Global insights into lung cancer-related depression and anxiety from 2005 to 2025: a bibliometric analysis

Introduction

Recent International Agency for Research on Cancer (IARC) statistics indicate that lung cancer remains a leading global malignancy and the foremost cause of cancer mortality, with an estimated 2.48 million new cases and 1.81 million deaths annually (1). The average age of lung cancer onset is decreasing, and over 80% of patients are diagnosed at advanced or locally advanced stages (2). Cancer significantly impacts patients’ mental health, often leading to psychological disorders such as anxiety and depression (3-5). Beyond the direct effects of the disease, common lung cancer treatments, including chemotherapy, can induce additional adverse symptoms that compound those caused by the cancer itself. These combined effects can severely impair patients’ quality of life and negatively influence treatment outcomes and survival rates (6,7).

With the transition from the biomedical model to the biopsychosocial model of medicine, growing emphasis has been placed on the role of mental health in tumorigenesis, progression, and metastasis (8). Studies suggest that psychological disorders (e.g., depression and anxiety) play an essential role in lung cancer development and may even contribute to its onset (9,10). Multimodal interventions combining exercise, nutrition, and palliative symptom management, along with various behavioral interventions, have demonstrated efficacy for lung cancer and its associated psychological symptoms (11,12). However, the feasibility and effectiveness of these treatment options depend on patient compliance (13). Psychological barriers among lung cancer patients can impair their decision-making abilities, thereby affecting their cooperation with the diagnostic and treatment process (14,15). Therefore, understanding the interplay between lung cancer and psychological disorders, as well as the factors influencing mental health in lung cancer patients, is essential for improving cancer prevention, disease management, and psychological interventions. In recent years, research on lung cancer-related depression and anxiety has gained momentum. However, no comprehensive study has systematically analyzed the state-of-the-art and novel trends shaping ongoing research.

Bibliometric analysis serves as a systematic and contemporary tool used to evaluate publications within a specific research field over a defined time period. It examines various parameters, including the number of articles, authors, countries/regions, journals, keywords, and references (16,17). Previous studies have applied bibliometric methods to explore the relationship between depression and cancers such as breast and digestive cancers, summarizing the current research landscape and emerging hotspots in these fields (18-20). These studies not only provided researchers with valuable insights into the evolution of a field but also facilitated cross-disciplinary collaboration, global partnerships, and the advancement of knowledge. Additionally, they supported healthcare professionals in remaining up to date with current therapeutic developments, ultimately enhancing clinical practices. As a result, bibliometric analysis has become a critical instrument in contemporary scientific investigation.

At present, there is a significant gap in bibliometric studies examining publication trends, research characteristics, and emerging hotspots associated with depression and anxiety in lung cancer. This study aimed to address this gap by analyzing research trends and hotspots in lung cancer-associated depression and anxiety from 2005 to 2025. By providing a comprehensive overview of the field over the past two decades, this analysis identifies key developments and potential avenues for future studies. We present this article in accordance with the BIBLIO reporting checklist (available at https://jtd.amegroups.com/article/view/10.21037/jtd-2025-1395/rc).

Methods

Data sources and search strategy

This research analyzed publications from January 1, 2005 to July 31, 2025, extracted from the Web of Science Core Collection (WoSCC) on August 30, 2025. To minimize potential bias due to database updates, all data were extracted and downloaded within one day. The search strategy used was as follows: TS = [(lung cancer) OR (lung neoplasm) OR (lung tumor) OR (lung carcinoma) OR (lung adenocarcinoma)] AND [TS = (depression) OR (depressive disorder) OR (anxiety)] AND [DT = (Article)] AND [LA = (English)]. Only publications indexed in the Science Citation Index-Expanded (SCI-E) were included. The following exclusion criteria were applied: (I) articles unrelevant to lung cancer-related depression and anxiety; (II) document types other than original research articles, including reviews, book chapters, conference proceedings, letters, editorials, news items, meeting abstracts, corrections, and retracted publications; (III) non-English publications; (IV) duplicate publications. To guarantee the reliability of the bibliometric analysis, three independent researchers (F.W., Y.Y.Z. and Z.Y.L.) manually reviewed all retrieved publications, verifying titles, author names, publication years, and abstracts. The final dataset was downloaded as full-record data files from WoSCC. The comprehensive screening process is displayed in Figure 1.

