Investigation of 2-stage meta-analysis methods for joint longitudinal and time-to-event data through simulation and real data application.

ABSTRACT:

Background

Joint modelling of longitudinal and time-to-event data is often preferred over separate longitudinal or time-to-event analyses as it can account for study dropout, error in longitudinally measured covariates, and correlation between longitudinal and time-to-event outcomes. The joint modelling literature focuses mainly on the analysis of single studies with no methods currently available for the meta-analysis of joint model estimates from multiple studies.

Methods

We propose a 2-stage method for meta-analysis of joint model estimates. These methods are applied to the INDANA dataset to combine joint model estimates of systolic blood pressure with time to death, time to myocardial infarction, and time to stroke. Results are compared to meta-analyses of separate longi

SUBMITTER: Sudell M 

PROVIDER: S-EPMC5887954 | biostudies-literature | 2018 Apr

REPOSITORIES: biostudies-literature