PDF (23.6 MB)
Collect
Submit Manuscript
Original Article | Open Access

Visualization analysis of research progress and trends in coexistence of lung cancer and pulmonary tuberculosis using bibliometrics

Ling Yang1,2,3Zhaoyang Ye1Linsheng Li1Li Zhuang1Jingzhi Guan3()Wenping Gong2 ()
Hebei North University, Zhangjiakou, China
Beijing Key Laboratory of New Techniques of Tuberculosis Diagnosis and Treatment, Senior Department of Tuberculosis, The Eighth Medical Center of PLA General Hospital, Beijing, China
Senior Department of Oncology, The Fifth Medical Center of PLA General Hospital, Beijing, China
Show Author Information

Graphical Abstract

View original image Download original image
This Graphical Abstract presents a summary of a bibliometric analysis investigating the current status and future research trends in the field of lung cancer combined with pulmonary tuberculosis (LC‐PTB). The study analyzed 460 publications from various countries and institutions using bibliometric tools. The visualized analysis highlights the increasing publication trend, with China as the leading contributor. Notable institutions, influential authors, and key journal publications are also identified. The co‐citation network reveals a shift in research focus toward immune mechanisms and immunotherapy. This study provides valuable insights and potential directions for differential diagnosis and exploring immunotherapeutic approaches in LC‐PTB.

Abstract

Background

The incidence of lung cancer combined with pulmonary tuberculosis has been increasing, but there is relatively limited published literature on the topic of lung cancer combined with tuberculosis (LC‐PTB) from a bibliometric perspective. Therefore, in this study, we aimed to quantitatively analyze the LC‐PTB‐related literature to better understand the current status of this field and identify future research trends.

Methods

We searched for articles related to LC‐PTB using the Web of Science Core Collection (SCI‐E) and conducted a visual analysis of publication quantity, countries, institutions, authors, journals, references, and keywords using bibliometric software (CiteSpace, VOSviewer, and Scimago Graphica).

Results

As of January 8, 2024, a total of 460 publications related to LC‐PTB were included for analysis from 3705 retrieved records. The number of publications has been increasing almost yearly, with most from China (n = 123), followed by the United States (n = 77). Taipei Medical University contributed the most publications (n = 11). Jing‐Yang Huang and Yung‐Po Liaw (eight documents each) ranked first among the included authors. The Journal of Thoracic Oncology was the most productive academic journal on LC‐PTB. The aggregation of key nodes in the co‐citation network and the chronological sequence indicated that LC‐PTB research has shifted from initial hotspots such as lung diseases, bronchitis, and exposure to recent areas, including immunotherapy, immune checkpoint inhibitors, and nivolumab.

Conclusion

In this study, we visualized the current status of LC‐PTB research as well as future trends using bibliometric methods, providing new insights into the differential diagnosis of LC‐PTB and its related promoting mechanisms.

Electronic Supplementary Material

Download File(s)
med-2-2-144_ESM.docx (21.2 KB)

References

[1]
Siddiqui F, Vaqar S, Siddiqui AH. Lung cancer. In: StatPearls [Internet]. Treasure Island (FL): StatPearls Publishing; 2024.
[2]

Siegel RL, Giaquinto AN, Jemal A. Cancer statistics, 2024. CA Cancer J Clin. 2024;74(1):12–49. https://doi.org/10.3322/caac.21820

[3]

Zheng RS, Zhang SW, Sun KX, Chen R, Wang SM, Li L, et al. Cancer statistics in China, 2016. Zhonghua Zhongliu Zazhi. 2023;45(3):212–20. https://doi.org/10.3760/cma.j.cn112152-20220922-00647

[4]

Li LS, Yang L, Zhuang L, Ye ZY, Zhao WG, Gong WP. From immunology to artificial intelligence: revolutionizing latent tuberculosis infection diagnosis with machine learning. Mil Med Res. 2023;10(1):58. https://doi.org/10.1186/s40779-023-00490-8

[5]

WHO. Global tuberculosis report 2023. Geneva: World Health Organization; 2023. p. 1–75.

