Meta-analysis of joint longitudinal and event-time outcomes

Sudell, ME ORCID: 0000-0002-7919-4981, Tudur Smith, C ORCID: 0000-0003-3051-1445 and Kolamunnage-Dona, R ORCID: 0000-0003-3886-6208
(2016) Meta-analysis of joint longitudinal and event-time outcomes. [Poster]

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Background: It is widely acknowledged that joint analysis of longitudinal and time-to-event data is preferable over separate longitudinal or time-to-event analyses as the joint approach can account for longitudinal measurement error, study dropout, and can produce less biased estimates [1]. However the literature focuses mainly on single study cases or doesn’t account for potential heterogeneity between studies or sites. In many situations, such as meta-analyses, it may be important to be able to account for this variability. Objectives: This investigation aims to assess the benefit of use of joint models compared to separate methods in meta-analyses. Methods: Joint longitudinal and time-to-event data were simulated under a range of associations, for high and low event rates, for 5 studies, under assumption of homogenous treatment effect or heterogeneous treatment effect across studies. A range of joint models, and separate longitudinal and survival models were fitted to each study within each simulation, and the results pooled using standard meta-analytic techniques. Estimates of the treatment affect, association parameters, bias, and coverage were output. Results: From the simulations, there appears to be a benefit for time-to-event coefficients to perform joint models during meta-analyses rather than separate analyses.

Item Type: Poster
Uncontrolled Keywords: Joint model, meta-analysis, longitudinal, time-to-event, simulation, multicentre
Depositing User: Symplectic Admin
Date Deposited: 01 Aug 2016 13:56
Last Modified: 03 Mar 2021 09:26