Kanser epidemiyolojisinde en çok atıf alan ilk 500 makalenin bibliyometrik analizi

Year 2025, Volume: 18 Issue: 3, 2 - 2

Yasemin Adali

https://doi.org/10.31362/patd.1543017

Abstract

Amaç: Bu çalışmanın amacı, “kanser epidemiyolojisi” konusundaki literatürün kapsamlı bir bibliyometrik analizini oluşturarak gelecekteki araştırmalar için öngörüler sunmaktır.
Gereç ve yöntemler: Makale verileri Web of Science Core Collection'dan (WoSCC) toplandı ve 2010-2024 yılları arasında "cancer*" ve "epidemi*" anahtar sözcükleri kullanılarak gelişmiş arama yapıldı. Sonuçlar daha sonra yalnızca WOS veri tabanındaki orijinal İngilizce makalelerden oluşan Science Citation Index Expanded ve Emerging Sources Citation Index yayın türüne göre rafine edildi. Veri analizi sonuçlarının bir özeti, açık kaynaklı R paketi Bibliometric ve VOS görüntüleyici (Sürüm 16.20) programlarıyla birlikte araştırıldı.
Bulgular: 2010-2024 zaman aralığında 180 farklı kaynakta yayınlanan en çok atıf alan 500 belge, yıllık %18,97'lik bir negatif yönde büyüme oranı gösterdi ve bu da yayın çıktısında bir düşüş olduğunu gözlemlenmiştir. Belge başına ortalama 70,1 ortak yazar olduğu gözlenmiş ve bu makalelerdeki iş birliği çabaların %60,8'ini yabancı ortak yazarlık oluşturduğu bulunmuştur. En çok görünen anahtar kelimeler, toplam bağlantı gücü 625 olan "epidemiyoloji” olarak bulundu, daha sonra 372 toplam bağlantı gücüne sahip olan "kanser" olduğu gözlenmiştir. Bibiliometrik analiz sonucuna göre Ferlay, J. makalesi 72.000'den fazla atıf aldığı tespit edilmiştir.
Sonuç: Bu bibliyometrik analiz, kanser epidemiyolojisi disiplininin genişlemesi, bilimsel mükemmellik düzeyi ve anahtar kelimelerin belirlenmesi hakkında nicel veriler sağlamış ve böylece en başarılı konuların belirlenmesini kolaylaştırmıştır.

Keywords

Bibliyometrik analiz, kanser epidemiyolojisi, bibliometrix, VOSwiever

Bibliometric analysis of the top 500 most cited articles in cancer epidemiology

Abstract

Purpose: The objective of this work is to provide perceptions for future research by creating a comprehensive bibliometric analysis of the literature on "cancer epidemiology".
Material and methods: Article data was collected from the Web of Science Core Collection (WoSCC) and advanced search was performed using the following keywords: “cancer*” and “epidemi*” between 2010-2024. The results were then refined according to the publication type of Science Citation Index Expanded and Emerging Sources Citation Index, which only consist of original English articles in the WOS database. A summary of the data analysis results examined along with open-source R package Bibliometric and VOS viewer (Version 16.20) programs.
Results: The 500 most cited documents published in 180 different sources in the time period 2010-2024 showed a negative annual growth rate of 18.97%, indicating a decrease in publication output. An average of 70.1 co-authors per document was observed, and 60.8% of the collaborative efforts in these articles were found to be foreign co-authorship. The most frequently appearing keywords were found to be "epidemiology" with a total link strength of 625, followed by "cancer" with a total link strength of 372. According to the bibiliometric analysis result, the article by Ferlay, J. mm was found to have more than 72,000 citations.
Conclusion: This bibliometric analysis has yielded quantitative data on the expansion of the cancer epidemiology discipline, the level of scientific excellence, and the identification of keywords, so facilitating the determination of the most accomplished topics.

Keywords

Bibliometric analysis, cancer epidemiology, bibliometrix, VOSwiever

Ethical Statement

Bibliometric analysis, ethics committe approval is not required

Supporting Institution

There are no financial supports.

