Mapping the evolution and frontiers of Translational Lung Cancer Research: a bibliometric analysis and literature review

Introduction

Background

The Translational Lung Cancer Research (TLCR) is an internationally recognized, peer-reviewed journal dedicated to the early detection, diagnosis, treatment, and prevention of lung cancer and pulmonary diseases. Aiming to bridge the gap between research and clinical application, TLCR fosters the timely exchange of ideas among experts and delivers a well-structured, informative, and inspiring journal for readers seeking in-depth knowledge on lung diseases. TLCR is the official publication of the Society for Translational Medicine (STM), supported by the Spanish Lung Cancer Group and the Brazilian Society of Thoracic Surgery. Professor Yong Song, a renowned expert in respiratory medicine, served as the position of Editor-in-Chief. The inaugural edition was released in March 2012 (1), followed by two additional quarterly publications within the same year. Starting in February 2013, TCLR has been publishing bimonthly, and from 2021 onwards, it has been published monthly. Under AME Publishing Company, thirteen volumes have been published, with one volume released annually. Additionally, 46 special series have been published in TLCR. Despite its relatively short history, TLCR has demonstrated high academic impact, ranking in the top 36% (Q2) of Medicine: Oncology journals according to the Scimago Journal Rank (SJR).

Rationale and knowledge gap

Bibliometric analysis of the publications can elucidate the knowledge structure and development patterns with specific journals (2). The practice of bibliometrics has significantly advanced with the use of computer-assisted statistics and software (3), enabling the summarization of journal contributions and cooperation patterns, as well as the analysis of large quantities of scholarly publications (4). Without thinking about the research object and more about the result value for the field, many studies now use bibliometric software to analyze specific high-level journals. In addition, analyzing a specific high-impact journal allows for a more detailed understanding of its contribution to the field, highlighting key research themes, influential publications, and collaboration patterns within the journal’s scope. For instance, Bamel et al. conducted a retrospective bibliometric analysis of the European Journal of Innovation Management from 1998 to 2021 (5). Donthu and colleagues conducted a bibliometric analysis for the 30 years of the Journal of Product and Brand Management (6). Nath et al. examined publications in Community Dentistry and Oral Epidemiology from 1973 to 2022 (7).

Given TLCR’s leading role in lung cancer research, a bibliometric analysis of the journal provides valuable insights into the field’s knowledge framework. It offers readers, editors, reviewers, and researchers a clearer understanding of the current scope, key contributors, emerging topics, and shifting research priorities.

Objective

The purpose of this study was to retrospectively review TLCR’s productivity, impact, emerging knowledge, and contribution to lung cancer research. Through analyzing publication and citation patterns, influential authors, institutions, and nations associated with TLCR were identified. Additionally, keyword analysis was conducted to uncover prevailing research topics and their evolution using CiteSpace, VOSviewer, and the R package Bibliometrix. We present this article in accordance with the Narrative Review reporting checklist (available at https://tlcr.amegroups.com/article/view/10.21037/tlcr-24-653/rc).

Methods

Search strategy

Publications from March 2012 to June 2024 were obtained from the Scopus database, PubMed, and Web of Science Core Collection (WoSCC) on June 30, 2024, using the search term ‘Translational Lung Cancer Research’ in the source title. All TLCR publications within this timeframe were included for analysis. The investigation was conducted independently by two researchers (Table S1).

Data extraction

The TLCR publications were collected and retrieved in Comma Separated Values (CSV) format from Scopus, PubMed, and WoSCC. The retrieved data were converted to text file (TXT) format using CiteSpace 6.3. R1 Advanced for further analysis. Bibliometric analysis of the selected studies was performed using CiteSpace 6.3.R1 Advanced, VOSviewer 1.6.19, and the Bibliometrix 4.1.2 package in R. The analysis covered publications from March 2012 to December 2023. Publications from 2024 were excluded from the main analysis due to incomplete citation data, which could lead to potential bias.

Analysis tools

CiteSpace 6.3.R1 Advanced (8) was used to conduct co-citation analysis of authors and references, as well as to identify citation bursts for keywords and authors. Link strength was measured using the cosine method, with analysis confined to each time slice. The g-index with a value of k=25 was applied for selection, and network pruning was carried out using algorithms for slicing and minimum spanning tree pruning.

