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. 2021 Sep 21;326(11):1045-1056.
doi: 10.1001/jama.2021.14075.

A Guideline for Reporting Mediation Analyses of Randomized Trials and Observational Studies: The AGReMA Statement

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A Guideline for Reporting Mediation Analyses of Randomized Trials and Observational Studies: The AGReMA Statement

Hopin Lee et al. JAMA. .

Abstract

Importance: Mediation analyses of randomized trials and observational studies can generate evidence about the mechanisms by which interventions and exposures may influence health outcomes. Publications of mediation analyses are increasing, but the quality of their reporting is suboptimal.

Objective: To develop international, consensus-based guidance for the reporting of mediation analyses of randomized trials and observational studies (A Guideline for Reporting Mediation Analyses; AGReMA).

Design, setting, and participants: The AGReMA statement was developed using the Enhancing Quality and Transparency of Health Research (EQUATOR) methodological framework for developing reporting guidelines. The guideline development process included (1) an overview of systematic reviews to assess the need for a reporting guideline; (2) review of systematic reviews of relevant evidence on reporting mediation analyses; (3) conducting a Delphi survey with panel members that included methodologists, statisticians, clinical trialists, epidemiologists, psychologists, applied clinical researchers, clinicians, implementation scientists, evidence synthesis experts, representatives from the EQUATOR Network, and journal editors (n = 19; June-November 2019); (4) having a consensus meeting (n = 15; April 28-29, 2020); and (5) conducting a 4-week external review and pilot test that included methodologists and potential users of AGReMA (n = 21; November 2020).

Results: A previously reported overview of 54 systematic reviews of mediation studies demonstrated the need for a reporting guideline. Thirty-three potential reporting items were identified from 3 systematic reviews of mediation studies. Over 3 rounds, the Delphi panelists ranked the importance of these items, provided 60 qualitative comments for item refinement and prioritization, and suggested new items for consideration. All items were reviewed during a 2-day consensus meeting and participants agreed on a 25-item AGReMA statement for studies in which mediation analyses are the primary focus and a 9-item short-form AGReMA statement for studies in which mediation analyses are a secondary focus. These checklists were externally reviewed and pilot tested by 21 expert methodologists and potential users, which led to minor adjustments and consolidation of the checklists.

Conclusions and relevance: The AGReMA statement provides recommendations for reporting primary and secondary mediation analyses of randomized trials and observational studies. Improved reporting of studies that use mediation analyses could facilitate peer review and help produce publications that are complete, accurate, transparent, and reproducible.

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Conflict of interest statement

Conflict of Interest Disclosures: Dr Lamb reported being a member of boards for the Health Technology Assessment (additional capacity funding board, end of life care and add-on studies board, prioritization group board, and trauma board). Dr VanderWeele reported receiving personal fees from Statistical Horizons. Dr Localio reported receiving grants from the Annals of Internal Medicine. Dr Guallar reported receiving personal fees from the American College of Physicians (Annals of Internal Medicine). Dr Kamper reported receiving grants from the National Health and Medical Research Council of Australia Fellowship. No other disclosures were reported.

Figures

Figure.
Figure.. Causal Directed Acyclic Graph Depicting Typical Variables and Relationships That Are Relevant to Mediation Analyses
A confounder of the association between an exposure and a mediator or between an exposure and an outcome is a preexposure variable that is associated with the exposure and with the mediator or outcome, respectively. A confounder of the association between a mediator and an outcome is a premediator variable (possibly affected by the exposure) that is associated with the mediator and outcome. Because confounders can distort associations, controlling for confounders of the exposure-mediator, exposure-outcome, and mediator-outcome associations is important in mediation analyses. A collider on a path in the causal directed acyclic graph between 2 variables is a variable that is affected by both variables. Standard adjustment for a collider typically introduces selection bias and special care may be needed when controlling for colliders. Effect modification (interaction) cannot be depicted in a standard directed acyclic graph.

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