Association between obesity and liver cancer from 2012 to... : Medicine (original) (raw)

1. Introduction

Liver cancer is a common malignant disease of the digestive system worldwide.[1,2] In 2019, there were 534,364 incident cases, 484,577 deaths, and 12.5 million disability adjusted life years due to liver cancer worldwide. From 2010 to 2019, the frequency of incident liver cancer cases increased by 27%, liver cancer deaths by 25%, and disability adjusted life years by 21%.[3] By 2040, 1.3 million people are estimated to die from liver cancer.[4]In total 5% to 15% of patients are eligible for surgical removal, which is only for patients in the early stage without cirrhosis. Trans-arterial chemoembolization and oral sorafenib dosage are treatment options for more advanced stages. However, neither current ablation therapies nor chemotherapy can effectively improve the outcome of liver cancer.[5,6] Therefore, the prevention of liver cancer is of great importance.

Obesity is an increasingly prevalent global health issue in most countries.[7,8] In recent years, many studies have focused on the connection between obesity and liver cancer.[9–11] A study explains the correlation between obesity and liver cancer: obesity induces alterations of gut microbiota, thus activating the deoxycholic acid-senescence-associated secretory phenotype axis, which is a process leading various inflammatory and tumor-promoting factors secreted in the liver, hence facilitating hepatocellular carcinoma development in mice.[12] Another study shows that obesity induced the hepatic translocation of lipoteichoic acid, so that it can create a tumor-promoting microenvironment.[13] Besides, obesity is a common risk factor for nonalcoholic fatty liver disease, which is a major cause of hepatocellular carcinoma.[14] Excess adult adiposity is widely known to raise the risk of liver cancer,[15] several studies suggest that adiposity at earlier ages is also a risk of liver cancer.[16–18] People with a high waist circumference had a 2-fold increased risk of liver cancer, according to cohort studies conducted in the US and Europe. Excess abdominal size is also associated with increased liver cancer risk.[19,20] So, it is crucial to investigate the relationship between obesity and liver cancer which is beneficial for understanding the inducing factors and etiology of tumor formation. People should keep a healthy diet and exercise regularly to avoid obesity so as to reduce the risk of liver cancer. We aim to improve prevention.

Bibliometric analysis, which employs mathematical and statistical methodologies, is presently the most often used tool for acquiring general knowledge structure and research objectives in an academic topic. Various scientific methodologies are employed to thoroughly comprehend the current state of an academic topic.[21] In recent years, with the deepening research of hepatocarcinogenesis and risk factors of liver cancer, studies have revealed that obesity is closely correlated to liver cancer.[22] Although the research on the obesity in liver cancer were formerly explored based on numerous experiments or studies,[23] no systematic analysis of characteristic of the research in this academic field were launched. Unlike other approaches like meta-analyses, traditional reviews, or experimental investigations, bibliometrics can not only characterize the state of academic research now but also evaluate its future directions and forecast emerging trends. In this study, we analyzed the current research status and future research trends using bibliometric methods for the first time, aiming to offer valuable insights for researchers.

2. Materials and methods

2.1. Ethics statement

This study did not involve any research on humans or animals, instead, it was based on published publications from January 01, 2012 to October 28, 2023 that were in the public domain. Therefore, ethical approval was not needed for this research.

2.2. Data sources and search strategy

The Web of Science Core Collection database was our first choice for finding and extracting pertinent papers. We constructed the search strategy using terms that probably be used in the majority of scientific papers in order to cover as many target articles as possible. The search strategy is mapped out in Table 1. We also looked for inclusion and exclusion criteria in the titles and abstracts. Generalized selection processes are shown in Figure 1. The inclusion criteria were as follow: (1) Language restriction for the publication is in English. (2) Published between January 01, 2012 to October 28, 2023. (3) The types of publications are articles and reviews. (4) The content of the articles was mainly focused on the correlation between obesity and liver cancer. The following studies were excluded: (1) Publication type was animal experiment. (2) Other types of publications, including editorial materials, meeting abstracts, early accesses, book chapters, proceeding papers, retracted publications, and corrections.

Table 1 - The research strategy of Web of Science Core Collection (WoSCC).

WoSCC = Web of Science Core Collection.

Figure 1.:

Flow chart of selection processes for eligible studies.