VOSviewer (9) (version 1.6.19) was employed for collaboration network analysis (including countries, institutions, and authors) and to determine keywords’ co-occurrence. The LinLog/modularity (this method is used for clustering items in a network, such as terms, citations, or co-authorships, which serves to detect communities or clusters within the network by optimizing a modularity-based quality function) method was applied in VOSviewer for this analysis.

The R package Bibliometrix (10) (version 4.1.2) was utilized to compute Lotka’s law (Lotka’s Law is a principle in bibliometrics that describes the frequency of publication by authors in a specific field, which is often used to analyze the productivity of researchers and to model the distribution of publications) and the ratio of publications across multiple countries. Visualization included collaborative globe maps of countries, production trends of countries over time, three-field plots, thematic analysis of terminology, and trending subjects of keywords.

Results and future direction

Study characteristics

The study workflow, from the search strategy to data processing, is depicted in Figure 1. A total of 2,032 publications from TLCR were included, covering the period from 2012 (n=50, 2.4%) to 2023 (n=227, 11.2%). The most common publication types were original articles (48.3%), reviews (28.1%), and editorials (12.3%) (Figure 2A). Since 2017, there has been a notable increase in annual publication volume, although a decline occurred in 2022 (n=229, 11.26%), likely due to coronavirus disease 2019 (COVID-19) research disruptions (11). The journal’s annual growth rate was 14.86%, and the average citations per year mirrored the publication output, reflecting the high quality of papers in TLCR (Figure 2B). Furthermore, the impact factor (IF) of TLCR steadily rose from 4.806 in 2018 to 6.498 in 2020, underscoring its growing prominence and international recognition (Figure 2C). Although the IF of TLCR appears to have declined since its peak in 2020, this trend may be partly explained by changes in the Journal Citation Reports’ (JCR) IF calculation method. In 2021, JCR revised its calculation approach, which could have temporarily inflated IFs across journals, leading to a peak that was not sustained in subsequent years. The observed decrease could thus represent a return to a more stable and realistic IF as the calculation method stabilizes. This explanation aligns with trends observed in other journals during the same period, suggesting that the fluctuation is not unique to TLCR but is part of a broader adjustment in IF metrics. While the IF of other journals generally decreased in 2023, the IF of TLCR did not decrease, indicating the journal’s high standards for paper quality. The average number of citations per document was 14.65, showcasing the high quality of papers.

Figure 1 Flow chart of literature data retrieval and processing analysis.

Figure 2 Study characteristics (A), annual publications (B), and impact factor (C) of Translational Lung Cancer Research.

Country analysis

A total of 44 countries contributed to publications in TLCR. The top ten countries of corresponding authors, ranked by publication count, are listed in Table 1 and shown in Figure 3A. China had the highest number of publications (n=587, 28.8%), followed by the USA (n=389, 19.14%) and Japan (n=137, 6.74%). The prominence of these countries in TLCR research can be attributed to research funding and infrastructure, and high disease burden. Over time, China and the USA saw a more rapid increase in publication volume compared to other countries (Figure 3B). The USA (n=7,676), China (n=6,655), and Spain (n=2,264) were the top three most cited countries (Figure 3C). High citation counts often indicate influential research that significantly contributes to the field, stemming from robust academic networks and impactful findings originating from these countries. According to the countries’ collaboration world map (Figure 3D), China and the United States (n=162) had the closest cooperation, followed by China and Italy (n=112), China and Japan (n=95). The United States had the highest centrality (n=0.27), followed by Spain (n=0.22) and China (n=0.18). These collaboration patterns may arise from historical ties, joint funding initiatives, and shared research interests, which facilitate productive partnerships. Furthermore, an analysis of corresponding authors’ countries showed that the top three countries with the highest proportion of multiple-country publications (MCP_ratio) were China (48.2%), Germany (29.5%), and the United Kingdom (29.5%) (Table 1). The high MCP_ratio in China indicates a strong emphasis on this specific theme, likely driven by strategic research priorities and initiatives targeting lung cancer.

