Literature DB >> 22364797

Confounding and control of confounding in nonexperimental studies of medications in patients with CKD.

Brian D Bradbury1, David T Gilbertson, M Alan Brookhart, Ryan D Kilpatrick.   

Abstract

Confounding is an important source of bias in nonexperimental studies, arising when the effect of an exposure on the occurrence of an outcome is distorted by the effect of some other factor. In nonexperimental studies of patients with CKD or who are on chronic dialysis, confounding is a significant concern owing to the high burden of comorbid disease, extent of required clinical management, and high frequency of adverse clinical events in this patient population. Confounding can be addressed in both the design stage (restriction, accurate measurement of confounders) and analysis stage (stratification, multivariable adjustment, propensity scores, marginal structural models, instrumental variable) of a study. Time-dependent confounding and confounding by indication are 2 special cases of confounding that can arise in studies of treatment effects and may require more sophisticated analytic techniques to adequately address. The availability and expanded use of large health care databases have ensured greater precision and have now placed the focus on validity. Addressing the major threats to validity, such as confounding, should be a first-order concern.
© 2012 National Kidney Foundation, Inc. Published by Elsevier Inc. All rights reserved.

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Year:  2012        PMID: 22364797     DOI: 10.1053/j.ackd.2012.01.001

Source DB:  PubMed          Journal:  Adv Chronic Kidney Dis        ISSN: 1548-5595            Impact factor:   3.620


  5 in total

1.  Health Economics and Outcomes Research of Wound Care: Overview of Methodology.

Authors:  Adrienne M Gilligan
Journal:  Adv Wound Care (New Rochelle)       Date:  2018-11-12       Impact factor: 4.730

Review 2.  Methods to control for unmeasured confounding in pharmacoepidemiology: an overview.

Authors:  Md Jamal Uddin; Rolf H H Groenwold; Mohammed Sanni Ali; Anthonius de Boer; Kit C B Roes; Muhammad A B Chowdhury; Olaf H Klungel
Journal:  Int J Clin Pharm       Date:  2016-04-18

3.  Confounding in Observational Studies Evaluating the Safety and Effectiveness of Medical Treatments.

Authors:  Magdalene M Assimon
Journal:  Kidney360       Date:  2021-05-14

4.  The greatly misunderstood erythropoietin resistance index and the case for a new responsiveness measure.

Authors:  Yossi Chait; Sahir Kalim; Joseph Horowitz; Christopher V Hollot; Elizabeth D Ankers; Michael J Germain; Ravi I Thadhani
Journal:  Hemodial Int       Date:  2016-02-03       Impact factor: 1.812

5.  Antihypertensive medications and risk of death and hospitalizations in US hemodialysis patients: Evidence from a cohort study to inform hypertension treatment practices.

Authors:  Tariq Shafi; Stephen M Sozio; Jason Luly; Karen J Bandeen-Roche; Wendy L St Peter; Patti L Ephraim; Aidan McDermott; Charles A Herzog; Deidra C Crews; Julia J Scialla; Navdeep Tangri; Dana C Miskulin; Wieneke M Michels; Bernard G Jaar; Philip G Zager; Klemens B Meyer; Albert W Wu; L Ebony Boulware
Journal:  Medicine (Baltimore)       Date:  2017-02       Impact factor: 1.889

  5 in total

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