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Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/18701

Title: Comparison of risks of cardiovascular events in the elderly using standard survival analysis and multiple-events and recurrent-events methods
Authors: Ip, Edward H.
Efendi, Achmad
Molenberghs, Geert
Bertoni, Alain G.
Issue Date: 2015
Abstract: Background: Epidemiological studies about cardiovascular diseases often rely on methods based on time-to-first-event for data analysis. Without taking into account multiple event-types and the recurrency of a specific cardiovascular event, this approach may underestimate the overall cardiovascular burden of some risk factors, if that is the goal of the study. Methods: In this study we compare four different statistical approaches, all based on the Weibull distribution family of survival model, in analyzing cardiovascular risk factors. We use data from the Cardiovascular Health Study as illustration. The four models respectively are time-to-first-event only, recurrent-events only, multiple-event-types only, and joint recurrent and multiple-event-type models. Results: Although the four models produce consistent results regarding the significance of the risk factors, the magnitude of the hazard ratios and their confidence intervals are different. The joint model produces hazard ratios that are substantially higher than the time-to-first-event model especially for the risk factors of smoking and diabetes. Conclusion: Our findings suggest that for people with diabetes and are currently smoking, the overall cardiovascular burden of these risk factors would be substantially higher than that estimated using time-to-first-event method.
Notes: [Ip, Edward H.] Wake Forest Sch Med, Dept Biostat Sci, Winston Salem, NC 27157 USA. [Efendi, Achmad] Univ Brawijaya, Dept Math, Programs Stat, Malang 65145, Indonesia. [Molenberghs, Geert] Univ Hasselt, I BioStat, Hasselt, Belgium. [Molenberghs, Geert] Katholieke Univ Leuven, Hasselt, Belgium. [Bertoni, Alain G.] Wake Forest Sch Med, Dept Epidemiol & Prevent, Winston Salem, NC 27157 USA. eip@wakehealth.edu
URI: http://hdl.handle.net/1942/18701
DOI: 10.1186/s12874-015-0004-3
ISI #: 000351198800001
ISSN: 1471-2288
Category: A1
Type: Journal Contribution
Validation: ecoom, 2016
Appears in Collections: Research publications

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