[6]

Liang HY, Li XL, Yu XS, Guan P, Yin ZH, He QC, et al. Facts and fiction of the relationship between preexisting tuberculosis and lung cancer risk: a systematic review. Int J Cancer. 2009;125(12):2936–44. https://doi.org/10.1002/ijc.24636

[7]

Dobler CC, Cheung K, Nguyen J, Martin A. Risk of tuberculosis in patients with solid cancers and haematological malignancies: a systematic review and meta‐analysis. Eur Respir J. 2017;50(2):1700157. https://doi.org/10.1183/13993003.00157-2017

[8]

Cheng MP, Abou Chakra CN, Yansouni CP, Cnossen S, Shrier I, Menzies D, et al. Risk of active tuberculosis in patients with cancer: a systematic review and meta‐analysis. Clin Infect Dis. 2017;64(5):635–44. https://doi.org/10.1093/cid/ciw838

[9]

Hwang SY, Kim JY, Lee HS, Lee S, Kim D, Kim S, et al. Pulmonary tuberculosis and risk of lung cancer: a systematic review and meta‐analysis. J Clin Med. 2022;11(3):765. https://doi.org/10.3390/jcm11030765

[10]

Jiang F, Sun T, Cheng P, Wang J, Gong W. A summary on tuberculosis vaccine development‐where to go? J Pers Med. 2023;13(3):408. https://doi.org/10.3390/jpm13030408

[11]

Ninkov A, Frank JR, Maggio LA. Bibliometrics: methods for studying academic publishing. Perspect Med Educ. 2022;11(3):173–6. https://doi.org/10.1007/s40037-021-00695-4

[12]

Broadus RN. Toward a definition of “bibliometrics”. Scientometrics. 1987;12(5):373–9. https://doi.org/10.1007/BF02016680

[13]

Schreiber K, Girard T, Kindler CH. Bibliometric analysis of original molecular biology research in anaesthesia. Anaesthesia. 2004;59(10):1002–7. https://doi.org/10.1111/j.1365-2044.2004.03873.x

[14]

Wang W, Wang H, Yao T, Li Y, Yi L, Gao Y, et al. The top 100 most cited articles on COVID‐19 vaccine: a bibliometric analysis. Clin Exp Med. 2023;23(6):2287–99. https://doi.org/10.1007/s10238-023-01046-9

[15]

Ellegaard O, Wallin JA. The bibliometric analysis of scholarly production: how great is the impact? Scientometrics. 2015;105(3):1809–31. https://doi.org/10.1007/s11192-015-1645-z

[16]

Kokol P, Blažun Vošner H, Završnik J. Application of bibliometrics in medicine: a historical bibliometrics analysis. Health Info Libr J. 2021;38(2):125–38. https://doi.org/10.1111/hir.12295

[17]

Quaia E, Vernuccio F. The H index myth: a form of fanaticism or a simple misconception? Tomography. 2022;8(3):1241–3. https://doi.org/10.3390/tomography8030102

[18]

Costas R, Bordons M. The h‐index: advantages, limitations and its relation with other bibliometric indicators at the micro level. J Informetr. 2007;1(3):193–203. https://doi.org/10.1016/j.joi.2007.02.001

[19]

Djoutsop OM, Mbougo JV, Kanmounye US. Global head and neck surgery research during the COVID pandemic: a bibliometric analysis. Ann Med Surg. 2021;68:102555. https://doi.org/10.1016/j.amsu.2021.102555

[20]

Wolfe AW. Social network analysis: methods and applications. Am Ethnol. 1997;24(1):219–20. https://doi.org/10.1525/ae.1997.24.1.219

[21]

Rivera MT, Soderstrom SB, Uzzi B. Dynamics of dyads in social networks: assortative, relational, and proximity mechanisms. Annu Rev Sociol. 2010;36(1):91–115. https://doi.org/10.1146/annurev.soc.34.040507.134743

[22]

Pendlebury DA. The use and misuse of journal metrics and other citation indicators. Arch Immunol Ther Exp. 2009;57(1):1–11. https://doi.org/10.1007/s00005-009-0008-y

[23]

Casadevall A, Fang FC. Impacted science: impact is not importance. mBio. 2015;6(5):e01593. https://doi.org/10.1128/mBio.01593-15

[24]

Garfield E. The history and meaning of the journal impact factor. JAMA. 2006;295(1):90–3. https://doi.org/10.1001/jama.295.1.90

[25]

