Mechanisms and mediation in survival analysis: towards an integrated analytical framework.
Authors
Haase, TrutzComber, Harry
Sharp, Linda
de Camargo Cancela, Marianna
Johnson, Howard
Pratschke, Jonathan

Issue Date
2016-02-29Keywords
RESEARCHHEALTH OUTCOMES
MeSH
Age FactorsAged
Cause of Death
Colonic Neoplasms
Female
Humans
Integrated Advanced Information Management Systems
Male
Middle Aged
Models, Statistical
Negotiating
Proportional Hazards Models
Sensitivity and Specificity
Sex Factors
Survival Analysis
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Mechanisms and mediation in survival analysis: towards an integrated analytical framework. 2016, 16:27 BMC Med Res MethodolJournal
BMC medical research methodologyDOI
10.1186/s12874-016-0130-6PubMed ID
26927506Abstract
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.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.
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.
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.
Item Type
ArticleLanguage
enISSN
1471-2288ae974a485f413a2113503eed53cd6c53
10.1186/s12874-016-0130-6
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