Stacey J. Winham

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Mayo Clinic College of Medicine and Science
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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

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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

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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

UNITED STATES
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Melissa Wilson

Associate Professor

Arizona State University

UNITED STATES
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Joanna Biernacka

Associate Professor

Mayo Clinic

UNITED STATES
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Andrew Maidment

Associate Professor, Clinician-Educator

University of Pennsylvania

UNITED STATES
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Barbara Stranger

Associate Professor

Northwestern University Feinberg School of Medicine

UNITED STATES
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Lea Davis

Assistant Professor

Vanderbilt University

UNITED STATES
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Joanna Martin

Karolinska Institutet

SWEDEN
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Lambert Leong

University of Hawai'i Cancer Center

UNITED STATES
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Aimilia Gastounioti

Assistant Professor

Washington University in St. Louis

UNITED STATES
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