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癌症免疫治疗生物标志物的全球研究趋势:可视化和文献计量分析

Yuan Qiao¹, Dong Xie², Zhengxiang Li²

¹Department of Clinical Pharmacy, Yan'an University Affiliated Hospital, Yan'an, Shaanxi, China.

Human vaccines & immunotherapeutics

|January 8, 2025

概括

这项研究分析了从1993年到2023年的2686篇关于癌症生物标志物的出版物. 人工智能和机器学习正在成为识别生物标志物的关键工具,并在瘤学中推进精准医学.

科学领域:

在瘤学瘤学.
免疫治疗是一种免疫疗法.
生物标志物研究生物标志物研究

背景情况:

全球癌症负担正在增加,需要改进治疗策略.
癌症免疫疗法看起来很有前途,但反应率有限.
生物标志物对于预测治疗疗效和指导个性化医疗至关重要.

研究的目的:

从1993年到2023年,确定癌症生物标志物发现的研究趋势和热点.
分析与癌症免疫治疗相关的生物标志物研究的演变.
突出新兴技术及其对生物标志物识别的影响.

主要方法:

从Web of Science核心集合中对2686个出版物的图书法分析.
使用CiteSpace,VOSviewer和R-bibliometrix对研究趋势进行可视化.
分析出版量,主要机构和地理分布.

主要成果:

自2015年以来,出版量显示出显著的上升趋势,美国是主要贡献者.
研究热点包括PD-1/PD-L1,CTLA-4,基因表达,TMB,BMI,微生物群,T细胞和基于血液的标记物 (LDH,NLR,细胞因子).
在过去的两年里,人工智能和机器学习已经成为生物标志物发现的关键研究领域.

结论:

生物标志物研究正在迅速发展,这是技术进步和对癌症生物学日益增长的理解所推动的.
发展中国家需要加强对全球生物标志物研究的参与和贡献.
人工智能和机器学习在瘤学领域具有重要的精准医学潜力,因为它们可以从复杂的数据集中识别新的生物标志物.

关键词:

生物标志物生物标志物文献数量计学文献数量计学文献量计学癌症癌症癌症癌症癌症免疫检查点抑制剂免疫检查点抑制剂免疫疗法免疫疗法视觉化分析分析

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