their initial visit[\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. The remaining patients can only be treated through other means, and for those with unresectable disease, even with the best chemotherapy regimens, the median survival rate remains low[\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. Studies have explored the use of immune checkpoint inhibitors (ICIs) in liver metastasis, with results showing that liver metastasis is not sensitive to ICIs[\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. Local regional therapy can cause irreversible damage to tumor cells and release tumor antigens, providing a theoretical basis for immunotherapy of liver metastasis. Therefore, researchers believe that the combination therapy of ICIs and local regional therapy is a promising option[\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. We have also noticed that \"pharmacokinetics\" is one of the latest trending topics. Since the vast majority of CRCLM cases are not candidates for surgery, chemotherapy has become prevalent, and the rise of this topic may be accompanied by the application of chemotherapy and other drug treatments, indicating that researchers may start to pay more attention to the safety and rationality of patient medication during chemotherapy, which is an indication of precision diagnosis and treatment. In the latest literature, nanomedicines composed of polymers, lipids, and inorganic nanoparticles are emerging and may replace traditional chemotherapy drugs because nanomedicines can effectively avoid side effects due to polytherapy[\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe body of literature collectively cited refers to documents that are cited by multiple other publications, thereby considering the collectively cited documents as the research foundation of a particular field. In this analysis, we examined the most frequently cited collectively cited documents to identify the research foundation of CRCLM. The most cited document is by Fong et al., published in the Annals of Surgery in 1999. This study confirmed a 5-year survival rate of 37% and a 10-year survival rate of 22% for CRCLM patients through a continuous analysis of 1001 cases of colorectal liver metastasis. It was also found that positive resection margins, extrahepatic disease, positive lymph nodes in the primary tumor, a time interval of less than 12 months from the primary tumor to metastasis, more than one liver tumor, the largest liver tumor diameter exceeding 5 cm, and carcinoembryonic antigen levels exceeding 200 ng/ml are significant risk factors for CRCLM, laying an important foundation for the surgical treatment of CRCLM[\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. Additionally, we noted that Jemal A et al.'s \u003cem\u003eCancer Statistics, 2010\u003c/em\u003e, published in 2011, ranks second in the list of cited documents. Although the article has a high impact factor of 503 points, the content described is relatively time-sensitive and dates back 14 years[\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e], making the high frequency of citation for this document somewhat puzzling.\u003c/p\u003e \u003cp\u003eIn addition, a bibliometric overview of the current state of CRCLM research reveals that studies on the pathogenesis of CRCLM do not seem to be reflected in this research, suggesting that such studies are either scarce or still in a very early stage. This may be a direction where researchers need to invest more effort. Furthermore, the topic of CRCLM diagnosis and treatment shows a sluggish pace, with research trends and high-frequency keywords indicating that there have been no revolutionary advances in recent years, and the topics of interest among researchers remain relatively conservative.\u003c/p\u003e \u003cp\u003eThe limitations of this study primarily stem from the reliance on a single database, WoSCC. A single database is prone to issues such as regional coverage bias, language bias, and metadata quality problems[\u003cspan additionalcitationids=\"CR23\" citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. This suggests that the interpretation of the results of this analysis should be more cautious. Future studies could employ a more comprehensive approach by integrating multiple databases to avoid these biases, thereby providing a more objective conclusion.