Using causal diagrams within the Grading of Recommendations, Assessment, Development and Evaluation framework to evaluate confounding adjustment in observational studies

Abstract

Background and Objectives

The current Grading of Recommendations, Assessment, Development and Evaluation (GRADE) system instructs appraisers to evaluate whether individual observational studies have sufficiently adjusted for confounding. However, it does not provide an explicit, transparent, or reproducible method for doing so. This article explores how implementing causal graphs into the GRADE framework can help appraisers and end-users of GRADE products to evaluate the adequacy of confounding control from observational studies.

Methods

Using modern epidemiological theory, we propose a system for incorporating causal diagrams into the GRADE process to assess confounding control.

Results

Integrating causal graphs into the GRADE framework enables appraisers to provide a theoretically grounded rationale for their evaluations of confounding control in observational studies. Additionally, the inclusion of causal graphs in GRADE may assist appraisers in demonstrating evidence for their appraisals in other domains of quality of evidence beyond confounding control. To support practical application, a worked example is included in the supplemental material to guide users through this approach.

Conclusion

GRADE calls for the explicit and transparent appraisal of evidence in the process of evidence synthesis. Incorporating causal diagrams into the evaluation of confounding control in observational studies aligns with the core principles of the GRADE framework, providing a clear, theory-based method for the adequacy of confounding control in observational studies.