References

• [1] Mattiuzzi C, Lippi G. Current cancer epidemiology. J Epidemiol Glob Health 2019;9:217–22. https://doi.org/10.2991/jegh.k.191008.001.
• [2] Kocic B, Filipovic S, Petrovic B, Nikolic M. Case-control design as investigative approach to assessing cancer etiology: development and future perspectives - PubMed. BUON 2012;17:428–35.
• [3] Piña-Sánchez P, Chávez-González A, Ruiz-Tachiquín M, Vadillo E, Monroy-García A, Montesinos JJ, et al. Cancer Biology, Epidemiology, and Treatment in the 21st Century: Current Status and Future Challenges From a Biomedical Perspective. Cancer Control 2021;28. https://doi.org/10.1177/10732748211038735.
• [4] Ohlan R, Ohlan A. A comprehensive bibliometric analysis and visualization of smart home research. Technol Forecast Soc Change 2022;184:121975. https://doi.org/10.1016/J.TECHFORE.2022.121975.
• [5] Aria M, Cuccurullo C. bibliometrix: An R-tool for comprehensive science mapping analysis. J Informetr 2017;11:959–75. https://doi.org/10.1016/j.joi.2017.08.007.
• [6] Stephan P, Veugelers R, Wang J. Reviewers are blinkered by bibliometrics. Nature 2017 544:7651 2017;544:411–2. https://doi.org/10.1038/544411a.
• [7] Moher D, Liberati A, Tetzlaff J, Altman DG. Preferred reporting items for systematic reviews and meta-analyses: The PRISMA statement. International Journal of Surgery 2010;8:336–41. https://doi.org/10.1016/j.ijsu.2010.02.007.
• [8] Siegel RL, Miller KD, Jemal A. Cancer statistics, 2017. CA Cancer J Clin 2017;67:7–30. https://doi.org/10.3322/caac.21387.
• [9] Siegel RL, Miller KD, Fuchs HE, Jemal A. Cancer Statistics, 2021. CA Cancer J Clin 2021;71:7–33. https://doi.org/10.3322/caac.21654.
• [10] Sung H, Ferlay J, Siegel RL, Laversanne M, Soerjomataram I, Jemal A, et al. Global Cancer Statistics 2020: GLOBOCAN Estimates of Incidence and Mortality Worldwide for 36 Cancers in 185 Countries. CA Cancer J Clin 2021;71:209–49. https://doi.org/10.3322/caac.21660.
• [11] Ferlay J, Soerjomataram I, Dikshit R, Eser S, Mathers C, Rebelo M, et al. Cancer incidence and mortality worldwide: Sources, methods and major patterns in GLOBOCAN 2012. Int J Cancer 2015;136:E359–86. https://doi.org/10.1002/ijc.29210.
• [12] Siegel R, Ma J, Zou Z, Jemal A. Cancer statistics, 2014. CA Cancer J Clin 2014;64:9–29. https://doi.org/10.3322/caac.21208.
• [13] Torre LA, Bray F, Siegel RL, Ferlay J, Lortet‐Tieulent J, Jemal A. Global cancer statistics, 2012. CA Cancer J Clin 2015;65:87–108. https://doi.org/10.3322/caac.21262.
• [14] Chen W, Zheng R, Baade PD, Zhang S, Zeng H, Bray F, et al. Cancer statistics in China, 2015. CA Cancer J Clin 2016;66:115–32. https://doi.org/10.3322/caac.21338.
• [15] Ferlay J, Shin HR, Bray F, Forman D, Mathers C, Parkin DM. Estimates of worldwide burden of cancer in 2008: GLOBOCAN 2008. Int J Cancer 2010;127:2893–917. https://doi.org/10.1002/ijc.25516.
• [16] Bolyen E, Rideout JR, Dillon MR, Bokulich NA, Abnet CC, Al-Ghalith GA, et al. Reproducible, interactive, scalable and extensible microbiome data science using QIIME 2. Nat Biotechnol 2019;37:852–7. https://doi.org/10.1038/s41587-019-0209-9.
• [17] Koboldt DC, Fulton RS, McLellan MD, Schmidt H, Kalicki-Veizer J, McMichael JF, et al. Comprehensive molecular portraits of human breast tumours. Nature 2012;490:61–70. https://doi.org/10.1038/nature11412.
• [18] Schulz KF, Altman DG, Moher D. CONSORT 2010 Statement: updated guidelines for reporting parallel group randomised trials. The BMJ 2010;340:698–702. https://doi.org/10.1136/BMJ.C332.
• [19] Altshuler DM, Durbin RM, Bentley DR, Chakravarti A, Clark AG, Donnelly P, et al. A global reference for human genetic variation. Nature 2015;526:68–74. https://doi.org/10.1038/nature15393.
• [20] Siegel RL, Miller KD, Fuchs HE, Jemal A. Cancer statistics, 2022. CA Cancer J Clin 2022;72:7–33. https://doi.org/10.3322/caac.21708.
• [21] Siegel RL, Miller KD, Jemal A. Cancer statistics, 2020. CA Cancer J Clin 2020;70:7–30. https://doi.org/10.3322/caac.21590.
• [22] Arem H, Loftfield E. Cancer Epidemiology: A Survey of Modifiable Risk Factors for Prevention and Survivorship. Am J Lifestyle Med 2018;12:200. https://doi.org/10.1177/1559827617700600.
• [23] Maresso KC, Basen-Engquist K, Hawk E. Cancer Epidemiology, Prevention, and Survivorship. Perioperative Care of the Cancer Patient 2023:3–14. https://doi.org/10.1016/B978-0-323-69584-8.00001-3.