Mechanisms and mediation in survival analysis: Towards an integrated analytical framework

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dc.contributor.author Pratschke, Jonathan
dc.contributor.author Haase, Trutz
dc.contributor.author Comber, Harry
dc.contributor.author Sharp, Linda
dc.contributor.author de Camargo Cancela, Marianna
dc.contributor.author Johnson, Howard
dc.date.accessioned 2017-06-20T11:39:46Z
dc.date.available 2017-06-20T11:39:46Z
dc.date.issued 2016-02-29
dc.identifier.citation Pratschke, J., Haase, T., Comber, H., Sharp, L., de Camargo Cancela, M. and Johnson, H. (2016) 'Mechanisms and mediation in survival analysis: towards an integrated analytical framework', BMC Medical Research Methodology, 16, 27 (13pp). doi: 10.1186/s12874-016-0130-6 en
dc.identifier.volume 16
dc.identifier.startpage 1
dc.identifier.endpage 13
dc.identifier.issn 1471-2288
dc.identifier.uri http://hdl.handle.net/10468/4116
dc.identifier.doi 10.1186/s12874-016-0130-6
dc.description.abstract Background: A wide-ranging debate has taken place in recent years on mediation analysis and causal modelling, raising profound theoretical, philosophical and methodological questions. The authors build on the results of these discussions to work towards an integrated approach to the analysis of research questions that situate survival outcomes in relation to complex causal pathways with multiple mediators. The background to this contribution is the increasingly urgent need for policy-relevant research on the nature of inequalities in health and healthcare. Methods: The authors begin by summarising debates on causal inference, mediated effects and statistical models, showing that these three strands of research have powerful synergies. They review a range of approaches which seek to extend existing survival models to obtain valid estimates of mediation effects. They then argue for an alternative strategy, which involves integrating survival outcomes within Structural Equation Models via the discrete-time survival model. This approach can provide an integrated framework for studying mediation effects in relation to survival outcomes, an issue of great relevance in applied health research. The authors provide an example of how these techniques can be used to explore whether the social class position of patients has a significant indirect effect on the hazard of death from colon cancer. Results: The results suggest that the indirect effects of social class on survival are substantial and negative (-0.23 overall). In addition to the substantial direct effect of this variable (-0.60), its indirect effects account for more than one quarter of the total effect. The two main pathways for this indirect effect, via emergency admission (-0.12), on the one hand, and hospital caseload, on the other, (-0.10) are of similar size. Conclusions: The discrete-time survival model provides an attractive way of integrating time-to-event data within the field of Structural Equation Modelling. The authors demonstrate the efficacy of this approach in identifying complex causal pathways that mediate the effects of a socio-economic baseline covariate on the hazard of death from colon cancer. The results show that this approach has the potential to shed light on a class of research questions which is of particular relevance in health research. en
dc.description.sponsorship Irish Cancer Society research (grant HIC12COM) en
dc.format.mimetype application/pdf en
dc.language.iso en en
dc.publisher BioMed Central en
dc.relation.uri https://bmcmedresmethodol.biomedcentral.com/articles/10.1186/s12874-016-0130-6
dc.rights © 2016, Pratschke et al. Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. en
dc.rights.uri https://creativecommons.org/licenses/by/4.0/ en
dc.subject Causal modelling en
dc.subject Mediation analysis en
dc.subject Social inequalities en
dc.subject Discrete-time survival model en
dc.subject Structural equation modelling en
dc.subject Deprivation index en
dc.subject Ireland en
dc.subject Colon cancer en
dc.title Mechanisms and mediation in survival analysis: Towards an integrated analytical framework en
dc.type Article (peer-reviewed) en
dc.internal.authorcontactother Harry Comber, Epidemiology and Public Health, University College Cork, Cork, Ireland +353-21-490-3000 E-mail: h.comber@ucc.ie en
dc.internal.availability Full text available en
dc.description.version Published Version en
dc.contributor.funder Irish Cancer Society en
dc.description.status Peer reviewed en
dc.identifier.journaltitle BMC Medical Research Methodology en
dc.internal.IRISemailaddress h.comber@ucc.ie en
dc.identifier.articleid 27


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© 2016, Pratschke et al. Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. Except where otherwise noted, this item's license is described as © 2016, Pratschke et al. Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
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