Unlocking Future Research Strategies: Key Collaborations and Network Characteristics in Helicobacter Pylori Eradication Therapy (2000-2023)

doi:10.21203/rs.3.rs-5000986/v1

Download PDF

Research Article

Unlocking Future Research Strategies: Key Collaborations and Network Characteristics in Helicobacter Pylori Eradication Therapy (2000-2023)

https://doi.org/10.21203/rs.3.rs-5000986/v1

This work is licensed under a CC BY 4.0 License

Version 1

posted

You are reading this latest preprint version

Aim

To analyze the collaboration patterns among researchers in Helicobacter pylori (H.pylori) eradication therapy from 2000 to 2023, identifying key contributors and evaluating the structural characteristics of the co-authorship network.

Method

This study utilized data from the Web of Science (WoS) Core Collection, analyzing 13,432 articles on Helicobacter pylori eradication published between 2000 and 2023. The co-authorship network was examined using macro-level indicators such as network density, clustering coefficient, number of components, and average path length, along with micro-level indicators including degree centrality, closeness centrality, and betweenness centrality. The analysis was conducted using Python (Version 3.10.5) in the PyCharm development environment (Software Version 2022.1.3).

Result

The co-authorship network demonstrated an evolving structure over the analyzed period, with increasing network density and clustering coefficients, suggesting enhanced collaboration among researchers. Key contributors such as Asaka M., Graham DY, and Mégraud F. consistently emerged as central figures, facilitating collaboration within the network. Despite these improvements, the network remained fragmented with several isolated components, indicating persistent gaps in global connectivity.

Conclusion

The study highlights the evolving collaborative landscape in H. pylori eradication research over the past two decades, emphasizing the importance of key researchers in driving scientific collaboration. Despite modest improvements in network connectivity, ongoing efforts to foster collaboration are essential to address challenges such as antibiotic resistance and enhance the effectiveness of H. pylori eradication therapies.

Medical Informatics

Gastroenterology & Hepatology

Bioinformatics

Information Retrieval and Management

Internal Medicine

Helicobacter pylori

Helicobacter pylori eradication therapy

co-authorship network analysis

network analysis

research collaboration

research trend analysis

Background and Objectives

Helicobacter pylori (H. pylori) eradication therapy plays a pivotal role in preventing and managing gastrointestinal diseases such as peptic ulcers, gastric mucosa-associated lymphoid tissue (MALT) lymphoma, and gastric cancer ¹. Despite significant advancements in treatment protocols, several challenges persist. Notably, the increasing prevalence of antibiotic-resistant H. pylori strains has complicated the efficacy of standard eradication regimens, leading to higher rates of treatment failure ². Additionally, variations in patient compliance due to side effects or complex medication schedules further undermine the success of eradication efforts ^3-4. These issues highlight the need for ongoing research and collaboration among scientists to develop more effective, patient-friendly, and adaptable treatment strategies. Co-authorship network analysis provides a means to map the landscape of scientific collaboration in this field, offering insights into how researchers connect, share knowledge, and collectively address these pressing challenges.

Scope of the Study

This study examines publications related to Helicobacter Pylori Eradication research indexed in the Web of Science (WoS) Core Collection database between 2000 and 2023. A total of 13,432 articles were selected for analysis, providing a comprehensive overview of the collaborative landscape within this specialized field over the past two decades. The dataset ensures the inclusion of the most recent publications (as of August 2024). The analysis will focus on constructing and evaluating co-authorship networks using macro-level indicators such as network density (the ratio of actual to possible connections), clustering coefficient (the degree to which nodes tend to cluster together), number of components (distinct connected subgroups within the network), and average path length (the average distance between nodes). At the micro-level, I will assess degree centrality (the number of direct connections each node has), closeness centrality (how close a node is to all other nodes), and betweenness centrality (the extent to which a node lies on the shortest path between other nodes). These metrics will help illuminate the structure and dynamics of researcher collaborations in this field.

