Trajectory analysis of drug-research trends in pancreatic cancer on PubMed and ClinicalTrials.gov

被引:9
|
作者
Jeong, Yoo Kyung [1 ]
Heo, Go Eun [1 ]
Kang, Keun Young [1 ]
Yoon, Dong Sup [2 ]
Song, Min [1 ]
机构
[1] Yonsei Univ, Dept Lib & Informat Sci, 50 Yonsei Ro, Seoul 120749, South Korea
[2] Yonsei Univ, Coll Med, Gangnam Severance Hosp, Pancreatobiliary Canc Clin,Dept Surg, Seoul, South Korea
基金
新加坡国家研究基金会;
关键词
Pancreatic cancer; Text mining; Bibliometric analysis; Data analysis; Information extraction; CONTINUOUS-INFUSION; 5-FLUOROURACIL; PHASE-II TRIAL; CELL ADHESION; GEMCITABINE; CAPECITABINE; CHEMOTHERAPY; COMBINATION; CARCINOMA; KNOWLEDGE; CETUXIMAB;
D O I
10.1016/j.joi.2016.01.003
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
Increasing interest in developing treatments for pancreatic cancer has led to a surge in publications in the field. Analyses of drug-research trends are needed to minimize risk in anti-cancer drug development. Here, we analyzed publications on anti-cancer drugs extracted from PubMed records and ClinicalTrials datasets. We conducted a drug cluster analysis by proposing the entity Dirichlet Multinomial Regression (eDMR) technique and in-depth network analysis of drug cluster and target proteins. The results show two distinct research clusters in both the ClinicalTrials dataset and the PubMed records. Specifically, various targets associated with anti-cancer drugs are investigated in new drug testing while the diverse chemicals are studied together with a standard therapeutic agent in the academic literature. In addition, our study confirms that drug research published in PubMed is preceded by clinical trials. Although we only evaluate drugs for pancreatic cancer in the present study, our method can be applied to drug-research trends of other diseases. (C) 2016 Elsevier Ltd. All rights reserved.
引用
收藏
页码:273 / 285
页数:13
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