Mediation analysis with a time-to-event outcome: a review of use and reporting in healthcare research

Background Mediation analysis tests whether the relationship between two variables is explained by a third intermediate variable. We sought to describe the usage and reporting of mediation analysis with time-to-event outcomes in published healthcare research. Methods A systematic search of Medline,...

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Veröffentlicht in:BMC medical research methodology Jg. 18; H. 1; S. 118 - 12
Hauptverfasser: Lapointe-Shaw, Lauren, Bouck, Zachary, Howell, Nicholas A., Lange, Theis, Orchanian-Cheff, Ani, Austin, Peter C., Ivers, Noah M., Redelmeier, Donald A., Bell, Chaim M.
Format: Journal Article
Sprache:Englisch
Veröffentlicht: London BioMed Central 29.10.2018
BioMed Central Ltd
Springer Nature B.V
BMC
Schlagworte:
Blindness
Counterfactuals
Data analysis
Data Interpretation, Statistical
Delivery of Health Care - methods
Delivery of Health Care - statistics & numerical data
Effect Modifier, Epidemiologic
Epidemiology
Event history analysis
Health Sciences
Health Services Research - methods
Health Services Research - statistics & numerical data
Humans
Indirect effect
Mediating effects (Research)
Mediation
Mediation analysis, Survival, Time-to-event, Methodology
Medical research
Medicine
Medicine & Public Health
Medicine, Experimental
Methods
Mortality
Outcome and process assessment (Health Care)
Outcome Assessment (Health Care) - methods
Outcome Assessment (Health Care) - statistics & numerical data
Pain
Proportional Hazards Models
Reporting
Research Article
Statistical Theory and Methods
statistics and modelling
Statistics for Life Sciences
Survival Analysis
Systematic review
Theory of Medicine/Bioethics
Time Factors
Variables
Visual impairment
Mediation analysis, Survival, Time-to-event, Methodology
Indirect effect
Counterfactuals
Reporting
Mediation
ISSN:1471-2288, 1471-2288
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Zusammenfassung:Background Mediation analysis tests whether the relationship between two variables is explained by a third intermediate variable. We sought to describe the usage and reporting of mediation analysis with time-to-event outcomes in published healthcare research. Methods A systematic search of Medline, Embase, and Web of Science was executed in December 2016 to identify applications of mediation analysis to healthcare research involving a clinically relevant time-to-event outcome. We summarized usage over time and reporting of important methodological characteristics. Results We included 149 primary studies, published from 1997 to 2016. Most studies were published after 2011 ( n  = 110, 74%), and the annual number of studies nearly doubled in the last year (from n  = 21 to n  = 40). A traditional approach (causal steps or change in coefficient) was most commonly taken ( n  = 87, 58%), and the majority of studies ( n  = 114, 77%) used a Cox Proportional Hazards regression for the outcome. Few studies ( n  = 52, 35%) mentioned any of the assumptions or limitations fundamental to a causal interpretation of mediation analysis. Conclusion There is increasing use of mediation analysis with time-to-event outcomes. Current usage is limited by reliance on traditional methods and the Cox Proportional Hazards model, as well as low rates of reporting of underlying assumptions. There is a need for formal criteria to aid authors, reviewers, and readers reporting or appraising such studies.
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ISSN:1471-2288
1471-2288
DOI:10.1186/s12874-018-0578-7