Figure 1 Study selection flowchart.

Bibliometric analysis

The WoS database (http://wcs.webofknowledge.com) was utilized to identify and analyze all publications related to lung cancer-associated depression and anxiety. The search results were processed to generate histograms illustrating publication trends. All relevant information from the WoSCC was exported in TXT format and subsequently analyzed with VOSviewer (v1.6.19) and CiteSpace (v6.1.R6) for bibliometric mapping. Additionally, the data were analyzed using the “bibliometrix” R package and the bibliometric online analysis platform (BOAP; https://bibliometric.com).

The annual publication count was extracted from WoSCC, while data on the top 10 most productive areas/countries and the ten most frequently cited journals were obtained from the BOAP. International as well as inter-author collaboration patterns were assessed using VOSviewer, which enables the construction of bibliometric network maps (21). To further analyze the research landscape of lung cancer-related depression and anxiety, we employed CiteSpace (22), a widely used bibliometric visualization tool, to evaluate institutional collaborations, reference co-citations, and keyword citation bursts. This analysis provided insights into the current research status and helped forecast emerging research hotspots within this field.

Results

Publication volume and temporal trend analysis

From the SCI-E database within WoSCC, 289 articles that met the inclusion criteria were retrieved. The annual publication count is shown at the top of the bars in Figure 2A. Studies on lung cancer-related depression and anxiety was divided into two distinct periods based on publication trends: (I) 2005–2018: a steady rise in the number of publications; (II) 2019–2025: a significant surge in research output. Additionally, we classified the retrieved studies into two categories: research examining lung cancer as a cause of depression or anxiety; research investigating the effect of depression or anxiety on lung cancer. The majority of studies focused on the former category (Figure 2B). To model publication growth trends, Microsoft Excel 2021 was used to fit a polynomial function: f(x)=0.0506x² − 202.43x + 202,544 (R²=0.7866), predicting that approximately 45 articles will be published by 2030 (Figure S1).

Figure 2 Assessment of publication volume and research trends on lung cancer-related depression and anxiety [2005–2025]. (A) Annual publication count of research articles on lung cancer-associated depression and anxiety, retrieved from the WOS database. (B) Proportion of articles published from 2005 to 2025 investigating lung cancer as a cause of depression or anxiety versus depression or anxiety affecting lung cancer. (C) Publication volume and growth trends for the top 10 regions/countries in lung cancer-related depression and anxiety research, based on data from the BOAP. (D) Total citation count of the 289 retrieved articles, categorized by country/region. BOAP, bibliometric online analysis platform; WOS, Web of Science.

Using the BOAP (http://bibliometric.com/), we identified the leading countries/regions in lung cancer-related depression and anxiety studies between 2005 and 2025. The top 10 countries with the greatest publication counts are presented in Figure 2C. Until 2017, the USA led research output in this field, but China surpassed the USA in annual publications and has maintained its lead since then. We further assessed the total citation counts of publications originating from each region/country (Figure 2D). The USA led with 2,645 citations, followed by China with 1,542 citations. To assess research impact, we calculated the mean number of citations per article (total citations divided by total articles) for each country/region. The top 10 countries/regions based on this metric are presented in Table 1, with Mexico (80.00 citations per article), Scotland (52.67 citations per article), England (45.50 citations per article) ranking as the top three.

Analysis of collaborating institutions and countries/regions

Between 2005 and 2025, a total of 289 articles on lung cancer-related depression and anxiety were published across 38 regions/countries. VOSviewer was used to assess international academic collaborations. As depicted in Figure 3A, each circle denotes a country or region, with the circle size reflecting the publication count and the lines between circles indicating collaborations between countries. The thickness of these lines represents the collaboration’s strength. The results showed that the USA was the leading country in global research collaborations, with the strongest partnerships observed between the USA and China, followed by the USA and England.