Figure 3 Analysis of countries engaged in publications in Translational Lung Cancer Research. (A) Countries’ co-occurrence map; (B) top 10 countries with the most significant number of publications over time; (C) top 20 most cited countries; (D) countries’ collaboration world map.

Institution analysis

A total of 2,898 institutions contributed to the publications in this study. The top 10 institutions, ranked by publication count, are shown in Figure S1. The leading institutions were Shanghai Jiao Tong University (n=127, 6.25%), Fudan University (n=111, 5.46%), and Tongji University (n=108, 5.31%). The top three institutions are all from Shanghai, China, which shows that Shanghai pays great attention to lung cancer-related research. Regarding publication trends over time (Figure S2), Peking University has experienced a notable increase in publication rate since 2018, outpacing other institutions. The overlay visualization of institutional departments (Figure S3) shows that early publications were primarily from the Department of Thoracic Surgery. However, starting in 2020, there was increased collaboration with other departments, including Oncology, Radiation, and Pulmonary Disease. This demonstrates that the entire medical process of lung cancer prevention, clinical treatment, and treatment requires multidisciplinary participation and cooperation. To better explore the connections between institutions, key countries, and keywords, Figure 4 illustrates a three-field plot. At present, institutions in leading countries, including China, the USA, and Japan, predominantly concentrate on non-small cell lung cancer (NSCLC). Furthermore, basic research is mainly centered around cellular-level immunotherapy.

Figure 4 Three-field plot analysis of institutions engaged in publications in Translational Lung Cancer Research.

Author analysis

Between 2012 and 2023, a total of 6,250 authors contributed to the publication of TLCR literature. The top three productive authors were Jianxing He (n=75) from the First Affiliated Hospital of Guangzhou Medical University, Yong Song (n=68) from Nanjing Medical University, and Yang Zhang (n=67) from Fudan University Shanghai Cancer Center (Figure S4). Jianxing He’s primary research focused on clinical (12-14) and basic research (15,16) related to NSCLC, as well as promoting the standardization of lung cancer treatment (17-19). According to the authors’ local impact analysis (Table 2), Rafael Rosell had the highest H-index (n=20), followed by Yong Song (n=19) and Karachaliou N (n=16). A deeper analysis of total citations revealed that the three most cited authors were Yong Song (1,248 citations), Rafael Rosell (1,119 citations), and Chengzhi Zhou (985 citations). Figure S5 depicts the co-authorship network of authors and their collaboration strength, with Song Yong leading in centrality (n=0.19), followed by Jiang Gening (n=0.17) and Chen Chun (n=0.16). The time overlay visualization indicates that Nike Karachalicu, Rafael Rosell, Yong Song, and Tangfeng Lv have significantly contributed to TLCR, with Xu Ke, Ahn Myung-Ju, and Lee Sang Hoon being the more active authors in the past two years (Figure 5).

Figure 5 Authors’ time-density map.

Journals, authors, and references cited by TLCR

Analyzing journals, authors, and references frequently cited articles is meaningful because it helps to identify the most influential research that has shaped the field of lung cancer. A comprehensive analysis was conducted on the journals, authors, and references most frequently cited by TLCR between 2012 and 2023. Excluding self-citations, the top journals referenced by TLCR were Journal of Thoracic Oncology (1,330 citations), Journal of Clinical Oncology (1,227 citations), and New England Journal of Medicine (1,205 citations) (Figure S6). The most frequently cited authors were Martin Reck (n=267), Roy S. Herbst (n=235), and Tony S Mok (n=169). In terms of centrality analysis, Denise R. Aberle (n=0.12) has the highest centrality, followed by Jean-Pierre Pignon (n=0.10) and Alice T. Shaw (n=0.09) (Figure S7). Cluster analysis of the references cited by TLCR identified 20 clusters (Figure 6). The most cited article was ‘Pembrolizumab plus Chemotherapy in Metastatic Non-Small-Cell Lung Cancer’ in cluster 4 (n=93) (20), followed by ‘Global cancer statistics 2018: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries’ in cluster 3 (n=92) (21), and ‘Pembrolizumab versus docetaxel for previously treated, PD-L1 positive, advanced non-small-cell lung cancer (KEYNOTE-010): a randomised controlled trial’ in cluster 1 (n=91) (22).