2.3. Statistical analysis

General characteristics of eligible publications, such as the number of yearly publications, citations, h-index, and Web of Science subject category lists were examined. In terms of data analysis and visualization, the dominant analytical tools for bibliometrics are CiteSpace, VOSviewer and R software. The optimal bibliometric analysis method remains a matter of debate. Therefore, we combine the properties and strengths of each of these tools, we used CiteSpace, VOSviewer, and R software simultaneously for current analysis. VOSviewer is a powerful software for building and visualizing bibliometric networks on the basis of publications, countries, and authors. The burst keywords and areas of research were explored via CiteSpace. At the same time, international cooperation between countries/regions is analyzed using the R package bibliometrix. In order to analyze the relationship between year of publication and the number of publications, IBM SPSS Statistics 25 software was uesd to perform Pearson correlation analysis.

3. Results

3.1. Annual tendencies of publications

The number of publications is a meaningful indicator to measure the level of progress of a field. In addition, changes in the number of publications, especially on an annual basis, not only indicate the degree of prosperity in the field to some extent, but also clearly show macro trends. Figure 2 shows the annual publication volume in current research from 2012 to 2023. Taken together, the amount of publications demonstrates different features prior to and following 2017: From 2012 to 2017, the annual number of publications was relatively steady, mostly hovering around 13. The publication volume shows a growth trend starting from 2018, with the number reaching the peak in 2022. This suggests that research on the association between obesity and liver cancer is receiving increasing attention from researchers and is thriving. Using Pearson correlation analysis, the trend of related studies was clearly predicted. According to Table 2, there is a moderate correlation between the publication outputs and the year of publication (R = 0.711, P = .010).

Table 2 - Pearson correlation analysis.

| | Correlations | | | | | --------------- | ------------------- | ----------- | -------- | | | | Year | Publication | | | Year | Pearson correlation | 1 | .711** | | Sig. (2-tailed) | | .010 | | | N | 12 | 12 | | | Publication | Pearson correlation | .711** | 1 | | Sig. (2-tailed) | .010 | | | | N | 12 | 12 | |

**. Correlation is significant at the 0.01 level (2-tailed).

Figure 2.:

Time trend of the annual research publications.

3.2. Distribution of countries/regions

From 2012 to 2023, a total of 537 research institutions from 44 countries/regions have published articles related to obesity and liver cancer . We found that these articles originated from 124 journals and 1428 authors. A world map that shows the cooperative relationship between various countries/regions was made using information from the published articles (Fig. 3). Figure 4 is a chord diagram illustrating the cooperation between different countries. Each colored block represents a country, and the lines among them represent the cooperation relationship. The countries were ranked based on the number of publications, and the top 10 countries are shown below. According to the Table 3, the United States published the most articles (n = 89, 38.20%), followed by China (n = 66, 28.33%), England (n = 30, 12.88%), Germany (n = 17, 7.30%), Japan (n = 15, 6.44%), South Korea (n = 15, 6.44%), Italy (n = 14, 6.01%), Sweden (n = 13, 5.58%), France (n = 12, 5.15%), and Australia (n = 11, 4.72%). USA and China have made prominent contributions in the obesity and liver cancer field. The United States plays a leading role in the research with the highest number of publications and total citations. It is noteworthy that France has the highest average citation score, indicating that research institutions in France are considerable scientific research forces in this field. Meanwhile, Figure 5 presents the collaboration map of different countries in obesity and liver cancer. Each frame represents one country and frame size is based on the number of publications. Connecting lines between them represent coopera tive relationship.We set the maximum number of countries per document to 25 and the minimum number of documents of a country to 3, 21 countries meet the thresholds. The result shows that USA mostly cooperated with China, Australia, France, and Germany. The outcome also indicates that scientific research transcends national borders, meaning that international cooperation will be crucial for carrying out studies in the field.

Table 3 - Top 10 productive countries related to obesity and liver cancer research.

Figure 3.:

The world map of collaboration relations between countries or regions.

Figure 4.:

Chord diagram of cooperation between different countries.

Figure 5.:

The collaboration map of countries.

3.4. Distribution of institutions

Table 4 shows the 12 most contributing research institutions. From 2012 to 2023, more than half of the top 12 research institutions from USA (9/12), followed by the China (3/12).The results reveal that institutions in USA and China have made pivotal contributions in obesity and liver cancer field.

Table 4 - 12 most productive institutions.

3.5. Contributions of authors

Twenty eight authors have published at least 3 publications, but only 8 of them ever used to cooperate with others (Fig. 6). This illustrates a lack of collaboration among scholars. Figure 7 shows the connection between authors, institutions, and countries. The left field represents authors, the middle field represents institutions, and the right field represents countries. Table 5 reveals that MCGLYNN KA from America not only has the most number of publications (17, 7.3%), but also gets the highest total citation (3633), and h-index.[15,24]

Table 5 - Top 10 authors ranked by number of publications.