Liu X, Zhao S, Tan L, Tan Y, Wang Y, Ye Z, et al. Frontier and hot topics in electrochemiluminescence sensing technology based on CiteSpace bibliometric analysis. Biosens Bioelectron. 2022;201:113932. https://doi.org/10.1016/j.bios.2021.113932

[26]

Xia Y, Yao RQ, Zhao PY, Tao ZB, Zheng LY, Zhou HT, et al. Publication trends of research on COVID‐19 and host immune response: a bibliometric analysis. Front Public Health. 2022;10:939053. https://doi.org/10.3389/fpubh.2022.939053

[27]

Xiong M, Xu Y, Zhao Y, He S, Zhu Q, Wu Y, et al. Quantitative analysis of artificial intelligence on liver cancer: a bibliometric analysis. Front Oncol. 2023;13:990306. https://doi.org/10.3389/fonc.2023.990306

[28]

Chen C. Searching for intellectual turning points: progressive knowledge domain visualization. Proc Natl Acad Sci USA. 2004;101(Suppl 1):5303–10. https://doi.org/10.1073/pnas.0307513100

[29]

van Eck NJ, Waltman L. Software survey: VOSviewer, a computer program for bibliometric mapping. Scientometrics. 2010;84(2):523–38. https://doi.org/10.1007/s11192-009-0146-3

[30]

Cobo MJ, López‐Herrera AG, Herrera‐Viedma E, Herrera F. Science mapping software tools: review, analysis, and cooperative study among tools. J Am Soc Inf Sci Technol. 2011;62(7):1382–402. https://doi.org/10.1002/asi.21525

[31]

Chen C. CiteSpace Ⅱ: detecting and visualizing emerging trends and transient patterns in scientific literature. J Am Soc Inf Sci. 2006;57(3):359–77. https://doi.org/10.1002/asi.20317

[32]

Hu Y, Wu L, He L, Luo X, Hu L, Wang Y, et al. Bibliometric and visualized analysis of scientific publications on rehabilitation of rotator cuff injury based on web of science. Front Public Health. 2023;11:1064576. https://doi.org/10.3389/fpubh.2023.1064576

[33]

Wei N, Xu Y, Li YN, Shi J, Zhang X, You Y, et al. A bibliometric analysis of T cell and atherosclerosis. Front Immunol. 2022;13:948314. https://doi.org/10.3389/fimmu.2022.948314

[34]

Adjei AA. The coming of a new age: the journal of thoracic oncology goes electronic in 2024. J Thorac Oncol. 2023;18(10):1257. https://doi.org/10.1016/j.jtho.2023.08.006

[35]

Wang J, Maniruzzaman M. A global bibliometric and visualized analysis of bacteria‐mediated cancer therapy. Drug Discov Today. 2022;27(10):103297. https://doi.org/10.1016/j.drudis.2022.05.023

[36]

Shi Y, Wei W, Li L, Wei Q, Jiang F, Xia G, et al. The global status of research in breast cancer liver metastasis: a bibliometric and visualized analysis. Bioengineered. 2021;12(2):12246–62. https://doi.org/10.1080/21655979.2021.2006552

[37]

Liu K, Zhao S, Li J, Zheng Y, Wu H, Kong J, et al. Knowledge mapping and research hotspots of immunotherapy in renal cell carcinoma: a text‐mining study from 2002 to 2021. Front Immunol. 2022;13:969217. https://doi.org/10.3389/fimmu.2022.969217

[38]

Jiang F, Su Y, Chang T. Knowledge mapping of global trends for myasthenia gravis development: a bibliometrics analysis. Front Immunol. 2023;14:1132201. https://doi.org/10.3389/fimmu.2023.1132201

[39]

Yu YH, Liao CC, Hsu WH, Chen HJ, Liao WC, Muo CH, et al. Increased lung cancer risk among patients with pulmonary tuberculosis: a population cohort study. J Thorac Oncol. 2011;6(1):32–7. https://doi.org/10.1097/JTO.0b013e3181fb4fcc

[40]

Fujita K, Terashima T, Mio T. Anti‐PD1 antibody treatment and the development of acute pulmonary tuberculosis. J Thorac Oncol. 2016;11(12):2238–40. https://doi.org/10.1016/j.jtho.2016.07.006

[41]