Figure 3 Cooperative networks among countries, regions, and institutions in lung cancer-related depression and anxiety research. The circles in this figure denotes various institutions and countries/regions, with the circle size reflecting the publication count, and the link’s thickness indicating the strength of cooperation between them. (A) Collaborative relationships among 38 regions/countries in assessing lung cancer-related depression and anxiety. (B) Map of institutional collaborations in lung cancer-associated depression or anxiety research, highlighting the 10 leading institutions in terms of productivity.

To further examine institutional collaborations, data in TXT format were imported into CiteSpace, revealing that 292 research institutions contributed to studies on lung cancer-related depression and anxiety. The ten leading institutions in research output are visualized in Figure 3B, where each concentric circle denotes an institution, with its size corresponding to the publication count and the connecting line thickness reflecting the intensity of collaborative relationships. Among these institutions, 10 had more than seven publications, with Harvard University (Washington, DC, USA) leading the field with 17 articles. Notably, eight of the top ten high-output institutions were US-based, indicating its dominant academic impact in this research area.

Co-authorship network analysis and core-author mapping

Through examination of author collaboration patterns within a given research area, it is possible to identify core authors and assess the degree of their interconnectivity (23). In this study, 1,699 authors published 289 articles on lung cancer-related depression or anxiety published between 2005 and 2025. Figure 4 illustrates the author collaboration network, where the node and font sizes increase with the number of publications, and the line’s thickness reflects the intensity of collaborative efforts between authors. The visualization map offers a clear representation of author collaborations, assisting researchers in identifying potential collaborators. Daniel C. McFarland, from University of Rochester Medical Center (Rochester, NY, USA), contributed the largest article count (n=9). The network visualization indicated active collaboration between highly productive authors and other contributors in the field.

Figure 4 Author collaboration network in lung cancer-related depression and anxiety research. This figure displays the co-authorship network within the field of lung cancer-related depression and anxiety. Each circle symbolizes an author, and the connections between circles denote collaborative relationships. Font size corresponds to the publication volume of each author.

Journal analysis

The BOAP was utilized to evaluate the influence of journals in the field. Table 2 lists the ten journals with the highest citation counts, with Psycho-Oncology leading with 1,048 citations, followed by Supportive Care In Cancer (532 citations), Journal of Clinical Oncology (451 citations), Journal of Pain And Symptom Management (417 citations), European Journal of Oncology Nursing (238 citations), European Journal of Cancer Care (185 citations), Lung Cancer (144 citations), Medicine (113 citations), Integrative Cancer Therapies (89 citations), and BMJ Supportive & Palliative Care (71 citations). Notably, 7 out of the 10 leading journals are based in the USA. Furthermore, the Journal of Clinical Oncology achieved the greatest average citation count per publication (112.75 citations). These results highlight the significant academic impact and esteemed reputation of this long-standing, internationally recognized journal.

Analysis of literature co-citation

Literature co-citation is a technique employed for identifying articles that are cited together by a group of authors. In this approach, each node denotes a reference, and the connecting lines between nodes indicate that these papers were co-cited within the set of 289 articles analyzed (Figure 5A). The node size is directly proportional to the citation frequency, while wider edges between nodes suggest a greater intensity of co-citation. Additionally, red nodes highlight documents with increased citation frequency over the past few years, while purple nodes signify earlier citations. The number of citations is a crucial indicator of an article’s impact within a particular research area. Table 3 presents the ten most cited references among the 289 articles. The most-cited article, published in Acta Psychiatrica Scandinavica by Zigmond et al., achieved the highest rank with 69 citations. This study introduced a self-assessment scale capable of reliably diagnosing anxiety or depression in a hospital outpatient setting (24). The second and third most-cited publications, appearing in the Journal of Clinical Oncology and Annals of Surgical Oncology, had citation counts of 58 and 34, respectively. The former highlighted the high prevalence and persistence of depression in lung cancer cases, particularly those experiencing more serious symptoms, emphasizing the significance of incorporating psychological assessments and interventions into palliative care (25). The latter study found that one-third of newly diagnosed non-small cell lung cancer (NSCLC) patients experienced depression and anxiety, with these mental health conditions being independently associated with treatment compliance and unfavorable prognosis (26).

