Literature DB >> 23515788

External phenome analysis enables a rational federated query strategy to detect changing rates of treatment-related complications associated with multiple myeloma.

Jeremy L Warner1, Gil Alterovitz, Kelly Bodio, Robin M Joyce.   

Abstract

Electronic health records (EHRs) are increasingly useful for health services research. For relatively uncommon conditions, such as multiple myeloma (MM) and its treatment-related complications, a combination of multiple EHR sources is essential for such research. The Shared Health Research Information Network (SHRINE) enables queries for aggregate results across participating institutions. Development of a rational search strategy in SHRINE may be augmented through analysis of pre-existing databases. We developed a SHRINE query for likely non-infectious treatment-related complications of MM, based upon an analysis of the Multiparameter Intelligent Monitoring in Intensive Care (MIMIC II) database. Using this query strategy, we found that the rate of likely treatment-related complications significantly increased from 2001 to 2007, by an average of 6% a year (p=0.01), across the participating SHRINE institutions. This finding is in keeping with increasingly aggressive strategies in the treatment of MM. This proof of concept demonstrates that a staged approach to federated queries, using external EHR data, can yield potentially clinically meaningful results.

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Year:  2013        PMID: 23515788      PMCID: PMC3721159          DOI: 10.1136/amiajnl-2012-001355

Source DB:  PubMed          Journal:  J Am Med Inform Assoc        ISSN: 1067-5027            Impact factor:   4.497


  20 in total

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3.  Multiparameter Intelligent Monitoring in Intensive Care II: a public-access intensive care unit database.

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9.  Lenalidomide plus dexamethasone for relapsed or refractory multiple myeloma.

Authors:  Meletios Dimopoulos; Andrew Spencer; Michael Attal; H Miles Prince; Jean-Luc Harousseau; Anna Dmoszynska; Jesus San Miguel; Andrzej Hellmann; Thierry Facon; Robin Foà; Alessandro Corso; Zvenyslava Masliak; Marta Olesnyckyj; Zhinuan Yu; John Patin; Jerome B Zeldis; Robert D Knight
Journal:  N Engl J Med       Date:  2007-11-22       Impact factor: 91.245

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Authors:  Jeremy L Warner; Gil Alterovitz
Journal:  AMIA Annu Symp Proc       Date:  2012-11-03
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  7 in total

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4.  pyPheWAS: A Phenome-Disease Association Tool for Electronic Medical Record Analysis.

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5.  Clinical and Pharmacological Aspects of Hospital-Acquired Acute Kidney Injuries Outside the Intensive Care Unit: A Phenome-Wide Association Study.

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6.  Characterizing phenotypic abnormalities associated with high-risk individuals developing lung cancer using electronic health records from the All of Us researcher workbench.

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Review 7.  The challenges, advantages and future of phenome-wide association studies.

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Journal:  Immunology       Date:  2014-02       Impact factor: 7.397

  7 in total

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