Picchi H, Mateus C, Chouaid C, Besse B, Marabelle A, Michot JM, et al. Infectious complications associated with the use of immune checkpoint inhibitors in oncology: reactivation of tuberculosis after anti PD‐1 treatment. Clin Microbiol Infect. 2018;24(3):216–8. https://doi.org/10.1016/j.cmi.2017.12.003

[42]

Wu CY, Hu HY, Pu CY, Huang N, Shen HC, Li CP, et al. Pulmonary tuberculosis increases the risk of lung cancer: a population‐based cohort study. Cancer. 2011;117(3):618–24. https://doi.org/10.1002/cncr.25616

[43]

Anastasopoulou A, Ziogas DC, Samarkos M, Kirkwood JM, Gogas H. Reactivation of tuberculosis in cancer patients following administration of immune checkpoint inhibitors: current evidence and clinical practice recommendations. J Immunother Cancer. 2019;7(1):239. https://doi.org/10.1186/s40425-019-0717-7

[44]

Chu YC, Fang KC, Chen HC, Yeh YC, Tseng CE, Chou TY, et al. Pericardial tamponade caused by a hypersensitivity response to tuberculosis reactivation after anti‐PD‐1 treatment in a patient with advanced pulmonary adenocarcinoma. J Thorac Oncol. 2017;12(8):e111–4. https://doi.org/10.1016/j.jtho.2017.03.012

[45]

Barber DL, Sakai S, Kudchadkar RR, Fling SP, Day TA, Vergara JA, et al. Tuberculosis following PD‐1 blockade for cancer immunotherapy. Sci Transl Med. 2019;11(475):eaat2702. https://doi.org/10.1126/scitranslmed.aat2702

[46]

Ho JCM, Leung CC. Management of co‐existent tuberculosis and lung cancer. Lung Cancer. 2018;122:83–7. https://doi.org/10.1016/j.lungcan.2018.05.030

[47]

Elkington PT, Bateman AC, Thomas GJ, Ottensmeier CH. Implications of tuberculosis reactivation after immune checkpoint inhibition. Am J Respir Crit Care Med. 2018;198(11):1451–3. https://doi.org/10.1164/rccm.201807-1250LE

[48]

Sheikhpour M, Mirbahari SN, Sadr M, Maleki M, Arabi M, Abolfathi H. A comprehensive study on the correlation of treatment, diagnosis and epidemiology of tuberculosis and lung cancer. Tanaffos. 2023;22(1):7–18.

[49]

Bordignon V, Bultrini S, Prignano G, Sperduti I, Piperno G, Bonifati C, et al. High prevalence of latent tuberculosis infection in autoimmune disorders such as psoriasis and in chronic respiratory diseases, including lung cancer. J Biol Regul Homeost Agents. 2011;25(2):213–20.

[50]

Li Z. The value of GeneXpert MTB/RIF for detection in tuberculosis: a bibliometrics‐based analysis and review. J Anal Methods Chem. 2022;2022:2915018–111. https://doi.org/10.1155/2022/2915018

[51]

Pan Y, Deng X, Zhuang Y, Li J. Research trends around exercise rehabilitation among cancer patients: a bibliometrics and visualized knowledge graph analysis. BioMed Res Int. 2022;2022:3755460–511. https://doi.org/10.1155/2022/3755460

[52]

Gandhi L, Rodríguez‐Abreu D, Gadgeel S, Esteban E, Felip E, De Angelis F, et al. Pembrolizumab plus chemotherapy in metastatic non‐small‐cell lung cancer. N Engl J Med. 2018;378(22):2078–92. https://doi.org/10.1056/NEJMoa1801005

[53]

Paz‐Ares L, Luft A, Vicente D, Tafreshi A, Gümüş M, Mazières J, et al. Pembrolizumab plus chemotherapy for squamous non‐small‐cell lung cancer. N Engl J Med. 2018;379(21):2040–51. https://doi.org/10.1056/NEJMoa1810865

[54]

Mok TSK, Wu YL, Kudaba I, Kowalski DM, Cho BC, Turna HZ, et al. Pembrolizumab versus chemotherapy for previously untreated, PD‐L1‐expressing, locally advanced or metastatic non‐small‐cell lung cancer (KEYNOTE‐042): a randomised, open‐label, controlled, phase 3 trial. Lancet. 2019;393(10183):1819–30. https://doi.org/10.1016/S0140-6736(18)32409-7