Figure 5 Reference co-citation network analysis of articles related to lung cancer-related depression and anxiety, published from 2005 to 2025. (A) CiteSpace co-citation network of 7,258 references concerning lung cancer-associated depression and anxiety. Each node represents a reference, with larger nodes indicating higher citation counts. Connections between nodes signify co-citation within the same article. More intense red nodes highlight recently frequent citations, whereas deeper purple nodes represent older references. The publication year and lead author of the 13 most-cited studies are displayed. (B) The 25 most influential references exhibiting the highest citation bursts regarding lung cancer-related depression and anxiety from 2005 to 2025. The blue bars represent the publication years, while the red bars highlight the periods of citation bursts.

Reference citation bursts refer to a sharp rise in citation count, typically indicating the development or transformation of a research discipline. The greater the intensity of a reference’s citation surge, the more significant its impact in the field. The top 25 references with the greatest citation bursts were identified using CiteSpace (Figure 5B). The blue line represents the time frame between 2005 and 2025, while the red line signifies the period during which the reference experienced a citation burst. Among the most recent burst references, the most notable and highly cited paper was a meta-analysis published in Molecular Psychiatry in 2020. This citation burst started in 2022 and persisted until 2025. The meta-analysis systematically assessed the relationship between anxiety and depression, as determined by symptom assessments or clinical diagnoses, and their impact on cancer prevalence, cancer-specific death rates, and overall mortality among cancer cases. The study found that anxiety and depression were markedly associated with an elevated risk of morbidity and cancer-specific mortality for several cancers, including lung cancer, as well as an elevated risk of overall mortality among lung cancer cases (27). These findings emphasize the critical importance of timely identification and targeted management of anxiety and depression in both cancer cases and the general population, with profound implications for public health and clinical practice.

Evaluation of research trends and keyword burst analysis

Keyword co-occurrence analysis (Figure 6A) highlights the 40 most frequent keywords used in studies related to lung cancer-associated depression and anxiety. The font size of each keyword corresponds to its frequency of usage. After removing less relevant terms, the following high-frequency keywords were retained: depression, anxiety, lung cancer, and quality of life. Keyword burst detection serves as an effective approach for identifying emerging research hotspots. Figure 6B displays the 15 keywords with the highest citation surge between 2005 and 2025. The green line denotes the time span of the entire study period [2005–2025], while the red line signifies the periods during which the burst in keyword frequency occurred. Among the keywords exhibiting recent bursts, “fatigue” (2.85), “stress” (2.99), and “NSCLC” (2.31) were identified as significant new focal points in the field.

Figure 6 Assessment of keywords and burst detection in papers on lung cancer-related depression and anxiety, published between 2005 and 2025. (A) Co-occurrence of the top 100 most common (≥5 occurrences) keywords in studies on lung cancer-related depression and anxiety. (B) The 15 keywords with the highest citation surge (ranked by their onset year). Red bars reflect a sharp rise in usage during the respective period, whereas blue bars indicate periods of lower frequency.

Discussion

This research presents the first bibliometric analysis of publications on lung cancer-related depression and anxiety from 2005 to 2025. Our findings indicate a substantial rise in research output over the past 6 years. Bibliometric and visual analyses identified the USA as the leading contributor, with Harvard University as the most influential institution and Daniel C. McFarland as the most prominent researcher in the field. Keyword burst detection highlighted “fatigue”, “stress”, and “non-small cell lung cancer” as emerging research hotspots. We hope that this analysis provides critical guidance to policymakers for formulating targeted research funding and healthcare strategies, supports researchers in discovering new research avenues, and assists clinicians in staying updated on emerging therapeutic methods to improve clinical practice.