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThe study employed bibliometric methods to reveal the current state and trends in CRCLM research, providing valuable guidance for researchers in understanding the research landscape of this field. There should be an increased emphasis on international collaboration in CRCLM research. Our research offers valuable insights for understanding and addressing CRCLM, laying the foundation for more in-depth studies and the discovery of more effective treatment methods. Further research should focus on the pathogenesis of CRCLM, early diagnosis, and personalized treatment to improve patient survival and quality of life.\u003c/p\u003e "},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eData availability statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe retrieved and downloaded data related to liver cancer and liver metastasis of colorectal cancer from the Web of Science Core Collection. These data are publicly accessible. Our use of the data complies with the guidelines of the database, and the data have been submitted as required (Supplementary Material 1).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics and consent to Participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent to publish declarations\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll authors agree to the publication of this article.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eClinical trial number\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eXusheng Zhang: Investigation, Methodology, Writing original draft, Writing \u0026amp; editing, Software, Writing review \u0026amp; editing. Bendong Chen: Investigation, Methodology, Writing original draft, Writing \u0026amp; editing, Software, Writing review \u0026amp; editing. Wenyan Zhou: Investigation, Methodology, Software, Writing original draft, Writing review \u0026amp; editing. Yongxin Ma: Methodology, Supervision, Visualization, Writing review \u0026amp; editing. Qi Wang: Methodology, Supervision, Visualization, Writing review \u0026amp; editing\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was supported by the project \u0026quot;Central Guidance for Local Science and Technology Development Special Project\u0026quot;, project number: 2024FRD05060.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflict of interest\u003c/strong\u003e\u003c/p\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\u003cp\u003e\u003cstrong\u003ePublisher\u0026rsquo;s note\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eBray F, Laversanne M, Sung H, Ferlay J, Siegel RL, Soerjomataram I, Jemal A: \u003cstrong\u003eGlobal cancer statistics 2022: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries\u003c/strong\u003e. \u003cem\u003eCA-CANCER J CLIN\u003c/em\u003e 2024, \u003cstrong\u003e74\u003c/strong\u003e(3):229-263.\u003c/li\u003e\n\u003cli\u003eDekker E, Tanis PJ, Vleugels JLA, Kasi PM, Wallace MB: \u003cstrong\u003eColorectal cancer\u003c/strong\u003e. \u003cem\u003eLANCET\u003c/em\u003e 2019, \u003cstrong\u003e394\u003c/strong\u003e(10207):1467-1480.\u003c/li\u003e\n\u003cli\u003eTrefts E, Gannon M, Wasserman DH: \u003cstrong\u003eThe liver\u003c/strong\u003e. \u003cem\u003eCURR BIOL\u003c/em\u003e 2017, 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A literature review\u003c/strong\u003e. \u003cem\u003eECANCERMEDICALSCIENC\u003c/em\u003e 2024, \u003cstrong\u003e18\u003c/strong\u003e:1771.\u003c/li\u003e\n\u003cli\u003eZhang X, Zhou Y, Wei G, Luo Y, Qiu M: \u003cstrong\u003eLocoregional therapies combined with immune checkpoint inhibitors for liver metastases\u003c/strong\u003e. \u003cem\u003eCANCER CELL INT\u003c/em\u003e 2024, \u003cstrong\u003e24\u003c/strong\u003e(1):302.\u003c/li\u003e\n\u003cli\u003eCosta KMN, Barros LA, Da Silva Soares IL, Oshiro-Junior JA: \u003cstrong\u003ePotential of Nanomedicines as an Alternative for the Treatment of Colorectal Cancer - A Review\u003c/strong\u003e. \u003cem\u003eANTI-CANCER AGENT ME\u003c/em\u003e 2024, \u003cstrong\u003e24\u003c/strong\u003e(7):477-487.\u003c/li\u003e\n\u003cli\u003eFong Y, Fortner J, Sun RL, Brennan MF, Blumgart LH: \u003cstrong\u003eClinical score for predicting recurrence after hepatic resection for metastatic colorectal cancer: analysis of 1001 consecutive cases\u003c/strong\u003e. \u003cem\u003eANN SURG\u003c/em\u003e 1999, \u003cstrong\u003e230\u003c/strong\u003e(3):309-318, 318-321.