[55]

Johnson EO, LaVerriere E, Office E, Stanley M, Meyer E, Kawate T, et al. Large‐scale chemical‐genetics yields new M. tuberculosis inhibitor classes. Nature. 2019;571(7763):72–8. https://doi.org/10.1038/s41586-019-1315-z

[56]

Brenner AV, Wang Z, Kleinerman RA, Wang L, Zhang S, Metayer C, et al. Previous pulmonary diseases and risk of lung cancer in Gansu Province, China. Int J Epidemiol. 2001;30(1):118–24. https://doi.org/10.1093/ije/30.1.118

[57]

Gong W, Liang Y, Wu X. The current status, challenges, and future developments of new tuberculosis vaccines. Hum Vaccin Immunother. 2018;14(7):1697–716. https://doi.org/10.1080/21645515.2018.1458806

[58]

Zhuang L, Ye Z, Li L, Yang L, Gong W. Next‐generation TB vaccines: progress, challenges, and prospects. Vaccines. 2023;11(8):1304. https://doi.org/10.3390/vaccines11081304

[59]

HosgoodIII HD, Chapman RS, He X, Hu W, Tian L, Liu LZ, et al. History of lung disease and risk of lung cancer in a population with high household fuel combustion exposures in rural China. Lung Cancer. 2013;81(3):343–6. https://doi.org/10.1016/j.lungcan.2013.06.019

[60]

Du J, Su Y, Qiao J, Gao S, Dong E, Wang R, et al. Application of artificial intelligence in diagnosis of pulmonary tuberculosis. Chin Med J. 2024;137(5):559–61. https://doi.org/10.1097/CM9.0000000000003018

[61]

Yang L, Zhuang L, Ye Z, Li L, Guan J, Gong W. Immunotherapy and biomarkers in patients with lung cancer with tuberculosis: recent advances and future Directions. iScience. 2023;26(10):107881. https://doi.org/10.1016/j.isci.2023.107881

[62]

King DA. The scientific impact of nations. Nature. 2004;430(6997):311–6. https://doi.org/10.1038/430311a

[63]

Talukdar T, Rathi V, Ish P. Geriatric tuberculosis in India‐challenges and solutions. Indian J Tuberc. 2022;69(Suppl 2):S209–12. https://doi.org/10.1016/j.ijtb.2022.10.003

[64]

Rallison SP. What are journals for? Ann R Coll Surg Engl. 2015;97(2):89–91. https://doi.org/10.1308/003588414X14055925061397

[65]

Suzuki K, Edelson A, Iversen LL, Hausmann L, Schulz JB, Turner AJ. A learned society’s perspective on publishing. J Neurochem. 2016;139(Suppl 2):17–23. https://doi.org/10.1111/jnc.13674

[66]

Shen C, Björk BC. Predatory’ open access: a longitudinal study of article volumes and market characteristics. BMC Med. 2015;13(1):230. https://doi.org/10.1186/s12916-015-0469-2

[67]

Cheng K, Zhang H, Guo Q, Zhai P, Zhou Y, Yang W, et al. Emerging trends and research foci of oncolytic virotherapy for central nervous system tumors: a bibliometric study. Front Immunol. 2022;13:975695. https://doi.org/10.3389/fimmu.2022.975695

[68]

Wu X, Deng Z, Zhao Q. Immunotherapy improves disease prognosis by affecting the tumor microenvironment: a bibliometric study. Front Immunol. 2022;13:967076. https://doi.org/10.3389/fimmu.2022.967076

[69]

Anichini A, Perotti VE, Sgambelluri F, Mortarini R. Immune escape mechanisms in non small cell lung cancer. Cancers. 2020;12(12):3605. https://doi.org/10.3390/cancers12123605

[70]

WHO. Framework for conducting reviews of tuberculosis programmes. Geneva: World Health Organization; 2014.

