Multivariable Confounding Adjustment in Distributed Data Networks without Sharing of Patient-Level Data

    Basic Details
    Date
    Monday, July 22, 2013
    Type
    Publication
    Medical Product
    aliskiren
    angiotensin II receptor blocker (ARB)
    angiotensin-converting enzyme (ACE) inhibitor
    Health Outcome(s)
    angioedema
    Description

    This article describes two approaches to conducting multivariable analyses for multi-site studies without sharing of patient-level data across sites: the case-centered logistic regression approach and the inverse variance-weighted meta-analysis approach.  The authors evaluate the above methods 1) by analyzing risks of angioedema associated with use of angiotensin-converting enzyme inhibitors, antiotensin II receptor blockers, and aliskiren, compared to use of beta-blockers in the Mini-Sentinel Distributed Database (MSDD), and 2) by performing simulations.

    Information
    Time Period
    2001-2010
    Data Source(s)
    Mini-Sentinel Distributed Database (MSDD)
    Author(s)

    Sengwee Toh ScD; Marsha E. Reichman PhD; Monika Houstoun PharmD; Xiao Ding PhD; Bruce H. Fireman MA; Eric Gravel; Mark Levenson PhD; Lingling Li PhD; Erick Moyneur; Azadeh Shoaibi PhD, MHS; Gwen Zornberg MD, MS, ScD; Sean Hennessy PharmD, PhD 

    Corresponding Author

    S. Toh, ScD, Department of Population Medicine, Harvard Pilgrim Healthcare Institute and Harvard Medical School, 401 Park Drive, Suite 401 East, Boston, MA 02215, USA. Email: darren_toh@harvardpilgrim.org