Figure 6.:

The collaboration map of authors.

Figure 7.:

The three-field plot of authors, institutions, and countries.

3.6. Analysis of number of citations

The influence of a publication in a certain scientific field can be gauged by its citation count. Table 6 displays the top 10 publications out of the 233 articles that were counted and ranked based on the amount of citations. The most cited article was Yoshimoto, S et al[12] of Japan Science and Technology Agency published in 2013 with a citation number of 1410. The review analyses of epidemiology of liver cancer are included among the 10 most cited articles.

Table 6 - Top 10 most cited articles related to obesity and liver cancer research.

3.7. Area of research

We set the k value of g-index to 25, then we get Figure 8 and Figure 9. There are 7 clusters in the main research field (Fig. 8). The 7 clusters cover risk factors, cancer, liver cancer, hepatocellular carcinoma, body mass index, overall survival, and Japan. The 7 clustering labels are presented in the form of a keyword timeline map (Fig. 9) in order to promote the analysis of clustering feature with the evolution over time.

Figure 8.:

Seven clusters of research.

Figure 9.:

Keyword timeline map.

3.8. Analysis of keywords

According to the keyword co-occurrence analysis of the literature, the hot topics in the research field are described in detail presentation. By analyzing the keywords of the 233 publications, totally 1086 keywords were discovered, and VOSviewer was used to identify 30 hotspots keywords that appeared at least 15 times and visualized connection with a network (Fig. 10A). Figure 11 is the treemap chart of the top 10 hotspots keywords with the highest frequencies. Examining the terms that have the most robust citation bursts “Burst words” are keywords that exhibit a sharp rise in frequency over time, signifying the frontier of academia in this area. In current study, we used CiteSpace software to identify the keywords with strong citation bursts. We set γ to 0.8 and 11 “Burst words” with strength >2.2 were presented. Figure 10B shows the top 11 “Burst words” as citations in the connection of obesity and liver cancer during the period of 2012 to 2023. The red strip represents the duration of the burst keywords. The most keywords with strongest citation bursts, diabetes mellitus, began in 2012 and end in 2013 with highest strength of 4.02, which was associated with the risk factors of hepatocarcinogenesis. The second strength of 3.02 was inflammationduring 2017 to 2018, which was associated with the trigger and cause of liver cancer. Impact and prevalence were the latest keywords with strong citation bursts, suggesting that these may be popular topics in recent years and years to come.

Figure 10.:

(A) The co-occurrence network of keywords. (B) Top 11 keywords with the strongest citation bursts.

Figure 11.:

Top 10 hotspots keywords.

4. Discussion

4.1. Summary of the research

Liver cancer is the seventh most prevalent cancer worldwide and the second most common cause of cancer deaths.[1] Hepatitis B virus infection, hepatitis C virus infection, alcoholism, and nonalcoholic fatty liver disease are by far the most common causes of hepatocellular carcinoma.[25,26] Some studies have shown that metabolic factors such as obesity have a greater overall impact on liver cancer than viral hepatitis.[27] Moreover, the obesity is closely associated with the rising prevalence and severity of nonalcoholic fatty liver disease, thereby forcing a deeper connection to liver cancer.[28] In recent years, the prevalence of obesity and overweight has been increasing, accounting for more than one-third of the population worldwide.[29,30] Therefore, it is necessary for the public to pay more attention to obesity, which is a preventable cause of liver cancer.

In present bibliometric analysis, we screened 233 publications including 167 articles and 66 reviews on the association between obesity and liver cancer research from the WoSCC database. The number of publications correlated with obesity and liver cancer has been showing an increasing trend since 2017, with approximately 3 times as many publications in 2022 as in 2012. The remarkable increase in the number of publications over the past ten years, illustrating that the research of obesity and liver cancer has attracted more attention of researchers. Substantial studies have revealed the involvement of obesity in hepatocellular carcinoma, including subtype, pathogenesis, prevention, treatment strategy, and societal management.[31–34]

For the first time we used bibliometric methods to analyze the contributions of countries, institutions, and authors in the research of the association between obesity and liver cancer. USA and the China have the largest number of published papers in this domain. The United States was the most influential country in the field of obesity and liver cancer, with the highest number of publications and citations. Articles published by Japan scholars have the second average number of citations and the third number of total citations, which suggests that their studies were superb and convincing. Despite of China's leading position of all other countries aside from the USA in terms of the number of articles published, the average citations of articles published by Chinese scholars are almost the lowest of the top 10 prolific countries. This demonstrates that Chinese scholars need to focus more on researches of higher quality rather than quantity. In addition, there should be more collaboration among authors in this field of research, so that resources, knowledge, and skills can be shared in order to improve research efficiency and innovation.

