Title:Multiple Sclerosis Risk Among Anti-tumor Necrosis Factor Alpha Users:
A Methodological Review of Observational Studies Based on Real-world
Data
Volume: 19
Issue: 2
Author(s): Lingyi Li, Mahyar Etminan*, Gilaad G. Kaplan, Helen Tremlett, Hui Xie and J. Antonio Aviña-Zubieta*
Affiliation:
- Experimental Medicine Program, University of British Columbia, Vancouver, British Columbia, Canada
- Department of Ophthalmology and Visual Sciences, Medicine
and Pharmacology, University of British Columbia, Vancouver, British Columbia, Canada
- Experimental Medicine Program, University of British Columbia, Vancouver, British Columbia, Canada
- Arthritis
Research Canada, Vancouver, British Columbia, Canada
- Division of Rheumatology, Faculty of Medicine, University of British Columbia,
Vancouver, British Columbia, Canada
Keywords:
Anti-TNFα, multiple sclerosis, causal directed acyclic graphs, confounding, collider, mediation.
Abstract: Epidemiologic studies on the risk of multiple sclerosis (MS) or demyelinating events associated
with anti-tumor necrosis factor alpha (TNFα) use among patients with rheumatic diseases
or inflammatory bowel diseases have shown conflicting results. Causal directed acyclic graphs
(cDAGs) are useful tools for understanding the differing results and identifying the structure of potential
contributing biases. Most of the available literature on cDAGs uses language that might be
unfamiliar to clinicians. This article demonstrates how cDAGs can be used to determine whether
there is a confounder, a mediator or collider-stratification bias and when to adjust for them appropriately.
We also use a case study to show how to control for potential biases by drawing a cDAG
depicting anti-TNFα use and its potential to contribute to MS onset. Finally, we describe potential
biases that might have led to contradictory results in previous studies that examined the effect of
anti-TNFα and MS, including confounding, confounding by contraindication, and bias due to
measurement error. Clinicians and researchers should be cognizant of confounding, confounding
by contraindication, and bias due to measurement error when reviewing future studies on the risk
of MS or demyelinating events associated with anti-TNFα use. cDAGs are a useful tool for selecting
variables and identifying the structure of different biases that can affect the validity of observational
studies.
