摘要在重大突发公共卫生事件的背景下，科技论文的临床应用价值被提到前所未有的重要位置。但如何评价这种类型的影响力以及有哪些有效指标仍需要深入挖掘与探索。引文桂冠奖是基于被引频次的诺贝尔生理学或医学奖的预测方法，而未被其预测却最终获得诺贝尔奖的原因可能是传统被引指标无法探测到论文的潜在临床影响力。本文引入美国NIH（National Institutes of Health）提出的论文临床转化潜力近似值指标（approximate potential to translate scores，APT），选择诺贝尔生理学或医学奖得主的论文集为样本，比较被引文桂冠奖预测和未被预测两组作者论文集的总被引次数、加权RCR（relative citation ratio）、被临床论文引用次数、APT均值、Human均值、Animal均值、Mol/Cell（Molecular/Cellular）均值这7项指标，以及转化力三角形模型的差异与指标间的相关性。被预测获奖和未被预测获奖两组论文的总被引次数、加权RCR、Mol/Cell均值有显著差异，未被预测组的Human均值与Animal均值及中位数均高于被预测组。从三角形模型上来看，被预测组的Mol/Cell均值较为明显，未被预测组的Human均值和Animal均值较明显。从相关分析结果可以看出，Mol/Cell均值与总被引次数显著正相关，而Animal均值与总被引次数显著负相关（P<0.05），Human均值与总被引次数相关性不显著。引文桂冠奖中使用的被引次数无法评价或预测临床转化方面的影响力，对分子、细胞生物学层面的基础研究影响力测度更为敏感，而对动物实验和临床研究影响力缺乏敏感性。而APT指标可较好地测度论文未来临床转化潜力，可考虑纳入科技论文评价指标体系，以弥补单纯基于引文分析指标的不足。
陈斯斯, 刘春丽. 论文临床影响力评价及预测指标的实证研究[J]. 情报学报, 2022, 41(2): 142-154.
Chen Sisi, Liu Chunli. Exploring the Clinical Impact Predictors of Papers— Based on the Empirical Analysis of Publications from Nobel Prize Winners in Physiology or Medicine. 情报学报, 2022, 41(2): 142-154.
1 Fasolo A, Sessa C. Translational research in phase I trials[J]. Clinical and Translational Oncology, 2009, 11(9): 580-588. 2 Contopoulos-Ioannidis D G, Alexiou G A, Gouvias T C, et al. Life cycle of translational research for medical interventions[J]. Science, 2008, 321(5894): 1298-1299. 3 Hanney S R, Castle-Clarke S, Grant J, et al. How long does biomedical research take? Studying the time taken between biomedical and health research and its translation into products, policy, and practice[J]. Health Research Policy and Systems, 2015, 13: 1. 4 McNamee L M, Walsh M J, Ledley F D. Timelines of translational science: from technology initiation to FDA approval[J]. PLoS One, 2017, 12(5): e0177371. 5 Wang D S, Song C M, Barabási A L. Quantifying long-term scientific impact[J]. Science, 2013, 342(6154): 127-132. 6 Weber G M. Identifying translational science within the triangle of biomedicine[J]. Journal of Translational Medicine, 2013, 11: 126. 7 杜建, 唐小利, 张燕舞, 等. 引文网络加速转化医学T1-T2-T3阶段的转化进程[J]. 中华临床营养杂志, 2013, 21(2): 98-102. 8 杜建, 唐小利. 为转化医学研究提供信息支撑——医学图情服务的新方向[J]. 图书情报工作, 2013, 57(20): 62-67. 9 Williams R S, Lotia S, Holloway A K, et al. From scientific discovery to cures: bright stars within a galaxy[J]. Cell, 2015, 163(1): 21-23. 10 Ke Q. Identifying translational science through embeddings of controlled vocabularies[J]. Journal of the American Medical Informatics Association, 2019, 26(6): 516-523. 