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Meta‐analysis of summary survival curve data
Author(s) -
Arends Lidia R.,
Hunink M. G. Myriam,
Stijnen Theo
Publication year - 2008
Publication title -
statistics in medicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.996
H-Index - 183
eISSN - 1097-0258
pISSN - 0277-6715
DOI - 10.1002/sim.3311
Subject(s) - univariate , random effects model , survival analysis , statistics , meta analysis , computer science , generalization , biometrics , multivariate statistics , econometrics , mathematics , medicine , artificial intelligence , mathematical analysis
The use of standard univariate fixed‐ and random‐effects models in meta‐analysis has become well known in the last 20 years. However, these models are unsuitable for meta‐analysis of clinical trials that present multiple survival estimates (usually illustrated by a survival curve) during a follow‐up period. Therefore, special methods are needed to combine the survival curve data from different trials in a meta‐analysis. For this purpose, only fixed‐effects models have been suggested in the literature. In this paper, we propose a multivariate random‐effects model for joint analysis of survival proportions reported at multiple time points and in different studies, to be combined in a meta‐analysis. The model could be seen as a generalization of the fixed‐effects model of Dear ( Biometrics 1994; 50 :989–1002). We illustrate the method by using a simulated data example as well as using a clinical data example of meta‐analysis with aggregated survival curve data. All analyses can be carried out with standard general linear MIXED model software. Copyright © 2008 John Wiley & Sons, Ltd.