Document Detail


Time-dependent study entries and exposures in cohort studies can easily be sources of different and avoidable types of bias.
MedLine Citation:
PMID:  23017635     Owner:  NLM     Status:  In-Data-Review    
Abstract/OtherAbstract:
OBJECTIVES: To display and discuss the reasons and consequences of length and time-dependent bias. They might occur in presence of a time-dependent study entry or a time-dependent exposure which might change from unexposed to exposed.
STUDY DESIGN AND SETTING: Recalling the popular study of Oscar nominees and using a real-data example from hospital epidemiology, we give innovative and easy-to-understand graphical presentations of how these biases corrupt the analyses via distorted time-at-risk. Cumulative hazard plots and Cox proportional hazards models were used. We are building bridges to medical disciplines such as critical care medicine, hepatology, pharmaco-epidemiology, transplantation medicine, neurology, gynecology and cardiology.
RESULTS: In presence of time-dependent bias, the hazard ratio (comparing exposed with unexposed) is artificially underestimated. The length bias leads to an artificial underestimation of the overall hazard. When both biases coexist it can lead to different directions of biased hazard ratios.
CONCLUSION: Since length and time-dependent bias might occur in several medical disciplines, we conclude that understanding and awareness are the best prevention of survival bias.
Authors:
Martin Wolkewitz; Arthur Allignol; Stephan Harbarth; Giulia de Angelis; Martin Schumacher; Jan Beyersmann
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Publication Detail:
Type:  Journal Article    
Journal Detail:
Title:  Journal of clinical epidemiology     Volume:  65     ISSN:  1878-5921     ISO Abbreviation:  J Clin Epidemiol     Publication Date:  2012 Nov 
Date Detail:
Created Date:  2012-09-28     Completed Date:  -     Revised Date:  -    
Medline Journal Info:
Nlm Unique ID:  8801383     Medline TA:  J Clin Epidemiol     Country:  United States    
Other Details:
Languages:  eng     Pagination:  1171-80     Citation Subset:  IM    
Copyright Information:
Copyright © 2012 Elsevier Inc. All rights reserved.
Affiliation:
Institute of Medical Biometry and Medical Informatics, University of Freiburg, Stefan-Meier-Strasse 26, 79104 Freiburg, Germany. Electronic address: wolke@imbi.uni-freiburg.de.
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