11 Hutchins B I, Davis M T, Meseroll R A, et al. Predicting translational progress in biomedical research[J]. PLoS Biology, 2019, 17(10): e3000416. 12 iCite[EB/OL]. [2020-10-27]. https://icite.od.nih.gov/. 13 Hutchins B I, Yuan X, Anderson J M, et al. Relative Citation Ratio (RCR): a new metric that uses citation rates to measure influence at the article level[J]. PLoS Biology, 2016, 14(9): e1002541. 14 Ioannidis J P, Boyack K, Wouters P F. Citation metrics: a primer on how (not) to normalize[J]. PLoS Biology, 2016, 14(9): e1002542. 15 陈斯斯, 刘春丽. 基于共引网络的出版物影响力评价新指标: 相对引用率[J]. 情报理论与实践, 2020, 43(7): 75-80. 16 Nobel success[EB/OL]. [2020-10-27]. https://clarivate.com/webofsciencegroup/solutions/successful-predictions/. 17 Garfield E. Citation indexes for science: a new dimension in documentation through association of ideas[J]. Science, 1955, 122(3159): 108-111. 18 王琳, 岳卫平. 基于引文分析的诺贝尔奖级科学家遴选——科睿唯安“引文桂冠奖”详解[J]. 世界科技研究与发展, 2019, 41(5): 447-454. 19 李正红, 李玉玲, 于双成. 我国诺贝尔生理学或医学奖研究的文献分析[J]. 医学与哲学(A), 2017, 38(2): 95-97. 20 章娟, 段志光, 于琦, 等. 中科院院士与诺贝尔生理学或医学奖获得者获奖前SCI论文比较[J]. 医学与哲学(A), 2016, 37(1): 22-26. 21 杜建, 武夷山. 基于被引速率指标识别睡美人文献及其“王子”——以2014年诺贝尔化学奖得主Stefan Hell的睡美人文献为例[J]. 情报学报, 2015, 34(5): 508-521. 22 鲍玉芳, 马建霞. 诺贝尔奖与科学家论文数量、被引频次的相关性——基于2000—2010年诺贝尔化学、物理学获奖者的实证研究[J]. 图书馆理论与实践, 2015(8): 40-45. 23 李江, 姜明利, 李玥婷. 引文曲线的分析框架研究——以诺贝尔奖得主的引文曲线为例[J]. 中国图书馆学报, 2014, 40(2): 41-49. 24 The Nobel Prize awarding institutions[EB/OL]. [2020-10-27]. https://www.nobelprize.org/the-nobel-prize-organisation/prize-awarding-institutions/. 25 Nomination and selection of literature laureates[EB/OL]. [2020-10-27]. https://www.nobelprize.org/nomination/literature/. 26 屠呦呦, 倪慕云, 钟裕容, 等. 中药青蒿化学成分的研究Ⅰ[J]. 药学学报, 1981, 16(5): 366-370. 27 曾建勋. 破除“SCI至上”需要弘扬“同行评议”[J]. 数字图书馆论坛, 2020(2): 1-2. 28 中国科学技术协会. 高质量科技期刊分级目录总汇[EB/OL]. (2021-11-04) [2021-01-04]. https://www.cast.org.cn/art/2021/11/4/art_43_172464.html. 29 Ioannidis J P A, Boyack K W, Small H, et al. Bibliometrics: is your most cited work your best?[J]. Nature, 2014, 514(7524): 561-562. 30 Ioannidis J P A, Klavans R, Boyack K W. Multiple citation indicators and their composite across scientific disciplines[J]. PLoS Biology, 2016, 14(7): e1002501. 31 Erren T C, Shaw D M, Gro? J V. How to avoid haste and waste in occupational, environmental and public health research[J]. Journal of Epidemiology and Community Health, 2015, 69(9): 823-825. 32 Ioannidis J P A, Khoury M J. Assessing value in biomedical research: the PQRST of appraisal and reward[J]. JAMA, 2014, 312(5): 483-484.
