title: Trend and Network Analysis of Common Eligibility Features for Cancer Trials in ClinicalTrials.gov.
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.
authors.affiliation: Department of Biomedical Informatics, Columbia University, New York City, USA.
authors.forename: Chunhua
authors.initials: C
authors.lastname: Weng
authors.affiliation: Department of Computer Science, The City College of New York, New York City, USA.
authors.forename: Anil
authors.initials: A
authors.lastname: Yaman
authors.affiliation: Department of Biomedical Informatics, Columbia University, New York City, USA.
authors.forename: Kuo
authors.initials: K
authors.lastname: Lin
authors.affiliation: Department of Biomedical Informatics, Columbia University, New York City, USA.
authors.forename: Zhe
authors.initials: Z
authors.lastname: He
keywords: Clinical Trials; Knowledge Management; Patient Selection