[71]

Kim HR, Hwang SS, Ro YK, Jeon CH, Ha DY, Park SJ, et al. Solid‐organ malignancy as a risk factor for tuberculosis. Respirology. 2008;13(3):413–9. https://doi.org/10.1111/j.1440-1843.2008.01282.x

[72]

Peng C, Jiang F, Liu Y, Xue Y, Cheng P, Wang J, et al. Development and evaluation of a promising biomarker for diagnosis of latent and active tuberculosis infection. Infect Dis Immun. 2024;4(1):10–24. https://doi.org/10.1097/id9.0000000000000104

[73]

Xie Y, Su N, Zhou W, Lei A, Li X, Li W, et al. Concomitant pulmonary tuberculosis impair survival in advanced epidermal growth factor receptor (EGFR) mutant lung adenocarcinoma patients receiving EGFR‐tyrosine kinase inhibitor. Cancer Manag Res. 2021;13:7517–26. https://doi.org/10.2147/CMAR.S326349

[74]

Liu N, Zheng L, Yu M, Zhang S. Epidermal growth factor receptor‐mutant pulmonary adenocarcinoma coexisting with tuberculosis: a case report. Medicine (Baltim). 2021;100(8):e24569. https://doi.org/10.1097/MD.0000000000024569

[75]

George S, Miao D, Demetri GD, Adeegbe D, Rodig SJ, Shukla S, et al. Loss of PTEN is associated with resistance to anti‐PD‐1 checkpoint blockade therapy in metastatic uterine leiomyosarcoma. Immunity. 2017;46(2):197–204. https://doi.org/10.1016/j.immuni.2017.02.001

[76]

Huang G, Redelman‐Sidi G, Rosen N, Glickman MS, Jiang X. Inhibition of mycobacterial infection by the tumor suppressor PTEN. J Biol Chem. 2012;287(27):23196–202. https://doi.org/10.1074/jbc.M112.351940

[77]

Yang Y, Yang L, Wang Y. Immunotherapy for lung cancer: mechanisms of resistance and response strategy. Zhongguo Fei Ai Za Zhi. 2021;24(2):112–23. https://doi.org/10.3779/j.issn.1009-3419.2021.101.02

[78]

Keikha M, Esfahani BN. The relationship between tuberculosis and lung cancer. Adv Biomed Res. 2018;7(1):58. https://doi.org/10.4103/abr.abr_182_17

[79]

Xiao F, Li C, Sun J, Zhang L. Knowledge domain and emerging trends in organic photovoltaic technology: a scientometric review based on CiteSpace analysis. Front Chem. 2017;5:67. https://doi.org/10.3389/fchem.2017.00067

[80]

Ma L, Ma J, Teng M, Li Y. Visual analysis of colorectal cancer immunotherapy: a bibliometric analysis from 2012 to 2021. Front Immunol. 2022;13:843106. https://doi.org/10.3389/fimmu.2022.843106

[81]

Zhang Y, Zhang Z. The history and advances in cancer immunotherapy: understanding the characteristics of tumor‐infiltrating immune cells and their therapeutic implications. Cell Mol Immunol. 2020;17(8):807–21. https://doi.org/10.1038/s41423-020-0488-6

[82]

Okwundu N, Grossman D, Hu‐Lieskovan S, Grossmann KF, Swami U. The dark side of immunotherapy. Ann Transl Med. 2021;9(12):1041. https://doi.org/10.21037/atm-20-4750

[83]

Wykes MN, Lewin SR. Immune checkpoint blockade in infectious diseases. Nat Rev Immunol. 2018;18(2):91–104. https://doi.org/10.1038/nri.2017.112

[84]

Dhar C. Testing for latent tuberculosis before starting patients on immune checkpoint inhibitors. Indian J Cancer. 2021;58(3):469–70. https://doi.org/10.4103/ijc.IJC_283_20

[85]

Waltman L, van Eck NJ. Source normalized indicators of citation impact: an overview of different approaches and an empirical comparison. Scientometrics. 2013;96(3):699–716. https://doi.org/10.1007/s11192-012-0913-4

[86]
Gingras Y. What bibliometrics teaches us about the dynamics of science. In: Bibliometrics and research evaluation: uses and abuses. Cambridge: MIT Press; 2016. p. 11–34.
Medicine Advances
Pages 144-164
Cite this article:
Yang L, Ye Z, Li L, et al. Visualization analysis of research progress and trends in coexistence of lung cancer and pulmonary tuberculosis using bibliometrics. Medicine Advances, 2024, 2(2): 144-164. https://doi.org/10.1002/med4.58
Metrics & Citations  
Article History
Copyright
Rights and Permissions
Return