Significance of the Study

This study aims to provide a comprehensive overview of the collaborative landscape in H. pylori eradication research, identifying key researchers, influential collaborations, and evolving trends over time. By elucidating the roles and connections of central figures within the network, the findings can guide targeted efforts to enhance collaboration, such as forming strategic alliances and prioritizing underrepresented research areas. For instance, understanding which researchers or groups are central to the network can help in designing initiatives to foster interdisciplinary collaboration, share resources, and integrate diverse expertise, which are crucial for tackling complex issues like antibiotic resistance. Moreover, the insights from this study could be applied to optimize research strategies, funding allocation, and policymaking, ultimately improving the global effectiveness of H. pylori eradication therapies.

The present study investigates the co-authorship patterns in Helicobacter Pylori Eradication research papers. I utilized the WoS Core Collection database, conducting a "Topic search" with the keyword "HELICOBACTER PYLORI ERADICATION" to analyze a total of 13,432 articles published between 2000 and 2023 (as of August 2024). In this analysis, I examined who collaborated with whom in co-authoring these papers. I conducted network analysis using the Python programming language (version 3.10.5) within the integrated development environment (IDE) PyCharm (software version 2022.1.3). This study employed methodology-established principles of social network analysis ⁵. I carried out the analysis in two main parts:

Macro-level Metrics:

Network Density

Calculated as the ratio of the number of edges to the maximum possible edges between all nodes.

Clustering Coefficient

Measured the extent to which nodes form clusters by considering the number of edges among neighboring nodes and calculating the average.

Components

Identified and counted the number of subgraphs (components) where nodes are mutually connected.

Average Path Length

Evaluated the average "distance" between nodes by calculating the overall average path length in the network ⁶.

Micro-level Metrics:

Degree Centrality

Measured the importance of each node by counting the number of edges it has in the network.

Closeness Centrality

Defined as the inverse of the sum of the shortest path lengths from a node to all other nodes, measuring how close each node is to others in the network.

Betweenness Centrality

Assessed the extent to which a node lies on the shortest paths between other nodes, indicating its importance in information transmission within the network ^6–7.

The significance of these macro-level metrics in understanding the structure of scientific collaboration networks and these micro-level centrality measures in scientific collaboration networks has been well documented and used ^6–7. Through these analyses, I can identify collaborative relationships and influential researchers in H. pylori eradication research. This information may be useful for understanding research trends and planning future collaborative studies.

The study analyzed the co-authorship network of researchers in the field of H. pylori eradication research, focusing on the periods from 2000 to 2023. The analysis was conducted using data from the WoS Core Collection and utilized both macro and micro-level network metrics to understand the evolution of collaborative networks in this field.

2000–2009 Network Analysis

During the 2000–2009 period, the co-authorship network comprised numerous components, totaling 1,213 (Table 1), reflecting a fragmented network structure (Fig. 1). The network density was 0.00057 (Table 1), indicating sparse connections among the researchers, with only 0.057% of potential collaborations being realized. The average clustering coefficient was 0.885 (Table 1), suggesting that when collaborations existed, they were likely to form tight-knit groups (Fig. 1). However, the average distance between nodes was infinite, indicating the lack of a fully connected network ⁸.

At the micro-level, key researchers identified by degree centrality included Asaka M., Gasbarrini G., and Lam SK, highlighting their frequent collaborations within the network (Table 2). Vaira D., Vakil N., and Asaka M. were among the top nodes by closeness centrality, reflecting their accessibility and importance in connecting other researchers (Table 3). In terms of betweenness centrality, De Francesco V., Vakil N., and Stolte M. held significant positions, acting as crucial bridges within the network, facilitating information flow and collaboration between otherwise disconnected groups (Table 4).

In the H. pylori eradication research during the period 2000–2009, Asaka Masahiro (Hokkaido Univ, Japan) and Vakil Nimish (University of Wisconsin, USA) were very influential in H. pylori eradication research during the period 2000–2009 (Fig. 1, Table 2–4).

2010–2019 Network Analysis

The 2010–2019 period saw an increase in the fragmentation of the network, with the number of components rising to 1,505 (Table 1). The network density slightly decreased to 0.00052 (Table 1), suggesting a continued trend of sparse connections with only 0.052% of possible links realized (Fig. 2). The average clustering coefficient improved to 0.900 (Table 1), indicating more cohesive groups among collaborating researchers (Fig. 2). However, the average distance remained infinite, signifying ongoing network disconnection ⁸.

