Trend and network analysis of common eligibility features for cancer trials in ClinicalTrials.gov

Chunhua Weng, Anil Yaman, Kuo Lin, Zhe He

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

6 Citations (Scopus)

Abstract

ClinicalTrials.gov has been archiving clinical trials since 1999, with > 165,000 trials at present. It is a valuable but relatively untapped resource for understanding trial design patterns and acquiring reusable trial design knowledge. We extracted common eligibility features using an unsupervised tag-mining method and mined their temporal usage patterns in clinical trials on various cancers. We then employed trend and network analysis to investigate two questions: (1) what eligibility features are frequently used to select patients for clinical trials within one cancer or across multiple cancers; and (2) what are the trends in eligibility feature adoption or discontinuation across cancer research domains? Our results showed that each cancer domain reuses a small set of eligibility features frequently for selecting cancer trial patients and some features are shared across different cancers, with value range adjustments for numerical measures. We discuss the implications for facilitating community-based clinical research knowledge sharing and reuse.

Original languageEnglish
Title of host publication Smart Health : international conference
EditorsXialong Zheng, Daniel Zeng, Hsinchun Chen, Yong Zhang, Chunxiao Xing, Daniel B. Neill
Place of PublicationBerlin
PublisherSpringer
Pages130-141
Number of pages12
ISBN (Print)978-3-319-08415-2
DOIs
Publication statusPublished - Jul 2014
EventICSH: International Conference on Smart Health - Beijing, China
Duration: 10 Jun 201411 Jun 2014
Conference number: 2014

Publication series

NameLecture Notes in Computer Science
Volume8549

Conference

ConferenceICSH: International Conference on Smart Health
Abbreviated titleICSH
Country/TerritoryChina
CityBeijing
Period10/06/1411/06/14

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