From 2005 to 2025, the USA and China were the primary contributors to studies on lung cancer-related depression and anxiety. The USA consistently led in total article citations and global research cooperation, with eight of the top 10 most productive research institutions and six of the ten most influential academic journals originating from the country. The results show that the USA exerts significant academic impact in this domain, driven by its strong research infrastructure, well-established regulatory framework, and substantial financial support. China entered the field in 2011 and surpassed the USA in annual publication volume in 2017, now holding the highest total number of publications. However, its total citation counts ranks second, significantly lower than that of the USA. This discrepancy suggests that while China has expanded its research output, further efforts are needed to enhance its academic impact, particularly by increasing the quality and influence of its publications.

With globalization, international collaboration in research has significantly increased, thereby supporting the development of influential publications on public health concerns. In the field of lung cancer-associated depression and anxiety, the USA maintains the strongest research partnerships, particularly with China, followed by collaborations with England. These results suggest the pivotal role of international cooperation in shaping the USA as a key academic hub in this field and driving advancements in research. Given the global burden of depression, further strengthening collaborations among countries and institutions is essential to accelerating progress and improving outcomes in this critical area of study.

The substantial growth in publications in the last six years suggests growing recognition of the impact of anxiety and depression in lung cancer cases. Treatments such as radiation therapy, chemotherapy, and surgery often cause substantial side effects, leading to heightened fear and distress, which may increase the risk of psychological disorders. A comparative prospective non-randomized follow-up study on NSCLC patients examined anxiety and depression in those receiving chemotherapy versus immunotherapy (28). This study provides valuable insights into the psychological changes associated with different treatment modalities and serves as a reference for clinicians in developing treatment strategies that incorporate mental health support. Furthermore, over the past two decades, research has increasingly focused on the effects of negative emotions, such as depression and anxiety, on lung cancer outcomes. Emotional stress is a psychological response to stressors, commonly manifested as depression and anxiety, and is particularly prevalent among cancer patients. Recently, Zeng et al. (29) conducted the first prospective study exploring the relationship between emotional stress and tumor immunotherapy efficacy. Their findings suggest that emotional stress, including depression and anxiety, is closely linked to immunotherapy resistance in lung cancer, indicating the potential significance of psychological interventions in optimizing cancer treatment outcomes.

The most prolific author in the field of lung cancer-associated depression and anxiety is Daniel C. McFarland from the University of Rochester Medical Center (USA). His primary research focuses on cancer-related inflammation and neuropsychiatric symptoms. As a contributor to European Society for Medical Oncology clinical practice guidelines (30), he has emphasized the importance of addressing not only cancer itself but also the patient’s psychosocial well-being. His recommendations advocate for a holistic treatment approach, incorporating psychotropic medications or psychotherapy when necessary to improve treatment compliance and quality of life. McFarland and his team have investigated the roles of inflammation in cancer-related psychiatric symptoms (31), identifying albumin and neutrophil-to-lymphocyte ratios as potential biomarkers for assessing and managing cancer-related depression and anxiety (32). In addition, his research on vitamin D deficiency and depression in metastatic lung cancer patients has introduced new prognostic factors for patient assessment. His findings suggest that clinicians should consider vitamin D levels and mental health status, alongside traditional tumor characteristics, to make more accurate prognostic evaluations and provide personalized treatment and rehabilitation strategies (33).