In terms of micro-level metrics, Gisbert JP., Kim N., and Graham DY emerged as central figures by degree of centrality, demonstrating their extensive co-authorship ties (Table 2). Graham DY, Sugano K., and Malfertheiner P. had high closeness centrality scores, making them pivotal points in the network for bridging collaborations (Table 3). Key researchers by betweenness centrality included Graham DY, Kuipers EJ, and Malfertheiner P., emphasizing their roles in linking disparate network components and facilitating broader collaborative interactions (Table 4).

In H. pylori eradication research during the period 2010–2019, Graham David Y (Baylor College of Medicine, USA) and Malfertheiner Peter (Otto von Guericke University, Germany) were very influential (Fig. 2, Table 2–4).

2020–2023 Network Analysis

During the period from 2020 to 2023, the co-authorship network for H. pylori eradication research showed a notable improvement in connectivity with a reduction in the number of components to 935 (Table 1), indicating a more interconnected network (Fig. 3). The network density increased to 0.00097 (Table 1), reflecting a rise in collaborative links among researchers (Fig. 3), albeit still representing a small fraction of potential relationships (0.097%). The average clustering coefficient further increased to 0.921 (Table 1), highlighting enhanced clustering and group formation among researchers (Fig. 3). However, the average distance between nodes remained infinite, suggesting persistent gaps in network connectivity ⁸.

At the micro level, the top researchers by degree centrality during this period included Mégraud F., Gisbert JP., and O'Morain C., signifying their central roles in the network through frequent co-authorships (Table 2). High closeness centrality scores were observed for Lu H., Mégraud F., and Graham DY., indicating their strategic positions in minimizing the distance to other nodes (Table 3). In terms of betweenness centrality, Lu H., Mégraud F., and Yamaoka Y. stood out as influential connectors, bridging various network clusters and playing critical roles in the dissemination of research within the field (Table 4).

Megraud Francis (University of Bordeaux, France) and Lu Hong (Shanghai Jiao Tong University, China) were very influential in H. pylori eradication research during the period 2020–2023 (Fig. 3, Table 2–4).

Summary

Overall, the analysis across these three periods underscores the evolving nature of researcher collaboration in H. pylori eradication therapy, with increasing clustering and modest gains in network density. Key individuals have consistently emerged as central figures, facilitating collaboration and contributing to the field’s research network, despite ongoing challenges in achieving full network connectivity.

This study examined the co-authorship network in H. pylori eradication research from 2000 to 2023, utilizing data from the WoS Core Collection. The analysis aimed to reveal the collaborative landscape, identify key researchers, and characterize the structure of these networks through both macro-level and micro-level metrics. The findings provide insights into the evolution of research collaboration in this field, highlighting the impact of key contributors and the overall connectivity among researchers.

During the initial period (2000–2009), the co-authorship network in H. pylori eradication research displayed a highly fragmented structure with a total of 1,213 components, suggesting that collaboration among researchers was limited. The network density was notably low at 0.00057, indicating that only 0.057% of possible collaborations were realized. Despite this sparse connectivity, the average clustering coefficient was relatively high at 0.885, implying that when researchers did collaborate, they tended to form tight-knit groups. However, the infinite average distance between nodes underscored the network’s disconnection, with many researchers isolated from the main collaborative clusters.

At the micro-level, Asaka M., Gasbarrini G., and Lam S.K. emerged as key figures based on degree centrality, suggesting that they were frequently involved in collaborative efforts. Closeness centrality highlighted the prominence of Vaira D., Vakil N., and Asaka M., indicating their strategic positions in connecting other researchers within the network. Additionally, betweenness centrality pointed to De Francesco V., Vakil N., and Stolte M. as significant bridges within the network, facilitating communication between otherwise disconnected subgroups. Notably, Asaka M. from Hokkaido University and Vakil N. from the University of Wisconsin played pivotal roles, demonstrating the influential presence of Japanese and American researchers in this period.

