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How biomedical papers accumulated their clinical citations: a large-scale retrospective analysis based on PubMed

Author

Listed:
  • Xin Li

    (Huazhong University of Science and Technology)

  • Xuli Tang

    (Central China Normal University)

  • Wei Lu

    (Wuhan University)

Abstract

This paper explored the temporal characteristics of clinical citations of biomedical papers, including how long it takes to receive its first clinical citation (the initial stage) and how long it takes to receive two or more clinical citations after its first clinical citation (the build-up stage). Over 23 million biomedical papers in PubMed between 1940 and 2013 and their clinical citations are used as the research data. We divide these biomedical papers into three groups and four categories from clinical citation level and translational science perspectives. We compare the temporal characteristics of biomedical papers of different groups or categories. From the perspective of clinical citation level, the results show that highly clinically cited papers had obvious advantages of receiving clinical citations over medium and lowly clinically cited papers in both the initial and build-up stages. Meanwhile, as the number of clinical citations increased in the build-up stage, the difference in the length of time to receive the corresponding number of clinical citations among the three groups of biomedical papers significantly increased. From the perspective of translational science, the results reveal that biomedical papers closer to clinical science more easily receive clinical citations than papers closer to basic science in both the initial and build-up stages. Moreover, we found that highly clinically cited papers had the desperate advantage of receiving clinical citations over even the clinical guidelines or clinical trials. The robustness analysis of the two aspects demonstrates the reliability of our results. The indicators proposed in this paper could be useful for pharmaceutical companies and government policy-makers to monitor the translational progress of biomedical research. Besides, the findings in this study could be interesting for young scholars in biomedicine to get more attention from clinical science and to obtain success in their scientific careers, especially for those in basic science.

Suggested Citation

  • Xin Li & Xuli Tang & Wei Lu, 2024. "How biomedical papers accumulated their clinical citations: a large-scale retrospective analysis based on PubMed," Scientometrics, Springer;Akadémiai Kiadó, vol. 129(6), pages 3315-3339, June.
    • Handle: RePEc:spr:scient:v:129:y:2024:i:6:d:10.1007_s11192-024-05016-0
    DOI: 10.1007/s11192-024-05016-0
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    References listed on IDEAS

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    1. Min, Chao & Sun, Jianjun & Pei, Lei & Ding, Ying, 2016. "Measuring delayed recognition for papers: Uneven weighted summation and total citations," Journal of Informetrics, Elsevier, vol. 10(4), pages 1153-1165.
    2. Mike Thelwall & Kayvan Kousha, 2016. "Are citations from clinical trials evidence of higher impact research? An analysis of ClinicalTrials.gov," Scientometrics, Springer;Akadémiai Kiadó, vol. 109(2), pages 1341-1351, November.
    3. Yong Huang & Yi Bu & Ying Ding & Wei Lu, 2019. "From zero to one: A perspective on citing," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 70(10), pages 1098-1107, October.
    4. Egghe, L. & Bornmann, L. & Guns, R., 2011. "A proposal for a First-Citation-Speed-Index," Journal of Informetrics, Elsevier, vol. 5(1), pages 181-186.
    5. Leo Egghe, 2000. "A Heuristic Study of the First-Citation Distribution," Scientometrics, Springer;Akadémiai Kiadó, vol. 48(3), pages 345-359, July.
    6. S. R. Goldberg & H. Anthony & T. S. Evans, 2015. "Modelling citation networks," Scientometrics, Springer;Akadémiai Kiadó, vol. 105(3), pages 1577-1604, December.
    7. Magnus Eriksson & Annika Billhult & Tommy Billhult & Elena Pallari & Grant Lewison, 2020. "A new database of the references on international clinical practice guidelines: a facility for the evaluation of clinical research," Scientometrics, Springer;Akadémiai Kiadó, vol. 122(2), pages 1221-1235, February.
    8. Ke, Qing, 2020. "The citation disadvantage of clinical research," Journal of Informetrics, Elsevier, vol. 14(1).
    9. B Ian Hutchins & Matthew T Davis & Rebecca A Meseroll & George M Santangelo, 2019. "Predicting translational progress in biomedical research," PLOS Biology, Public Library of Science, vol. 17(10), pages 1-25, October.
    10. Xin Li & Xuli Tang & Wei Lu, 2023. "Tracking biomedical articles along the translational continuum: a measure based on biomedical knowledge representation," Scientometrics, Springer;Akadémiai Kiadó, vol. 128(2), pages 1295-1319, February.
    11. Li, Xin & Tang, Xuli & Cheng, Qikai, 2022. "Predicting the clinical citation count of biomedical papers using multilayer perceptron neural network," Journal of Informetrics, Elsevier, vol. 16(4).
    12. Eugene I KaneIII & Gail L Daumit & Kevin M Fain & Roberta W Scherer & Emma Elizabeth McGinty, 2022. "Evaluating the Revised National Institutes of Health clinical trial definition impact on recruitment progress," Research Evaluation, Oxford University Press, vol. 31(2), pages 249-256.
    13. Li, Xin & Tang, Xuli, 2021. "Characterizing interdisciplinarity in drug research: A translational science perspective," Journal of Informetrics, Elsevier, vol. 15(4).
    14. Jian Du & Yishan Wu, 2018. "A parameter-free index for identifying under-cited sleeping beauties in science," Scientometrics, Springer;Akadémiai Kiadó, vol. 116(2), pages 959-971, August.
    15. Ludo Waltman & Nees Jan van Eck & Anthony F. J. van Raan, 2012. "Universality of citation distributions revisited," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 63(1), pages 72-77, January.
    16. Francis Narin & Gabriel Pinski & Helen Hofer Gee, 1976. "Structure of the Biomedical Literature," Journal of the American Society for Information Science, Association for Information Science & Technology, vol. 27(1), pages 25-45, January.
    17. Quentin L. Burrel, 2001. "Stochastic modelling of the first-citation distribution," Scientometrics, Springer;Akadémiai Kiadó, vol. 52(1), pages 3-12, September.
    18. Grant Lewison & Guillermo Paraje, 2004. "The classification of biomedical journals by research level," Scientometrics, Springer;Akadémiai Kiadó, vol. 60(2), pages 145-157, June.
    19. Ludo Waltman & Nees Jan van Eck & Anthony F. J. van Raan, 2012. "Universality of citation distributions revisited," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 63(1), pages 72-77, January.
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