The most cited article was published in Nature, revealing that obesity can change the intestinal microbiota through senescence-associated secretory phenotype,[12] which provide a new research direction of pathogenesis of liver cancer.

4.2. Research limitations

The constraints that existed in the current study ought to be taken into account in further research. First, the database contained just publications from WoSCC and might have excluded some relevant and important ones. Second, we aimed to study on the global trend of association between obesity and liver cancer, but selection bias might have been resulted from the exclusion of non-English publications. Furthermore, because the WoSCC retrieval algorithm was not based on full text, it is possible that a few pertinent articles were overlooked and other irrelevant articles were included. This could have resulted in bias when it came to the visualization of the association between obesity and liver cancer.

5 Conclusions

In the current study, we first employed bibliometric methods to investigate the relationships between obesity and liver cancer. The annual number of publications on obesity and liver cancer has shown an increasing trend in the past decade, demonstrating the potential for precise study in this sector and its increasing focus.

Acknowledgments

The authors sincerely thank all the open-access resources and R package bibliometrix.

Author contributions

Data curation: Donghong Wang.

Formal analysis: Donghong Wang.

Methodology: Donghong Wang.

Project administration: Zhibin Ma.

Software: Donghong Wang.

Visualization: Donghong Wang.

Writing – original draft: Donghong Wang.

Writing – review & editing: Zhibin Ma.

Abbreviation:

WoSCC

Web of Science Core Collection.

References

[1]. McGlynn KA, Petrick JL, El-Serag HB. Epidemiology of hepatocellular carcinoma. Hepatology. 2021;73:4–13.

[2]. Zelber-Sagi S, Noureddin M, Shibolet O. Lifestyle and hepatocellular carcinoma what is the evidence and prevention recommendations. Cancers. 2021;14:103.

[3]. Huang DQ, Singal AG, Kono Y, Tan DJH, El-Serag HB, Loomba R. Changing global epidemiology of liver cancer from 2010 to 2019: NASH is the fastest growing cause of liver cancer. Cell Metab. 2022;34:969–77.e2.

[4]. Rumgay H, Arnold M, Ferlay J, et al. Global burden of primary liver cancer in 2020 and predictions to 2040. J Hepatol. 2022;77:1598–606.

[5]. Man S, Luo C, Yan M, Zhao G, Ma L, Gao W. Treatment for liver cancer: From sorafenib to natural products. Eur J Med Chem. 2021;224:113690.

[6]. Anwanwan D, Singh SK, Singh S, Saikam V, Singh R. Challenges in liver cancer and possible treatment approaches. Biochim Biophys Acta Rev Cancer. 2020;1873:188314.

[7]. Jebeile H, Kelly AS, O’Malley G, Baur LA. Obesity in children and adolescents: epidemiology, causes, assessment, and management. Lancet Diabetes Endocrinol. 2022;10:351–65.

[8]. Saitta C, Pollicino T, Raimondo G. Obesity and liver cancer. Ann Hepatol. 2019;18:810–5.

[9]. Marengo A, Rosso C, Bugianesi E. Liver cancer: connections with obesity, fatty liver, and cirrhosis. Annu Rev Med. 2016;67:103–17.

[10]. Shimizu M, Tanaka T, Moriwaki H. Obesity and hepatocellular carcinoma: targeting obesity-related inflammation for chemoprevention of liver carcinogenesis. Semin Immunopathol. 2013;35:191–202.

[11]. Divella R, Mazzocca A, Daniele A, Sabbà C, Paradiso A. Obesity, nonalcoholic fatty liver disease and adipocytokines network in promotion of cancer. Int J Biol Sci. 2019;15:610–6.

[12]. Yoshimoto S, Loo TM, Atarashi K, et al. Obesity-induced gut microbial metabolite promotes liver cancer through senescence secretome. Nature. 2013;499:97–101.

[13]. Loo TM, Kamachi F, Watanabe Y, et al. Gut microbiota promotes obesity-associated liver cancer through PGE2-mediated suppression of antitumor immunity. Cancer Discov. 2017;7:522–38.