In the subsequent decade (2010–2019), the co-authorship network became even more fragmented, with the number of components increasing to 1,505. The network density slightly decreased to 0.00052, continuing the trend of limited connectivity with only 0.052% of potential collaborations realized. However, the clustering coefficient improved to 0.900, indicating a stronger tendency for researchers to form cohesive groups when they did collaborate. Despite this, the network remained largely disconnected, as reflected by the persistent infinite average distance between nodes.

Micro-level analysis revealed that Gisbert J.P., Kim N., and Graham D.Y. were central to the network based on degree centrality, highlighting their extensive co-authorship ties. Researchers like Graham D.Y., Sugano K., and Malfertheiner P. scored high in closeness centrality, making them crucial connectors within the network. In terms of betweenness centrality, Graham D.Y., Kuipers E.J., and Malfertheiner P. stood out as key figures who played significant roles in bridging various subcomponents of the network. The influential roles of Graham D.Y. from Baylor College of Medicine and Malfertheiner P. from Otto von Guericke University were particularly notable, illustrating the central involvement of U.S. and European researchers during this period.

In the most recent period (2020–2023), the co-authorship network continued to exhibit a fragmented network, as indicated by the presence of 935 components. Although this suggests that some progress has been made toward integration, the network remains significantly divided. The network density was calculated at 0.00097, reflecting persistent challenges in forming widespread collaborations, with only 0.097% of potential connections realized. The average clustering coefficient was 0.921, demonstrating a strong inclination for researchers to form clustered groups when collaborative relationships were established. However, the average path length remained infinite, indicating that many researchers were still poorly integrated into the broader network.

At the micro-level, significant contributors identified by degree centrality included Mégraud F., Gisbert J.P., and O’Morain C., highlighting their frequent co-authorships. Closeness centrality analysis indicated that Lu H., Mégraud F., and Graham D.Y. were particularly effective in maintaining proximity to other researchers, enhancing their influence within the network. In terms of betweenness centrality, researchers like Lu H., Mégraud F., and Yamaoka Y. were crucial in linking disparate sections of the network, thereby facilitating broader collaborative interactions. The prominence of Lu H. and Mégraud F. emphasized the growing contributions of Asian and European researchers in the latest phase of H. pylori eradication research.

The analysis reveals several important trends in the collaborative landscape of H. pylori eradication research over the past two decades. Despite improvements in clustering and some reduction in fragmentation, the overall low network density and infinite average distances suggest that the field remains highly compartmentalized, with many researchers operating in isolated groups. Key figures such as Mégraud F., Graham D.Y., and Lu H. have played central roles in their respective periods, acting as pivotal connectors and influential contributors to the field.

These findings underscore the need for enhanced collaboration strategies to bridge gaps within the network and foster greater integration among researchers. Efforts to promote interdisciplinary and international collaborations could help overcome the current limitations, facilitating more cohesive and productive research environments. By identifying key researchers and collaborations, this study provides a foundation for targeted initiatives to strengthen the global research network in H. pylori eradication, ultimately contributing to the development of more effective and innovative treatment strategies.

The co-authorship network analysis of researchers in H. pylori eradication therapy from 2000 to 2023 reveals a landscape characterized by evolving collaboration patterns, increasing clustering, and persistent challenges in achieving cohesive network connectivity. Throughout the three analyzed periods (2000–2009, 2010–2019, and 2020–2023), the network exhibited significant fragmentation, as evidenced by the high number of components and low network density. However, a gradual increase in the clustering coefficient suggests an improving tendency for researchers to form cohesive groups when collaborating.

In the 2000–2009 period, the network was highly fragmented, with a network density of just 0.00057, meaning only 0.057% of potential collaborations were realized. The network's structure was dominated by numerous small, disconnected components, totaling 1,213, and the average path length was infinite, indicating limited direct connections among researchers. Key figures such as Asaka Masahiro (Hokkaido University, Japan) and Vakil Nimish (University of Wisconsin, USA) emerged as influential, playing central roles in facilitating collaborations. Their high degree and betweenness centralities underscored their importance in connecting disparate groups within the network, despite its overall disjointed nature.

