Breaking Down Bias: A Methodological Primer on Identifying, Evaluating, and Mitigating Bias in Cardiovascular...

Area of Science:

• Cardiovascular Research
• Epidemiology
• Biostatistics

Background:

• Systematic error (bias) is a significant challenge in observational cardiovascular research.
• Bias can profoundly impact study design, conduct, interpretation, and lead to misleading results.
• Misinformation from biased research can negatively affect clinical practice and patient outcomes.

Purpose of the Study:

• To provide a concise introduction to identifying, evaluating, and mitigating bias in observational cardiovascular research.
• To discuss common biases in longitudinal cardiovascular studies, including selection bias, information bias, confounding, competing risks, immortal time bias, and confounding by indication.
• To highlight strategies and tools for minimizing and assessing bias to enhance causal association estimation.

Main Methods:

• Theoretical overview of 3 main types of bias: selection bias, information bias, and confounding.
• Discussion of specialized biases in longitudinal cardiovascular research: competing risks, immortal time bias, confounding by indication.
• Highlighting strategies: target trial framework, directed acyclic graphs (DAGs), quantitative bias analysis, and risk of bias assessments.

Main Results:

• The review synthesizes key concepts and practical approaches for bias management in observational cardiovascular research.
• It provides a framework for researchers to critically assess and address potential biases in their studies.
• Examples from cardiovascular literature illustrate the theoretical concepts and practical implications of bias.

Conclusions:

• Effective identification, evaluation, and mitigation of bias are crucial for valid observational cardiovascular research.
• Utilizing tools like the target trial framework and DAGs can strengthen study design and reduce bias.
• This primer aims to improve the accuracy of causal association estimation in cardiovascular research, benefiting researchers and healthcare professionals.