Figure 6 A timeline view of cited references by Translational Lung Cancer Research.

Most frequently cited studies of TLCR

Table 3 presents the top ten highly impactful articles published by TLCR. The most frequently cited studies between 2012 and 2023 offer significant insights into the treatment and understanding of lung cancer. The top-cited article, by Shaker A. Mousa [2016], with 1,251 citations, discusses current treatments and future advances for NSCLC, emphasizing the role of biomarker testing in improving patient survival (23). Another highly cited work by Brett G. M. Hughes [2014], with 601 citations, reviews targeted therapies for NSCLC, focusing on oncogenic drivers and the development of targeted agents (24). Additionally, de Groot’s [2018] study on lung cancer epidemiology, cited 459 times, highlights the long-term effects of tobacco smoking and raises concerns about the potential impacts of marijuana smoking and e-cigarette vaping (25). These studies, among others, have significantly contributed to the field by addressing treatment strategies, recurrence, immune-related toxicities, global trends in mortality, and mechanisms of resistance, reflecting the broad scope and critical importance of ongoing research in lung cancer.

Keywords co-occurrence analysis

Keyword co-occurrence is a valuable bibliometric tool for identifying trending topics in scientific research. We analyzed the frequency of keyword occurrences in the field to explore current areas of focus (Figure S8). Papers published in TLCR predominantly focused on aged NSCLC adults (n=879), with a significant emphasis on overall survival (n=507), cancer staging (n=406), and cancer immunotherapy (n=324). The most common types of studies published in TLCR were controlled studies (n=477), major clinical studies (n=470), and retrospective studies (n=319) (Figure S9). Moreover, 14 distinct clusters were generated using the log-likelihood ratio to analyze co-occurring keywords (Figure 7). The largest cluster (#0) has 89 members and a silhouette value of 0.782, labelled as non-small cell lung cancer. The major citing article of the cluster is: Osimertinib versus comparator first-generation epidermal growth factor receptor tyrosine kinase inhibitors as first-line treatment in patients with advanced EGFR-mutated non-small cell lung cancer: a Chinese, multicenter, real-world cohort study (33), which was authored by Dongming Zhang in 2023. Other significant clusters include tolerability safety (#1), differential diagnosis (#2), lung adenocarcinoma (#3), radiotherapy outcomes (#4). video-assisted thoracic surgery (#5), advanced NSCLC (#6), lung cancer (#7). Smaller clusters delve into specific areas such as anti-angiogenic therapy (#10), malignant pleural mesothelioma (#11), receptor-mutated NSCLC (#12), and lysosomal gene (#13), underscoring the comprehensive and multifaceted nature of TLCR’s contributions to lung cancer research.

Figure 7 Keywords clusters map.

Changes in trends of research of TLCR

Changes in publication trends in the TLCR were explored using thematic terminology analysis (Figure 8A). Basic themes: the primary themes of “non-small cell lung cancer”, “overall survival”, and “cancer survival” indicate a strong focus on the most common type of lung cancer and the key metrics for assessing treatment effectiveness and patient outcomes (34,35). Motor themes: themes such as “cancer surgery”, “computer-assisted tomography”, “progression-free survival”, and “drug efficiency” reflect advancements in surgical techniques, imaging technologies, and the importance of measuring how long patients live without their disease progressing, as well as the efficacy of various treatments (36-38). Emerging or declining themes: the identification of themes like “unclassified drug” and “protein expression” suggests areas of ongoing exploration and potential challenges in drug classification, as well as a waning focus on specific protein markers that were previously considered important in cancer research (39,40). Potential future development trends (Figure 8B): the mention of “first-line treatment” and “ensartinib” as potential future trends highlights the ongoing evolution in treatment protocols, particularly emphasizing the importance of novel therapies and their positioning in initial treatment regimens for lung cancer (41,42). Top keywords with strongest citation bursts (Figure 8C): the keyword “review” (burst strength =64.08, 2012–2018) having the strongest citation burst since 1999 points to the increasing importance of summarizing and synthesizing existing research to inform clinical practice, while the recent burst of “data analysis software” indicates a growing reliance on computational tools for analyzing cancer data, reflecting advancements in research methodologies.