[14]. Ajmera V, Cepin S, Tesfai K, et al. A prospective study on the prevalence of NAFLD, advanced fibrosis, cirrhosis and hepatocellular carcinoma in people with type 2 diabetes. J Hepatol. 2023;78:471–8.

[15]. Lauby-Secretan B, Scoccianti C, Loomis D, Grosse Y, Bianchini F, Straif K. Body Fatness and Cancer—Viewpoint of the IARC Working Group. N Engl J Med. 2016;375:794–8.

[16]. Berentzen TL, Gamborg M, Holst C, Sørensen TIA, Baker JL. Body mass index in childhood and adult risk of primary liver cancer. J Hepatol. 2014;60:325–30.

[17]. Hagström H, Tynelius P, Rasmussen F. High BMI in late adolescence predicts future severe liver disease and hepatocellular carcinoma: a national, population-based cohort study in 1.2 million men. Gut. 2018;67:1536–42.

[18]. Hassan MM, Abdel-Wahab R, Kaseb A, et al. Obesity early in adulthood increases risk but does not affect outcomes of hepatocellular carcinoma. Gastroenterology. 2015;149:119–29.

[19]. Florio AA, Campbell PT, Zhang X, et al. Abdominal and gluteofemoral size and risk of liver cancer: the liver cancer pooling project. Int J Cancer. 2020;147:675–85.

[20]. Campbell PT, Newton CC, Freedman ND, et al. Body Mass Index, waist circumference, diabetes, and risk of liver cancer for U.S. Adults. Cancer Res. 2016;76:6076–83.

[21]. Arruda H, Silva ER, Lessa M, Proença D Jr., Bartholo R. VOSviewer and Bibliometrix. J Med Libr Assoc. 2022;110:392–5.

[22]. Akl MG, Widenmaier SB. Immunometabolic factors contributing to obesity-linked hepatocellular carcinoma. Front Cell Dev Biol. 2023;10:1089124.

[23]. Becattini B, Breasson L, Sardi C, Zani F, Solinas G. PI3Kγ promotes obesity-associated hepatocellular carcinoma by regulating metabolism and inflammation. JHEP Rep. 2021;3:100359.

[24]. Hou Z, Wang W, Su S, et al. Bibliometric and visualization analysis of biomechanical research on lumbar intervertebral disc. J. Pain Res. 2023;16:3441–62.

[25]. Konyn P, Ahmed A, Kim D. Current epidemiology in hepatocellular carcinoma. Expert Rev. Gastroenterol. Hepatol. 2021;15:1295–307.

[26]. Li L, Wang H. Heterogeneity of liver cancer and personalized therapy. Cancer Lett. 2016;379:191–7.

[27]. Shin HS, Jun BG, Yi S-W. Impact of diabetes, obesity, and dyslipidemia on the risk of hepatocellular carcinoma in patients with chronic liver diseases. Clin. Mol. Hepatol. 2022;28:773–89.

[28]. Polyzos SA, Kountouras J, Mantzoros CS. Obesity and nonalcoholic fatty liver disease: from pathophysiology to therapeutics. Metabolism 2019;92:82–97. Available at: https://www.metabolismjournal.com/article/S0026-0495(18)30253-1/fulltext.

[29]. Sun B, Karin M. Obesity, inflammation, and liver cancer. J Hepatol. 2012;56:704–13.

[30]. Sohn W, Lee HW, Lee S, et al. Obesity and the risk of primary liver cancer: a systematic review and meta-analysis. Clin. Mol. Hepatol. 2021;27:157–74.

[31]. Chaisaingmongkol J, Budhu A, Dang H, et al. Common molecular subtypes among asian hepatocellular carcinoma and cholangiocarcinoma. Cancer Cell. 2017;32:57–70.e3.

[32]. Grohmann M, Wiede F, Dodd GT, et al. Obesity Drives STAT-1-Dependent NASH and STAT-3-Dependent HCC. Cell. 2018;175:1289–306.e20.

[33]. Tsuneki H, Maeda T, Takata S, et al. Hypothalamic orexin prevents non-alcoholic steatohepatitis and hepatocellular carcinoma in obesity. Cell Rep. 2022;41:111497.

[34]. Allaire M, Bruix J, Korenjak M, et al. What to do about hepatocellular carcinoma: recommendations for health authorities from the International Liver Cancer Association. JHEP Rep. 2022;4:100578.

Keywords:

bibliometric analysis; liver cancer; obesity; publications; trend

Copyright © 2024 the Author(s). Published by Wolters Kluwer Health, Inc.