Literature DB >> 23920601

A method for probing disease relatedness using common clinical eligibility criteria.

Mary Regina Boland1, Riccardo Miotto, Chunhua Weng.   

Abstract

Clinical trial eligibility criteria define fine-grained characteristics of research volunteers for various disease trials and hence are a promising data source for disease profiling. This paper explores the feasibility of using disease-specific common eligibility features (CEFs) for representing diseases and understanding their relatedness. We extracted disease-specific CEFs from eligibility criteria on ClinicalTrials.gov for three illustrative categories - cancers, mental disorders and chronic diseases - each including seven diseases. We then constructed disease-specific CEF networks to assess the degree of overlap among the diseases. Using these automatically derived networks, we observed several findings that were confirmed in medicine. For example, we highlighted connections among schizophrenia, epilepsy and depression. We also identified a link between Crohn's disease and arthritis. These observations confirm the value of using clinical trial eligibility criteria for identifying disease relatedness. We further discuss the implications of CEFs for standardizing clinical trial eligibility criteria through reuse.

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Year:  2013        PMID: 23920601      PMCID: PMC3803102     

Source DB:  PubMed          Journal:  Stud Health Technol Inform        ISSN: 0926-9630


  8 in total

1.  Cancer risk in patients with earlier diagnosis of cutaneous melanoma in situ.

Authors:  C Wassberg; M Thörn; J Yuen; T Hakulinen; U Ringborg
Journal:  Int J Cancer       Date:  1999-10-29       Impact factor: 7.396

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Authors:  Paul Shannon; Andrew Markiel; Owen Ozier; Nitin S Baliga; Jonathan T Wang; Daniel Ramage; Nada Amin; Benno Schwikowski; Trey Ideker
Journal:  Genome Res       Date:  2003-11       Impact factor: 9.043

3.  Characteristics of clinical trials registered in ClinicalTrials.gov, 2007-2010.

Authors:  Robert M Califf; Deborah A Zarin; Judith M Kramer; Rachel E Sherman; Laura H Aberle; Asba Tasneem
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4.  Network analysis of clinical trials on depression: implications for comparative effectiveness research.

Authors:  Suresh K Bhavnani; Simona Carini; Jessica Ross; Ida Sim
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5.  Association of CYP1B1 genetic polymorphism with incidence to breast and lung cancer.

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6.  Depression and schizophrenia in epilepsy: social and biological risk factors.

Authors:  E B Schmitz; M M Robertson; M R Trimble
Journal:  Epilepsy Res       Date:  1999-05       Impact factor: 3.045

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  8 in total
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  8 in total

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