\u003c/li\u003e\n\u003cli\u003eJemal A, Siegel R, Xu J, Ward E: \u003cstrong\u003eCancer statistics, 2010\u003c/strong\u003e. \u003cem\u003eCA-CANCER J CLIN\u003c/em\u003e 2010, \u003cstrong\u003e60\u003c/strong\u003e(5):277-300.\u003c/li\u003e\n\u003cli\u003eLiu W: \u003cstrong\u003eThe data source of this study is Web of Science Core Collection? Not enough\u003c/strong\u003e. \u003cem\u003eSCIENTOMETRICS\u003c/em\u003e 2019, \u003cstrong\u003e121\u003c/strong\u003e(3):1815-1824.\u003c/li\u003e\n\u003cli\u003e\u003cstrong\u003eMissing author address information in Web of Science \u003c/strong\u003e\u003cstrong\u003e\u0026mdash;\u003c/strong\u003e\u003cstrong\u003e An explorative study\u003c/strong\u003e.\u003c/li\u003e\n\u003cli\u003eLiu W: \u003cstrong\u003eThe changing role of non-English papers in scholarly communication: Evidence from Web of Science\u0026apos;s three journal citation indexes\u003c/strong\u003e. \u003cem\u003eLEARN PUBL\u003c/em\u003e 2017, \u003cstrong\u003e30\u003c/strong\u003e(2):115-123.\u003c/li\u003e\n\u003c/ol\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":"Bibliometrics, Colorectal cancer, Liver metastasis, CiteSpace, VOSviewers","lastPublishedDoi":"10.21203/rs.3.rs-6792171/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6792171/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eliver metastases from colonrectal cazncer is a significant source of secondary liver malignancies. Considerable progress has been made in its diagnosis and treatment over the years. However, no recent bibliometric analysis has been identified on this topic. The present study aims to comprehensively elucidate the knowledge structure and research status related to liver metastasis in colorectal cancer using bibliometric methods.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eUtilizing the Web of Science Core Collection (WoSCC) database, a systematic literature search was performed for publications concerning liver metastasis in colorectal cancer from 2018 to 2024. Analyses were carried out using VOSviewer, CiteSpace software, and the R package \"bibliometrix\" to facilitate the relevant assessments.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eThe analysis encompassed 6,340 articles distributed across 538 countries/regions. Findings revealed a consistent annual increase in the volume of publications addressing liver metastasis in colorectal cancer. Among the top research institutions were Sun Yat-sen University and Fudan University. The journal \"\u003cem\u003eCancers\u003c/em\u003e\" and \"\u003cem\u003eAnnals of Surgery\u003c/em\u003e\" emerged as the most prominent publication outlet in this domain, also being the most frequently co-cited journal. The body of research was produced by 37,041 authors, with JN Vauther, C Verhoef, and Y Wang identified as the top three influential authors in the context of liver metastasis in colorectal cancer. Moreover, Fong Y, Jemal A, and Van Cutsem E were recognized for having the highest citation counts. A timeline visualization of keywords by frequency indicated that \"chemotherapy\" stands out as the most critical topic within this research area. Additional emerging trends included \"tumor metastasis\", \"pharmacokinetics\", and \"metastatic rectal cancer\".\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eThis investigation represents the inaugural comprehensive bibliometric analysis summarizing the research trajectories and advancements in liver metastasis associated with colorectal cancer. The insights derived from this study delineate the current research frontiers and trending topics, thereby serving as a valuable resource for future investigations within the realm of liver metastasis in colorectal cancer, although limiting the analysis to studies indexed in WoSCC may introduce bias into the results\u003c/p\u003e","manuscriptTitle":"Knowledge Mapping of liver metastases from colonrectal cazncer: A bibliometric analysis (2018–2024) and reflections","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-06-23 06:26:58","doi":"10.21203/rs.3.rs-6792171/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":"1487fba1-a3db-4b6c-9c88-252c2b0a45c9","owner":[],"postedDate":"June 23rd, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-07-29T09:09:19+00:00","versionOfRecord":[],"versionCreatedAt":"2025-06-23 06:26:58","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6792171","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6792171","identity":"rs-6792171","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}