Evidence synthesis for constructing directed acyclic graphs (ESC-DAGs): a novel and systematic method for building directed acyclic graphs

Ferguson, K. D., McCann, M. , Katikireddi, S. V. , Thomson, H. , Green, M. J. , Smith, D. J. and Lewsey, J. D. (2019) Evidence synthesis for constructing directed acyclic graphs (ESC-DAGs): a novel and systematic method for building directed acyclic graphs. International Journal of Epidemiology, (doi:10.1093/ije/dyz150) (PMID:31325312) (Early Online Publication)

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Abstract

Background: Directed acyclic graphs (DAGs) are popular tools for identifying appropriate adjustment strategies for epidemiological analysis. However, a lack of direction on how to build them is problematic. As a solution, we propose using a combination of evidence synthesis strategies and causal inference principles to integrate the DAG-building exercise within the review stages of research projects. We demonstrate this idea by introducing a novel protocol: ‘Evidence Synthesis for Constructing Directed Acyclic Graphs’ (ESC-DAGs)’. Methods: ESC-DAGs operates on empirical studies identified by a literature search, ideally a novel systematic review or review of systematic reviews. It involves three key stages: (i) the conclusions of each study are ‘mapped’ into a DAG; (ii) the causal structures in these DAGs are systematically assessed using several causal inference principles and are corrected accordingly; (iii) the resulting DAGs are then synthesised into one or more ‘integrated DAGs’. This demonstration article didactically applies ESC-DAGs to the literature on parental influences on offspring alcohol use during adolescence. Conclusions: ESC-DAGs is a practical, systematic and transparent approach for developing DAGs from background knowledge. These DAGs can then direct primary data analysis and DAG-based sensitivity analysis. ESC-DAGs has a modular design to allow researchers who are experienced DAG users to both use and improve upon the approach. It is also accessible to researchers with limited experience of DAGs or evidence synthesis.

Item Type:Articles
Status:Early Online Publication
Refereed:Yes
Glasgow Author(s) Enlighten ID:Thomson, Dr Hilary and Katikireddi, Dr Vittal and Lewsey, Professor Jim and Green, Dr Michael and Smith, Professor Daniel and McCann, Dr Mark and Ferguson, Karl
Authors: Ferguson, K. D., McCann, M., Katikireddi, S. V., Thomson, H., Green, M. J., Smith, D. J., and Lewsey, J. D.
College/School:College of Medical Veterinary and Life Sciences > Institute of Health and Wellbeing > Health Economics and Health Technology Assessment
College of Medical Veterinary and Life Sciences > Institute of Health and Wellbeing > MRC/CSO SPHSU
College of Medical Veterinary and Life Sciences > Institute of Health and Wellbeing > Mental Health and Wellbeing
Journal Name:International Journal of Epidemiology
Publisher:Oxford University Press
ISSN:0300-5771
ISSN (Online):1464-3685
Published Online:19 July 2019
Copyright Holders:Copyright © 2019 The Authors
First Published:First published in International Journal of Epidemiology 2019
Publisher Policy:Reproduced under a Creative Commons License

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Project CodeAward NoProject NamePrincipal InvestigatorFunder's NameFunder RefLead Dept
727661SPHSU Core Renewal: Complexity in Health Improvement Research ProgrammeLaurence MooreMedical Research Council (MRC)MC_UU_12017/14IHW - MRC/CSO SPHU
SPHSU14
727651SPHSU Core Renewal: Measuring and Analysing Socioeconomic Inequalities in Health Research ProgrammeAlastair LeylandMedical Research Council (MRC)MC_UU_12017/13IHW - MRC/CSO SPHU
727671SPHSU Core Renewal: Informing Healthy Public Policy Research ProgrammePeter CraigMedical Research Council (MRC)MC_UU_12017/15IHW - MRC/CSO SPHU
SPHSU13
SPHSU15

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