From 2010 to 2019, the network's fragmentation slightly worsened, with the number of components rising to 1,505 and network density declining to 0.00052. Nevertheless, the clustering coefficient increased to 0.900, suggesting a higher propensity for researchers to cluster together when collaborative relationships were formed. Prominent researchers during this period included Graham David Y (Baylor College of Medicine, USA) and Malfertheiner Peter (Otto von Guericke University, Germany), who exhibited high degree and betweenness centralities, indicating their roles as pivotal connectors in the network. These findings highlight the ongoing importance of specific researchers in maintaining collaborative links, even as the network struggled with overall connectivity.

The most recent period, 2020–2023, showed signs of improvement in network connectivity, with the number of components reducing to 935 and the network density increasing to 0.00097, reflecting a modest rise in collaborative links. The clustering coefficient further improved to 0.921, denoting enhanced group formation among researchers. Noteworthy contributors during this time included Mégraud Francis (University of Bordeaux, France) and Lu Hong (Shanghai Jiao Tong University, China), who played central roles in the network, as indicated by their high degree, closeness, and betweenness centralities. Their strategic positions enabled them to act as critical nodes in the dissemination of research and collaboration within the field.

Overall, the findings from this study underscore the critical roles of key individuals and clusters in driving collaborative research in H. pylori eradication therapy. Despite improvements in clustering and modest gains in network density, significant challenges remain in achieving a fully connected and cohesive research network. The insights from this analysis highlight the need for targeted efforts to enhance collaboration, including fostering new partnerships, reducing barriers to international cooperation, and promoting the integration of underrepresented research groups. Such initiatives are essential for addressing complex challenges, such as antibiotic resistance, and advancing the field of H. pylori eradication therapy on a global scale.

H. pylori, Helicobacter pylori; WoS, Web of Science; MALT lymphoma

Funding statement: none

Conflict of interest disclosure statement: none

Ethics approval statement: not applicable for this article.

Kwok A, Lam T, Katelaris P, Leong RW (2008) Helicobacter pylori eradication therapy: indications, efficacy and safety. Expert Opin Drug Saf 7(3):271–281
Hu Y, Zhu Y, Lu NH (2020) Recent progress in Helicobacter pylori treatment. Chin Med J (Engl) 133(3):335–343
O'Connor JP, Taneike I, O'Morain C (2009) Improving compliance with helicobacter pylori eradication therapy: when and how? Th Adv Gastroenterol 2(5):273–279
Hafeez M, Qureshi ZA, Khattak AL, Saeed F, Asghar A, Azam K, Khan MA (2021) Helicobacter Pylori Eradication Therapy: Still a Challenge. Cureus 13(5):e14872
Wasserman S, Faust K (1994) Social network analysis: Methods and applications. Cambridge University Press. https://doi.org/10.1017/CBO9780511815478
Newman M (2001) Scientific collaboration networks. II. Shortest paths, weighted networks, and centrality. Phys Rev E 64(1):016132
Newman ME (2001) The structure of scientific collaboration networks. Proc Natl Acad Sci USA 98(2):404–409
Barabasi AL, Albert R (1999) Emergence of scaling in random networks. Science 286(5439):509–512

Tables 1 to 4 are available in the Supplementary Files section.

The authors declare no competing interests.

Table1.xlsx
Network Metrics
Table2.xlsx
Top 20 Nodes by Degree Centrality
Table3.xlsx
Top 20 Nodes by Closeness Centrality
Table4.xlsx
Top 20 Nodes by Betweenness Centrality

Download PDF

Version 1

posted

You are reading this latest preprint version

Unlocking Future Research Strategies: Key Collaborations and Network Characteristics in Helicobacter Pylori Eradication Therapy (2000-2023)

Status:

Version 1

Abstract

Aim

Method

Result

Conclusion

Figures

Introduction

Material and methods

Macro-level Metrics:

Micro-level Metrics:

Results

2000–2009 Network Analysis

2010–2019 Network Analysis

2020–2023 Network Analysis

Summary

Discussion

Conclusion

Abbreviations

Declarations

References

Tables

Additional Declarations

Supplementary Files

Status:

Version 1