Please use this identifier to cite or link to this item: http://hdl.handle.net/2381/32430
Title: Adjusting for measurement error in baseline prognostic biomarkers included in a time-to-event analysis: a joint modelling approach.
Authors: Crowther, Michael J.
Lambert, Paul C.
Abrams, Keith R.
First Published: 1-Dec-2013
Citation: BMC Medical Research Methodology, 2013, 13:146
Abstract: Background: Methodological development of joint models of longitudinal and survival data has been rapid in recent years; however, their full potential in applied settings are yet to be fully explored. We describe a novel use of a specific association structure, linking the two component models through the subject specific intercept, and thus extend joint models to account for measurement error in a biomarker, even when only the baseline value of the biomarker is of interest. This is a common occurrence in registry data sources, where often repeated measurements exist but are simply ignored. Methods: The proposed specification is evaluated through simulation and applied to data from the General Practice Research Database, investigating the association between baseline Systolic Blood Pressure (SBP) and the time-to-stroke in a cohort of obese patients with type 2 diabetes mellitus. Results: By directly modelling the longitudinal component we reduce bias in the hazard ratio for the effect of baseline SBP on the time-to-stroke, showing the large potential to improve on previous prognostic models which use only observed baseline biomarker values. Conclusions: The joint modelling of longitudinal and survival data is a valid approach to account for measurement error in the analysis of a repeatedly measured biomarker and a time-to-event. User friendly Stata software is provided.
DOI Link: 10.1186/1471-2288-13-146
ISSN: 1471-2288
eISSN: 1471-2288
Links: http://www.biomedcentral.com/1471-2288/13/146
http://hdl.handle.net/2381/32430
Version: Publisher Version
Status: Peer-reviewed
Type: Journal Article
Rights: © 2013 Crowther et al.; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Description: PMCID: PMC4219390
Appears in Collections:Published Articles, Dept. of Health Sciences

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