Figure 8 Hotspots and trends analysis. (A) Thematic evolution map; (B) trend topics; (C) top 30 keywords with the strongest citation bursts.

The most recently published articles in 2024 of TLCR

The articles published in TLCR in 2024 highlight significant advances in lung cancer treatment, particularly focusing on immunotherapy and the tumor microenvironment. The most central topics include PD-L1, which plays a crucial role in the immune response against tumors, and nivolumab, an immune checkpoint inhibitor that has shown promise in treating NSCLC (43). Other key topics include ‘Immune Checkpoint Inhibitors’, ‘Tumor Microenvironment’, and ‘Carboplatin’. These topics underscore a concerted effort to enhance lung cancer treatment through a deeper understanding of immune mechanisms, the tumor microenvironment, and the development of effective combination therapies. The focus on central themes like PD-L1, immune checkpoint inhibitors, and tumor mutational burden reflects ongoing efforts to personalize and improve lung cancer care.

Comparison of this study with other bibliometric studies

We compared our study’s results with other bibliometric articles in the lung cancer field, finding both similarities and distinctions. Our study and the other articles all show a steady rise in lung cancer research output, with China consistently leading in contributions, particularly from institutions like Shanghai Jiao Tong University (44,45). However, other studies emphasize the higher citation impact of U.S. publications, reflecting a difference in academic influence (46,47).

Common research themes include immunotherapy, treatment strategies, and resistance mechanisms. Both our study and others note a growing interest in AI and machine learning. A key distinction is our focus on older adults with NSCLC, which is less prominent in other studies.

For future directions, our study suggests prioritizing first-line treatments, ensartinib, and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis, while others highlight “heterogeneity and subtypes” and “immunotherapy”. Despite these nuances, all studies emphasize precision treatment and innovative technologies.

Strengths and limitations

A notable strength of this study lies in the utilization of advanced bibliometric software, which effectively captured a comprehensive overview of research published in TLCR. This approach allowed for a detailed analysis of the distribution and characteristics of research articles, as well as the identification of prevailing topic trends within this scientific domain. However, there are some limitations in this study. The topic analysis in this study focused solely on author keywords from each paper, which may not fully capture the complexity of the various research areas in surgery. Additionally, the included studies were not subjected to critical appraisal, and the analysis did not assess the societal impact of the research, whether positive, negative, or neutral.

Conclusions

This bibliometric study reviews Translational Lung Cancer Research (TLCR) publications from 2012 to 2024, highlighting a positive trend in output with 2,032 articles up to 2023 and 121 in 2024, despite a recent decline. China leads in contributions, with top institutions and authors driving research. The most cited topics include treatment strategies, recurrence, and immune-related toxicities, reflecting TLCR’s focus on key lung cancer challenges. Future research in TLCR is likely to emphasize first-line treatments, novel therapies like ensartinib, and advanced analysis methods. In conclusion, this study underscores TLCR’s significant contributions to lung cancer research and provides valuable insights into its evolution and future directions.

Acknowledgments

Funding: This study was supported by the National Natural Science Foundation of China (Nos. 32201147 and 82272599), the Natural Science Foundation of Sichuan Province (No. 2024NSFSC1575), and 1.3.5 project for disciplines of excellence, West China Hospital, Sichuan University (No. ZYGD23014).

Footnote

Reporting Checklist: The authors have completed the Narrative Review reporting checklist. Available at https://tlcr.amegroups.com/article/view/10.21037/tlcr-24-653/rc

Peer Review File: Available at https://tlcr.amegroups.com/article/view/10.21037/tlcr-24-653/prf

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://tlcr.amegroups.com/article/view/10.21037/tlcr-24-653/coif). The authors have no conflicts of interest to declare.

Ethical Statement: The authors are accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved.

Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0/.

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