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2013年至2022年卵巢癌耐药性的文献计量学与可视化分析

Bibliometric and visualized analysis of drug resistance in ovarian cancer from 2013 to 2022.

作者信息

Liu Jiahua, Ma Junnan, Zhang Jiarong, Li Chengming, Yu Bowen, Choe Hyok Chol, Ding Kaiyue, Zhang Liu, Zhang Lin

机构信息

Institute (College) of Integrative Medicine, Dalian Medical University, Dalian, China.

出版信息

Front Oncol. 2023 May 18;13:1173863. doi: 10.3389/fonc.2023.1173863. eCollection 2023.

DOI:10.3389/fonc.2023.1173863
PMID:37324006
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10263169/
Abstract

OBJECTIVE

As one of the cancers that seriously threatens women's health, ovarian cancer has a high morbidity and mortality rate. Surgery and chemotherapy are the basic treatment strategies for ovarian cancer, and chemotherapy resistance is a significant factor in affecting the prognosis, survival cycle, and recurrence of ovarian cancer. This article aims to analyze articles about ovarian cancer and drug resistance via bibliometric software, offering new ideas and directions for researchers in this field.

METHODS

Both Citespace and Vosviewer are bibliometric software on the Java platform. Articles were collected on ovarian cancer and drug resistance in the Web of Science Core Collection database from 2013 to 2022. The countries, institutions, journals, authors, keywords, and references were analyzed, and the development status of this field was indicated from multiple perspectives.

RESULTS

Studies on ovarian cancer and drug resistance generally showed an increasing trend from 2013 to 2022. The People's Republic of China and Chinese institutions contributed more to this field. published the most articles, and the journal with the most citations was . Li Li was the author with the most publications, and Siegel RL was the author with the most citations. Through burst detection, it can be found that the research hotspots in this field mainly focused on the in-depth exploration of the drug resistance mechanism of ovarian cancer and the progress of PARP inhibitors and bevacizumab in the treatment of ovarian cancer.

CONCLUSIONS

Many studies on the mechanism of drug resistance in ovarian cancer have been discovered; however, the deeper mechanism remains to be explored. Compared with traditional chemotherapy drugs, PARP inhibitors and bevacizumab have shown better efficacy, but PARP inhibitors have initially shown drug resistance. The future direction of this field should be to overcome the resistance of existing drugs and actively develop new ones.

摘要

目的

卵巢癌作为严重威胁女性健康的癌症之一，发病率和死亡率较高。手术和化疗是卵巢癌的基本治疗策略，化疗耐药是影响卵巢癌预后、生存周期及复发的重要因素。本文旨在通过文献计量软件分析关于卵巢癌与耐药性的文章，为该领域研究人员提供新思路和方向。

方法

Citespace和Vosviewer均为基于Java平台的文献计量软件。收集2013年至2022年Web of Science核心合集数据库中关于卵巢癌与耐药性的文章。对国家、机构、期刊、作者、关键词及参考文献进行分析，从多个角度呈现该领域的发展状况。

结果

2013年至2022年，卵巢癌与耐药性的研究总体呈上升趋势。中华人民共和国及中国机构对该领域贡献较大。发表文章最多，被引频次最高的期刊是 。李丽是发文量最多的作者，Siegel RL是被引频次最高的作者。通过突现检测发现，该领域研究热点主要集中在卵巢癌耐药机制的深入探索以及PARP抑制剂和贝伐单抗在卵巢癌治疗中的进展。

结论

已发现许多关于卵巢癌耐药机制的研究；然而，更深层次的机制仍有待探索。与传统化疗药物相比，PARP抑制剂和贝伐单抗已显示出更好的疗效，但PARP抑制剂已初步出现耐药。该领域未来方向应是克服现有药物的耐药性并积极研发新药。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2f2e/10263169/9afb759efc1b/fonc-13-1173863-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2f2e/10263169/e98b24b59839/fonc-13-1173863-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2f2e/10263169/3145ed98bf33/fonc-13-1173863-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2f2e/10263169/c33522de8df1/fonc-13-1173863-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2f2e/10263169/36f28e7f28ab/fonc-13-1173863-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2f2e/10263169/e42eaf1b5412/fonc-13-1173863-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2f2e/10263169/c726738ffa3a/fonc-13-1173863-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2f2e/10263169/22bda74a93eb/fonc-13-1173863-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2f2e/10263169/2e99c980194a/fonc-13-1173863-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2f2e/10263169/9afb759efc1b/fonc-13-1173863-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2f2e/10263169/e98b24b59839/fonc-13-1173863-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2f2e/10263169/3145ed98bf33/fonc-13-1173863-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2f2e/10263169/c33522de8df1/fonc-13-1173863-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2f2e/10263169/36f28e7f28ab/fonc-13-1173863-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2f2e/10263169/e42eaf1b5412/fonc-13-1173863-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2f2e/10263169/c726738ffa3a/fonc-13-1173863-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2f2e/10263169/22bda74a93eb/fonc-13-1173863-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2f2e/10263169/2e99c980194a/fonc-13-1173863-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2f2e/10263169/9afb759efc1b/fonc-13-1173863-g009.jpg

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