Keyword bursts serve as measures of significant research themes and developing trends. The top 25 keyword bursts with the highest citation counts are presented in Figure 6B, covering the entire 2005–2025 period, reflecting the dynamic evolution of research interests. Among the most recent keywords, “fatigue” emerged as the strongest burst, beginning in 2020 with an intensity of 2.58. Cancer-related fatigue (CRF) is a prevalent symptom among lung cancer patients, characterized by persistent physical, emotional, or cognitive exhaustion that does not improve with rest, significantly impairing quality of life (34). Recent years have seen notable advancements in the study and clinical management of CRF (35). Studies have linked CRF to inflammatory responses, hypothalamic-pituitary-adrenal axis dysfunction, and metabolic disorders induced by the tumor microenvironment and treatments (36,37). In addition, recent findings suggest that gut microbiota dysbiosis may contribute to fatigue through the gut-brain axis (38). Both non-pharmacological (39,40) and pharmacological (41) interventions have demonstrated efficacy in alleviating CRF and improving quality of life among lung cancer cases. The second and third most recent keyword bursts were “stress” and “NSCLC”, respectively. The emergence of these keywords reflects the growing research interest in the relationship between lung cancer (particularly NSCLC) and emotional stress (depression or anxiety). Substantial advancements have been achieved in elucidating the underlying mechanisms of pathogenesis (42) and clinical management (43,44) of emotional stress in lung cancer patients. Moreover, psychological distress, such as anxiety and depression, are strongly associated with increased mortality in lung cancer patients (45). These psychological factors may influence disease progression and treatment outcomes through mechanisms such as immunosuppression, inflammatory responses, and behavioral changes (29,33,46). Therefore, early identification of psychological barriers in cancer patients is crucial for optimizing treatment outcomes. In recent years, artificial intelligence (AI) has played an indispensable role in healthcare, particularly in diagnostic support, treatment identification, patient health management, and improving healthcare infrastructure (47). Numerous studies indicate that leveraging AI technologies to extract detailed features from medical images can provide powerful assistance in tumor diagnosis, prognosis assessment, and treatment plan formulation (48-50). Overall, these keyword trends suggest that future research will increasingly focus on the impact and underlying biological mechanisms of psychological interventions on cancer treatment outcomes in lung cancer patients with emotional stress (depression or anxiety), particularly those with NSCLC. Additionally, whether AI technology can play a predictive role in the interaction between cancer-related emotional disorders and the disease itself will emerge as another clinically significant research focus. This aligns with the broader shift in medicine from a biomedical approach to a biopsychosocial framework, highlighting the integration of psychological and social factors into cancer care.

Nevertheless, there are few limitations in this study. First, this study relied solely on data retrieved from the WoSCC, as it provided the complete datasets needed for co-citation analysis in CiteSpace, including titles, authors, affiliations, and references. However, this meant that literature from other major databases, such as Ovid, Embase, and PubMed, was excluded, possibly leading to an incomplete sample of studies on lung cancer-related depression or anxiety published between 2005 and 2025. Second, since English is the dominant language in academic publishing, we included only studies published in English. This approach excluded non-English articles, which may contain valuable insights, thus introducing a language bias. Third, citation lag can result in an underestimation of the influence of recently published high-quality research. This limitation highlights the importance of regular updates in future research to capture emerging trends. Additionally, although the number of studies on lung cancer-related depression or anxiety has been growing, the overall volume of literature remains relatively small. As a result, our findings may be influenced by the limited dataset. Future research should aim to address these limitations by incorporating data from multiple databases, including non-English studies, and ensuring ongoing updates to reflect the latest advancements in the field.

Conclusions

This research represents the first bibliometric analysis of articles on lung cancer-related depression and anxiety. Since 2019, the number of publications in this field has increased rapidly, with the USA and China emerging as leading contributors. Future research is expected to focus on the effects and biological mechanisms of psychological interventions on lung cancer patients with depression or anxiety, particularly those with NSCLC. This research provides valuable insights for advancing research on therapeutic strategies and neurobiological mechanisms of lung cancer-associated depression and anxiety.

Acknowledgments

We would like to express our gratitude to EditSprings (https://www.editsprings.cn) for the expert linguistic services provided. We thank the developers of CiteSpace and VOSviewer for providing tools that aided in the analysis.

Footnote

Reporting Checklist: The authors have completed the BIBLIO reporting checklist. Available at https://jtd.amegroups.com/article/view/10.21037/jtd-2025-1395/rc

Peer Review File: Available at https://jtd.amegroups.com/article/view/10.21037/jtd-2025-1395/prf

Funding: This work was supported by the Health and Medical Research Project of Anhui Province (grant No. AHWJ2024Aa20018).

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://jtd.amegroups.com/article/view/10.21037/jtd-2025-1395/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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