Stacey J. Winham
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Automated Density Measures for Estimating Breast Cancer Risk and Therapy Response
Open Date: 2013-09-01
Close Date: 2018-08-31
Articles (11)
Year:
2023
Year:
2023
Mendelian randomization has become a popular tool to assess causal relationships using existing observational data. While randomized controlled trials are considered the gold standard for establishing causality between exposures and outcomes, it is not always feasible to conduct a trial. Mendelian randomization is a causal inference method that uses observational data to infer causal relationships by using genetic variation as a surrogate for the exposure of interest. Publications using the approach have increased dramatically in recent years, including in the field of hepatology. In this concise review, we describe the concepts, assumptions, and interpretation of Mendelian randomization as related to studies in hepatology. We focus on the strengths and weaknesses of the approach for a non-statistical audience, using an illustrative example to assess the causal relationship between body mass index and NAFLD.
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2023
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2023
Year:
2023
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2022
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2021
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2021
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2021
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2021
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2021
Collaborators (9)
Karla Kerlikowske
University of California
Melissa Wilson
Associate Professor
Arizona State University
Joanna Biernacka
Associate Professor
Mayo Clinic
Andrew Maidment
Associate Professor, Clinician-Educator
University of Pennsylvania
Barbara Stranger
Associate Professor
Northwestern University Feinberg School of Medicine
Lea Davis
Assistant Professor
Vanderbilt University
Joanna Martin
Karolinska Institutet
Lambert Leong
University of Hawai'i Cancer Center
Aimilia Gastounioti
Assistant Professor
Washington University in St. Louis
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